somethingone/MULocBench · Datasets at Hugging Face

organization string	repo_name string	base_commit string	iss_html_url string	iss_label string	title string	body string	code null	pr_html_url string	commit_html_url null	file_loc string	own_code_loc list	ass_file_loc list	other_rep_loc list	analysis dict	loctype dict	iss_has_pr int64
scikit-learn	scikit-learn	559609fe98ec2145788133687e64a6e87766bc77	https://github.com/scikit-learn/scikit-learn/issues/25525	Bug module:feature_extraction	Extend SequentialFeatureSelector example to demonstrate how to use negative tol	### Describe the bug I utilized the SequentialFeatureSelector for feature selection in my code, with the direction set to "backward." The tolerance value is negative and the selection process stops when the decrease in the metric, AUC in this case, is less than the specified tolerance. Generally, increasing the number of features results in a higher AUC, but sacrificing some features, especially correlated ones that offer little contribution, can produce a pessimistic model with a lower AUC. The code worked as expected in sklearn 1.1.1, but when I updated to sklearn 1.2.1, I encountered the following error. ### Steps/Code to Reproduce ```python from sklearn.datasets import load_breast_cancer from sklearn.linear_model import LogisticRegression from sklearn.feature_selection import SequentialFeatureSelector from sklearn.preprocessing import StandardScaler from sklearn.pipeline import Pipeline X, y = load_breast_cancer(return_X_y=True) TOL = -0.001 feature_selector = SequentialFeatureSelector( LogisticRegression(max_iter=1000), n_features_to_select="auto", direction="backward", scoring="roc_auc", tol=TOL ) pipe = Pipeline( [('scaler', StandardScaler()), ('feature_selector', feature_selector), ('log_reg', LogisticRegression(max_iter=1000))] ) if __name__ == "__main__": pipe.fit(X, y) print(pipe['log_reg'].coef_[0]) ``` ### Expected Results ``` $ python sfs_tol.py [-2.0429818 0.5364346 -1.35765488 -2.85009904 -2.84603016] ``` ### Actual Results ```python-traceback $ python sfs_tol.py Traceback (most recent call last): File "/home/modelling/users-workspace/nsofinij/lab/open-source/sfs_tol.py", line 28, in <module> pipe.fit(X, y) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/pipeline.py", line 401, in fit Xt = self._fit(X, y, *fit_params_steps) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/pipeline.py", line 359, in _fit X, fitted_transformer = fit_transform_one_cached( File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/joblib/memory.py", line 349, in __call__ return self.func(args, kwargs) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/pipeline.py", line 893, in _fit_transform_one res = transformer.fit_transform(X, y, fit_params) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/utils/_set_output.py", line 142, in wrapped data_to_wrap = f(self, X, args, kwargs) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/base.py", line 862, in fit_transform return self.fit(X, y, *fit_params).transform(X) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/feature_selection/_sequential.py", line 201, in fit self._validate_params() File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/base.py", line 581, in _validate_params validate_parameter_constraints( File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/utils/_param_validation.py", line 97, in validate_parameter_constraints raise InvalidParameterError( sklearn.utils._param_validation.InvalidParameterError: The 'tol' parameter of SequentialFeatureSelector must be None or a float in the range (0, inf). Got -0.001 instead. ``` ### Versions ```shell System: python: 3.10.8 \| packaged by conda-forge \| (main, Nov 22 2022, 08:26:04) [GCC 10.4.0] executable: /home/modelling/opt/anaconda3/envs/py310/bin/python machine: Linux-4.14.301-224.520.amzn2.x86_64-x86_64-with-glibc2.26 Python dependencies: sklearn: 1.2.1 pip: 23.0 setuptools: 66.1.1 numpy: 1.24.1 scipy: 1.10.0 Cython: None pandas: 1.5.3 matplotlib: 3.6.3 joblib: 1.2.0 threadpoolctl: 3.1.0 Built with OpenMP: True threadpoolctl info: user_api: openmp internal_api: openmp prefix: libgomp filepath: /home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/scikit_learn.libs/libgomp-a34b3233.so.1.0.0 version: None num_threads: 64 user_api: blas internal_api: openblas prefix: libopenblas filepath: /home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/numpy.libs/libopenblas64_p-r0-15028c96.3.21.so version: 0.3.21 threading_layer: pthreads architecture: SkylakeX num_threads: 64 user_api: blas internal_api: openblas prefix: libopenblas filepath: /home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/scipy.libs/libopenblasp-r0-41284840.3.18.so version: 0.3.18 threading_layer: pthreads architecture: SkylakeX num_threads: 64 ```	null	https://github.com/scikit-learn/scikit-learn/pull/26205	null	{'base_commit': '559609fe98ec2145788133687e64a6e87766bc77', 'files': [{'path': 'examples/feature_selection/plot_select_from_model_diabetes.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [145], 'mod': [123, 124, 125]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "examples/feature_selection/plot_select_from_model_diabetes.py" ], "doc": [], "test": [], "config": [], "asset": [] }	null
pallets	flask	cb94f4c5d3d4e1797207fd03d20d06c7bc0d05b4	https://github.com/pallets/flask/issues/2264	cli	Handle app factory in FLASK_APP	`FLASK_APP=myproject.app:create_app('dev')` [ Gunicorn does this with `eval`](https://github.com/benoitc/gunicorn/blob/fbd151e9841e2c87a18512d71475bcff863a5171/gunicorn/util.py#L364), which I'm not super happy with. Instead, we could use `literal_eval` to allow a simple list of arguments. The line should never be so complicated that `eval` would be necessary anyway. ~~~python # might need to fix this regex m = re.search(r'(\w+)(\(.\))', app_obj) if m: app = getattr(mod, m.group(1))(literal_eval(m.group(2))) ~~~	null	https://github.com/pallets/flask/pull/2326	null	{'base_commit': 'cb94f4c5d3d4e1797207fd03d20d06c7bc0d05b4', 'files': [{'path': 'flask/cli.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [11, 12]}, "(None, 'find_best_app', 32)": {'mod': [58, 62, 69, 71]}, "(None, 'call_factory', 82)": {'mod': [82, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93]}, "(None, 'locate_app', 125)": {'mod': [151, 153, 154, 155, 156, 158]}}}, {'path': 'tests/test_cli.py', 'status': 'modified', 'Loc': {"(None, 'test_locate_app', 148)": {'add': [152], 'mod': [154, 155, 156, 157, 158, 159, 160, 161]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "flask/cli.py" ], "doc": [], "test": [ "tests/test_cli.py" ], "config": [], "asset": [] }	1
localstack	localstack	737ca72b7bce6e377dd6876eacee63338fa8c30c	https://github.com/localstack/localstack/issues/894		ERROR:localstack.services.generic_proxy: Error forwarding request:	Starting local dev environment. CTRL-C to quit. Starting mock API Gateway (http port 4567)... Starting mock DynamoDB (http port 4569)... Starting mock SES (http port 4579)... Starting mock Kinesis (http port 4568)... Starting mock Redshift (http port 4577)... Starting mock S3 (http port 4572)... Starting mock CloudWatch (http port 4582)... Starting mock CloudFormation (http port 4581)... Starting mock SSM (http port 4583)... Starting mock SQS (http port 4576)... Starting local Elasticsearch (http port 4571)... Starting mock SNS (http port 4575)... Starting mock DynamoDB Streams service (http port 4570)... Starting mock Firehose service (http port 4573)... Starting mock Route53 (http port 4580)... Starting mock ES service (http port 4578)... Starting mock Lambda service (http port 4574)... 2018-08-11T13:33:08:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d442415d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d442415d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) 2018-08-11T13:34:08:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425fa10>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425fa10>: Failed to establish a new connection: [Errno 111] Connection refused',)) 2018-08-11T13:35:09:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4429c3d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4429c3d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) 2018-08-11T13:36:09:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425f910>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425f910>: Failed to establish a new connection: [Errno 111] Connection refused',))	null	https://github.com/localstack/localstack/pull/1526	null	{'base_commit': '737ca72b7bce6e377dd6876eacee63338fa8c30c', 'files': [{'path': 'README.md', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [186]}}}, {'path': 'localstack/config.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [14]}}}, {'path': 'localstack/services/kinesis/kinesis_starter.py', 'status': 'modified', 'Loc': {"(None, 'start_kinesis', 14)": {'add': [17], 'mod': [14, 23, 24]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "localstack/config.py", "localstack/services/kinesis/kinesis_starter.py" ], "doc": [ "README.md" ], "test": [], "config": [], "asset": [] }	1
huggingface	transformers	d2871b29754abd0f72cf42c299bb1c041519f7bc	https://github.com/huggingface/transformers/issues/30		[Feature request] Add example of finetuning the pretrained models on custom corpus		null	https://github.com/huggingface/transformers/pull/25107	null	{'base_commit': 'd2871b29754abd0f72cf42c299bb1c041519f7bc', 'files': [{'path': 'src/transformers/modeling_utils.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [75, 108]}, "('PreTrainedModel', 'from_pretrained', 1959)": {'add': [2227]}, "(None, 'load_state_dict', 442)": {'mod': [461]}, "('PreTrainedModel', '_load_pretrained_model', 3095)": {'mod': [3183, 3388, 3389, 3390, 3391, 3392, 3393, 3394, 3395, 3396, 3397, 3398, 3399, 3400, 3401, 3402, 3403, 3404]}}}, {'path': 'src/transformers/trainer.py', 'status': 'modified', 'Loc': {"('Trainer', '__init__', 313)": {'mod': [468, 469, 470]}, "('Trainer', '_wrap_model', 1316)": {'mod': [1382, 1385, 1387]}, "('Trainer', 'train', 1453)": {'mod': [1520]}, "('Trainer', '_inner_training_loop', 1552)": {'mod': [1654]}, "('Trainer', 'create_accelerator_and_postprocess', 3866)": {'mod': [3889]}}}, {'path': 'src/transformers/training_args.py', 'status': 'modified', 'Loc': {"('TrainingArguments', None, 158)": {'add': [464], 'mod': [439, 442, 445, 457]}, "('TrainingArguments', '__post_init__', 1221)": {'add': [1522, 1524, 1585], 'mod': [1529, 1530, 1531, 1533, 1534, 1535, 1536, 1537, 1543, 1544, 1547, 1548, 1550, 1551, 1555, 1556, 1558, 1559, 1560, 1589, 1591, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1602]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "src/transformers/trainer.py", "src/transformers/modeling_utils.py", "src/transformers/training_args.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
pandas-dev	pandas	51a70dcb7133bc7cb8e6bea5da39a2cf58fa8319	https://github.com/pandas-dev/pandas/issues/11080	Indexing Performance	PERF: checking is_monotonic_increasing/decreasing before sorting on an index	We don't keep the sortedness state in an index per-se, but it is rather cheap to check - `is_monotonic_increasing` or `is_monotonic_decreasing` on a reg-index - MultiIndex should check `is_lexsorted` (this might be done already) ``` In [8]: df = DataFrame(np.random.randn(1000000,2),columns=list('AB')) In [9]: %timeit df.sort_index() 10 loops, best of 3: 37.1 ms per loop In [10]: %timeit -n 1 -r 1 df.index.is_monotonic_increasing 1 loops, best of 1: 2.01 ms per loop In [11]: %timeit -n 1 -r 1 df.index.is_monotonic_increasin^C KeyboardInterrupt In [11]: %timeit df.set_index('A').sort_index() 10 loops, best of 3: 175 ms per loop In [12]: %timeit -n 1 -r 1 df.set_index('A').index.is_monotonic_increasing 1 loops, best of 1: 9.54 ms per loop ```	null	https://github.com/pandas-dev/pandas/pull/11294	null	{'base_commit': '51a70dcb7133bc7cb8e6bea5da39a2cf58fa8319', 'files': [{'path': 'asv_bench/benchmarks/frame_methods.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [932]}}}, {'path': 'doc/source/whatsnew/v0.17.1.txt', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [54]}}}, {'path': 'pandas/core/frame.py', 'status': 'modified', 'Loc': {"('DataFrame', 'sort_index', 3126)": {'add': [3159]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "pandas/core/frame.py", "asv_bench/benchmarks/frame_methods.py" ], "doc": [ "doc/source/whatsnew/v0.17.1.txt" ], "test": [], "config": [], "asset": [] }	1
zylon-ai	private-gpt	fdb45741e521d606b028984dbc2f6ac57755bb88	https://github.com/zylon-ai/private-gpt/issues/10		Suggestions for speeding up ingestion?	I presume I must be doing something wrong, as it is taking hours to ingest a 500kbyte text on an i9-12900 with 128GB. In fact it's not even done yet. Using models are recommended. Help? Thanks Some output: llama_print_timings: load time = 674.34 ms llama_print_timings: sample time = 0.00 ms / 1 runs ( 0.00 ms per run) llama_print_timings: prompt eval time = 12526.78 ms / 152 tokens ( 82.41 ms per token) llama_print_timings: eval time = 157.46 ms / 1 runs ( 157.46 ms per run) llama_print_timings: total time = 12715.48 ms	null	https://github.com/zylon-ai/private-gpt/pull/224	null	{'base_commit': 'fdb45741e521d606b028984dbc2f6ac57755bb88', 'files': [{'path': 'README.md', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [4, 15, 17, 23, 25, 28, 58, 62, 86]}}}, {'path': 'example.env', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [4], 'mod': [2]}}}, {'path': 'ingest.py', 'status': 'modified', 'Loc': {"(None, 'main', 71)": {'add': [79], 'mod': [75, 76, 81, 84, 87, 90]}, '(None, None, None)': {'mod': [22]}}}, {'path': 'privateGPT.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [3, 11]}, "(None, 'main', 20)": {'mod': [21, 22]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "ingest.py", "privateGPT.py" ], "doc": [ "README.md" ], "test": [], "config": [ "example.env" ], "asset": [] }	1
huggingface	transformers	9fef668338b15e508bac99598dd139546fece00b	https://github.com/huggingface/transformers/issues/9		Crash at the end of training	Hi, I tried running the Squad model this morning (on a single GPU with gradient accumulation over 3 steps) but after 3 hours of training, my job failed with the following output: I was running the code, unmodified, from commit 3bfbc21376af691b912f3b6256bbeaf8e0046ba8 Is this an issue you know about? ``` 11/08/2018 17:50:03 - INFO - __main__ - device cuda n_gpu 1 distributed training False 11/08/2018 17:50:18 - INFO - __main__ - * Example * 11/08/2018 17:50:18 - INFO - __main__ - unique_id: 1000000000 11/08/2018 17:50:18 - INFO - __main__ - example_index: 0 11/08/2018 17:50:18 - INFO - __main__ - doc_span_index: 0 11/08/2018 17:50:18 - INFO - __main__ - tokens: [CLS] to whom did the virgin mary allegedly appear in 1858 in lou ##rdes france ? [SEP] architectural ##ly , the school has a catholic character . atop the main building ' s gold dome is a golden statue of the virgin mary . immediately in front of the main building and facing it , is a copper statue of christ with arms up ##rai ##sed with the legend " ve ##ni ##te ad me om ##nes " . next to the main building is the basilica of the sacred heart . immediately behind the basilica is the gr ##otto , a marian place of prayer and reflection . it is a replica of the gr ##otto at lou ##rdes , france where the virgin mary reputed ##ly appeared to saint bern ##ade ##tte so ##ub ##iro ##us in 1858 . at the end of the main drive ( and in a direct line that connects through 3 statues and the gold dome ) , is a simple , modern stone statue of mary . [SEP] 11/08/2018 17:50:18 - INFO - __main__ - token_to_orig_map: 17:0 18:0 19:0 20:1 21:2 22:3 23:4 24:5 25:6 26:6 27:7 28:8 29:9 30:10 31:10 32:10 33:11 34:12 35:13 36:14 37:15 38:16 39:17 40:18 41:19 42:20 43:20 44:21 45:22 46:23 47:24 48:25 49:26 50:27 51:28 52:29 53:30 54:30 55:31 56:32 57:33 58:34 59:35 60:36 61:37 62:38 63:39 64:39 65:39 66:40 67:41 68:42 69:43 70:43 71:43 72:43 73:44 74:45 75:46 76:46 77:46 78:46 79:47 80:48 81:49 82:50 83:51 84:52 85:53 86:54 87:55 88:56 89:57 90:58 91:58 92:59 93:60 94:61 95:62 96:63 97:64 98:65 99:65 100:65 101:66 102:67 103:68 104:69 105:70 106:71 107:72 108:72 109:73 110:74 111:75 112:76 113:77 114:78 115:79 116:79 117:80 118:81 119:81 120:81 121:82 122:83 123:84 124:85 125:86 126:87 127:87 128:88 129:89 130:90 131:91 132:91 133:91 134:92 135:92 136:92 137:92 138:93 139:94 140:94 141:95 142:96 143:97 144:98 145:99 146:100 147:101 148:102 149:102 150:103 151:104 152:105 153:106 154:107 155:108 156:109 157:110 158:111 159:112 160:113 161:114 162:115 163:115 164:115 165:116 166:117 167:118 168:118 169:119 170:120 171:121 172:122 173:123 174:123 11/08/2018 17:50:18 - INFO - __main__ - token_is_max_context: 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 11/08/2018 17:50:18 - INFO - __main__ - input_ids: 101 2000 3183 2106 1996 6261 2984 9382 3711 1999 8517 1999 10223 26371 2605 1029 102 6549 2135 1010 1996 2082 2038 1037 3234 2839 1012 10234 1996 2364 2311 1005 1055 2751 8514 2003 1037 3585 6231 1997 1996 6261 2984 1012 3202 1999 2392 1997 1996 2364 2311 1998 5307 2009 1010 2003 1037 6967 6231 1997 4828 2007 2608 2039 14995 6924 2007 1996 5722 1000 2310 3490 2618 4748 2033 18168 5267 1000 1012 2279 2000 1996 2364 2311 2003 1996 13546 1997 1996 6730 2540 1012 3202 2369 1996 13546 2003 1996 24665 23052 1010 1037 14042 2173 1997 7083 1998 9185 1012 2009 2003 1037 15059 1997 1996 24665 23052 2012 10223 26371 1010 2605 2073 1996 6261 2984 22353 2135 2596 2000 3002 16595 9648 4674 2061 12083 9711 2271 1999 8517 1012 2012 1996 2203 1997 1996 2364 3298 1006 1998 1999 1037 3622 2240 2008 8539 2083 1017 11342 1998 1996 2751 8514 1007 1010 2003 1037 3722 1010 2715 2962 6231 1997 2984 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11/08/2018 17:50:18 - INFO - __main__ - input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... [truncated] ... Iteration: 100%\|█████████▉\| 29314/29324 [3:27:55<00:04, 2.36it/s][A Iteration: 100%\|█████████▉\| 29315/29324 [3:27:55<00:03, 2.44it/s][A Iteration: 100%\|█████████▉\| 29316/29324 [3:27:56<00:03, 2.26it/s][A Iteration: 100%\|█████████▉\| 29317/29324 [3:27:56<00:02, 2.35it/s][A Iteration: 100%\|█████████▉\| 29318/29324 [3:27:56<00:02, 2.44it/s][A Iteration: 100%\|█████████▉\| 29319/29324 [3:27:57<00:02, 2.25it/s][A Iteration: 100%\|█████████▉\| 29320/29324 [3:27:57<00:01, 2.35it/s][A Iteration: 100%\|█████████▉\| 29321/29324 [3:27:58<00:01, 2.41it/s][A Iteration: 100%\|█████████▉\| 29322/29324 [3:27:58<00:00, 2.25it/s][A Iteration: 100%\|█████████▉\| 29323/29324 [3:27:59<00:00, 2.36it/s][ATraceback (most recent call last): File "code/run_squad.py", line 929, in <module> main() File "code/run_squad.py", line 862, in main loss = model(input_ids, segment_ids, input_mask, start_positions, end_positions) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 477, in __call__ result = self.forward(input, kwargs) File "/0x0d4ff90d01fa4168983197b17d73bb0c_dependencies/code/modeling.py", line 467, in forward start_loss = loss_fct(start_logits, start_positions) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 477, in __call__ result = self.forward(input, **kwargs) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/loss.py", line 862, in forward ignore_index=self.ignore_index, reduction=self.reduction) File "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py", line 1550, in cross_entropy return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction) File "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py", line 1403, in nll_loss if input.size(0) != target.size(0): RuntimeError: dimension specified as 0 but tensor has no dimensions Exception ignored in: <bound method tqdm.__del__ of Iteration: 100%\|█████████▉\| 29323/29324 [3:27:59<00:00, 2.36it/s]> Traceback (most recent call last): File "/usr/local/lib/python3.6/dist-packages/tqdm/_tqdm.py", line 931, in __del__ self.close() File "/usr/local/lib/python3.6/dist-packages/tqdm/_tqdm.py", line 1133, in close self._decr_instances(self) File "/usr/local/lib/python3.6/dist-packages/tqdm/_tqdm.py", line 496, in _decr_instances cls.monitor.exit() File "/usr/local/lib/python3.6/dist-packages/tqdm/_monitor.py", line 52, in exit self.join() File "/usr/lib/python3.6/threading.py", line 1053, in join raise RuntimeError("cannot join current thread") RuntimeError: cannot join current thread ```	null	https://github.com/huggingface/transformers/pull/16310	null	{'base_commit': '9fef668338b15e508bac99598dd139546fece00b', 'files': [{'path': 'tests/big_bird/test_modeling_big_bird.py', 'status': 'modified', 'Loc': {"('BigBirdModelTester', '__init__', 47)": {'mod': [73]}, "('BigBirdModelTest', 'test_fast_integration', 561)": {'mod': [584]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [], "doc": [], "test": [ "tests/big_bird/test_modeling_big_bird.py" ], "config": [], "asset": [] }	1
psf	requests	ccabcf1fca906bfa6b65a3189c1c41061e6c1042	https://github.com/psf/requests/issues/3698		AttributeError: 'NoneType' object has no attribute 'read'	Hello :) After a recent upgrade for our [coala](https://github.com/coala/coala) project to `requests` 2.12.1 we encounter an exception in our test suites which seems to be caused by `requests`. Build: https://ci.appveyor.com/project/coala/coala-bears/build/1.0.3537/job/1wm7b4u9yhgkxkgn Relevant part: ``` ================================== FAILURES =================================== _________________ InvalidLinkBearTest.test_redirect_threshold _________________ self = <tests.general.InvalidLinkBearTest.InvalidLinkBearTest testMethod=test_redirect_threshold> def test_redirect_threshold(self): long_url_redirect = """ https://bitbucket.org/api/301 https://bitbucket.org/api/302 """.splitlines() short_url_redirect = """ http://httpbin.org/status/301 """.splitlines() self.assertResult(valid_file=long_url_redirect, invalid_file=short_url_redirect, > settings={'follow_redirects': 'yeah'}) tests\general\InvalidLinkBearTest.py:157: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests\general\InvalidLinkBearTest.py:75: in assertResult out = list(uut.run("valid", valid_file, settings)) bears\general\InvalidLinkBear.py:80: in run file, timeout, link_ignore_regex): bears\general\InvalidLinkBear.py:53: in find_links_in_file code = InvalidLinkBear.get_status_code(link, timeout) bears\general\InvalidLinkBear.py:37: in get_status_code timeout=timeout).status_code C:\Python34\lib\site-packages\requests\api.py:96: in head return request('head', url, kwargs) C:\Python34\lib\site-packages\requests\api.py:56: in request return session.request(method=method, url=url, kwargs) C:\Python34\lib\site-packages\requests\sessions.py:488: in request resp = self.send(prep, send_kwargs) C:\Python34\lib\site-packages\requests_mock\mocker.py:69: in _fake_send return self._real_send(session, request, **kwargs) C:\Python34\lib\site-packages\requests\sessions.py:641: in send r.content C:\Python34\lib\site-packages\requests\models.py:772: in content self._content = bytes().join(self.iter_content(CONTENT_CHUNK_SIZE)) or bytes() _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ def generate(): # Special case for urllib3. if hasattr(self.raw, 'stream'): try: for chunk in self.raw.stream(chunk_size, decode_content=True): yield chunk except ProtocolError as e: raise ChunkedEncodingError(e) except DecodeError as e: raise ContentDecodingError(e) except ReadTimeoutError as e: raise ConnectionError(e) else: # Standard file-like object. while True: > chunk = self.raw.read(chunk_size) E AttributeError: 'NoneType' object has no attribute 'read' C:\Python34\lib\site-packages\requests\models.py:705: AttributeError ``` happens on Windows and Linux. Thanks in advance :)	null	https://github.com/psf/requests/pull/3718	null	{'base_commit': 'ccabcf1fca906bfa6b65a3189c1c41061e6c1042', 'files': [{'path': 'requests/models.py', 'status': 'modified', 'Loc': {"('Response', 'content', 763)": {'mod': [772]}}}, {'path': 'tests/test_requests.py', 'status': 'modified', 'Loc': {"('TestRequests', None, 55)": {'add': [1096]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "requests/models.py" ], "doc": [], "test": [ "tests/test_requests.py" ], "config": [], "asset": [] }	1
AntonOsika	gpt-engineer	fc805074be7b3b507bc1699e537f9b691c6f91b9	https://github.com/AntonOsika/gpt-engineer/issues/674	bug documentation	ModuleNotFoundError: No module named 'tkinter'	Bug description When running `gpt-engineer --improve` (using the recent version from PyPI), I get the following output: ``` $ gpt-engineer --improve Traceback (most recent call last): File "/home/.../.local/bin/gpt-engineer", line 5, in <module> from gpt_engineer.main import app File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/main.py", line 12, in <module> from gpt_engineer.collect import collect_learnings File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/collect.py", line 5, in <module> from gpt_engineer import steps File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/steps.py", line 19, in <module> from gpt_engineer.file_selector import FILE_LIST_NAME, ask_for_files File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/file_selector.py", line 4, in <module> import tkinter as tk ModuleNotFoundError: No module named 'tkinter' ``` Expected behavior No error. In https://github.com/AntonOsika/gpt-engineer/pull/465, no changes where made to the required packages, so tkinter might be added there. (Or made optional.) EDIT: The error happens always, regardless of the command line parameter.	null	https://github.com/AntonOsika/gpt-engineer/pull/675	null	{'base_commit': 'fc805074be7b3b507bc1699e537f9b691c6f91b9', 'files': [{'path': 'docs/installation.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [45]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "3", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [], "doc": [ "docs/installation.rst" ], "test": [], "config": [], "asset": [] }	1
pallets	flask	85dce2c836fe03aefc07b7f4e0aec575e170f1cd	https://github.com/pallets/flask/issues/593	blueprints	Nestable blueprints	I'd like to be able to register "sub-blueprints" using `Blueprint.register_blueprint(args, kwargs)`. This would register the nested blueprints with an app when the "parent" is registered with it. All parameters are preserved, other than `url_prefix`, which is handled similarly to in `add_url_rule`. A naíve implementation could look like this: ``` python class Blueprint(object): ... def register_blueprint(self, blueprint, options): def deferred(state): url_prefix = options.get('url_prefix') if url_prefix is None: url_prefix = blueprint.url_prefix if 'url_prefix' in options: del options['url_prefix'] state.app.register_blueprint(blueprint, url_prefix, *options) self.record(deferred) ```	null	https://github.com/pallets/flask/pull/3923	null	{'base_commit': '85dce2c836fe03aefc07b7f4e0aec575e170f1cd', 'files': [{'path': 'CHANGES.rst', 'status': 'modified', 'Loc': {'(None, None, 71)': {'add': [71]}}}, {'path': 'docs/blueprints.rst', 'status': 'modified', 'Loc': {'(None, None, 122)': {'add': [122]}}}, {'path': 'src/flask/app.py', 'status': 'modified', 'Loc': {"('Flask', '__call__', 1982)": {'add': [1987]}, "('Flask', 'update_template_context', 712)": {'mod': [726, 727, 728]}, "('Flask', 'register_blueprint', 971)": {'mod': [990, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1004]}, "('Flask', '_find_error_handler', 1230)": {'mod': [1238, 1239, 1240, 1241, 1242, 1243, 1244]}, "('Flask', 'preprocess_request', 1741)": {'mod': [1752, 1755, 1756, 1761, 1762]}, "('Flask', 'process_response', 1768)": {'mod': [1782, 1784, 1785]}, "('Flask', 'do_teardown_request', 1794)": {'mod': [1818, 1819, 1820]}}}, {'path': 'src/flask/blueprints.py', 'status': 'modified', 'Loc': {"('BlueprintSetupState', '__init__', 16)": {'add': [47]}, "('Blueprint', '__init__', 141)": {'add': [170]}, "('Blueprint', 'register', 213)": {'add': [225], 'mod': [281, 282, 286, 287, 288, 289, 290, 291, 292, 293]}, "('BlueprintSetupState', 'add_url_rule', 53)": {'mod': [71]}, "('Blueprint', None, 78)": {'mod': [213]}}}, {'path': 'tests/test_blueprints.py', 'status': 'modified', 'Loc': {"(None, 'test_app_url_processors', 828)": {'add': [852]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "src/flask/blueprints.py", "src/flask/app.py" ], "doc": [ "docs/blueprints.rst", "CHANGES.rst" ], "test": [ "tests/test_blueprints.py" ], "config": [], "asset": [] }	null
AUTOMATIC1111	stable-diffusion-webui	f92d61497a426a19818625c3ccdaae9beeb82b31	https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/14263	bug	[Bug]: KeyError: "do_not_save" when trying to save a prompt	### Is there an existing issue for this? - [X] I have searched the existing issues and checked the recent builds/commits ### What happened? When I try to save a prompt, it errors in the console saying ``` File "/home/ciel/stable-diffusion/stable-diffusion-webui/modules/styles.py", line 212, in save_styles style_paths.remove("do_not_save") KeyError: 'do_not_save' ``` and the file is not modified I manually commented it out and it doesn't seem to break anything, except that it is saved to styles.csv.csv instead of styles.csv ### Steps to reproduce the problem Try to save a prompt ### What should have happened? Save into style.csv with no error ### Sysinfo { "Platform": "Linux-6.6.4-zen1-1-zen-x86_64-with-glibc2.38", "Python": "3.11.4", "Version": "v1.7.0-RC-5-gf92d6149", "Commit": "f92d61497a426a19818625c3ccdaae9beeb82b31", "Script path": "/home/ciel/stable-diffusion/stable-diffusion-webui", "Data path": "/home/ciel/stable-diffusion/stable-diffusion-webui", "Extensions dir": "/home/ciel/stable-diffusion/stable-diffusion-webui/extensions", "Checksum": "e15aad6adb98a2a0ad13cad2b45b61b03565ef4f258783021da82b4ef7f37fa9", "Commandline": [ "launch.py" ], "Torch env info": { "torch_version": "2.2.0", "is_debug_build": "False", "cuda_compiled_version": "N/A", "gcc_version": "(GCC) 13.2.1 20230801", "clang_version": "16.0.6", "cmake_version": "version 3.26.4", "os": "Arch Linux (x86_64)", "libc_version": "glibc-2.38", "python_version": "3.11.4 (main, Jul 5 2023, 13:45:01) [GCC 11.2.0] (64-bit runtime)", "python_platform": "Linux-6.6.4-zen1-1-zen-x86_64-with-glibc2.38", "is_cuda_available": "True", 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"ftfy==6.1.3", "future==0.18.3", "fvcore==0.1.5.post20221221", "gdown==4.7.1", "gfpgan==1.3.8", "gitdb==4.0.11", "gitpython==3.1.32", "google-auth-oauthlib==1.1.0", "google-auth==2.25.1", "gradio-client==0.5.0", "gradio==3.41.2", "grpcio==1.60.0", "h11==0.12.0", "httpcore==0.15.0", "httpx==0.24.1", "huggingface-hub==0.19.4", "idna==3.4", "imageio==2.33.0", "importlib-metadata==7.0.0", "importlib-resources==6.1.1", "inflection==0.5.1", "iopath==0.1.9", "jinja2==3.1.2", "jsonmerge==1.8.0", "jsonschema-specifications==2023.11.2", "jsonschema==4.20.0", "kiwisolver==1.4.5", "kornia==0.6.7", "lark==1.1.2", "lazy-loader==0.3", "lightning-utilities==0.10.0", "llvmlite==0.41.1", "lmdb==1.4.1", "lpips==0.1.4", "lxml==4.9.3", "markdown==3.5.1", "markupsafe==2.1.3", "matplotlib==3.8.2", "mediapipe==0.10.8", "mpmath==1.2.1", "multidict==6.0.4", "networkx==3.0rc1", "numba==0.58.1", "numpy==1.23.5", "oauthlib==3.2.2", "omegaconf==2.2.3", "open-clip-torch==2.20.0", "opencv-contrib-python==4.8.1.78", "opencv-python==4.8.1.78", "orjson==3.9.10", "packaging==23.2", "pandas==2.1.4", "piexif==1.1.3", "pillow==9.5.0", "pip==23.1.2", "platformdirs==4.1.0", "portalocker==2.8.2", "protobuf==3.20.0", "psutil==5.9.5", "pyasn1-modules==0.3.0", "pyasn1==0.5.1", "pycparser==2.21", "pydantic==1.10.13", "pydub==0.25.1", "pyparsing==3.1.1", "pysocks==1.7.1", "python-dateutil==2.8.2", "python-multipart==0.0.6", "pytorch-lightning==1.9.4", "pytorch-triton-rocm==2.1.0+dafe145982", "pytz==2023.3.post1", "pywavelets==1.5.0", "pyyaml==6.0.1", "realesrgan==0.3.0", "referencing==0.32.0", "regex==2023.10.3", "reportlab==4.0.7", "requests-oauthlib==1.3.1", "requests==2.28.1", "resize-right==0.0.2", "rpds-py==0.13.2", "rsa==4.9", "safetensors==0.3.1", "scikit-image==0.21.0", "scipy==1.11.4", "semantic-version==2.10.0", "sentencepiece==0.1.99", "setuptools==65.5.0", "six==1.16.0", "smmap==5.0.1", "sniffio==1.3.0", "sounddevice==0.4.6", "soupsieve==2.5", "starlette==0.26.1", "svglib==1.5.1", "sympy==1.11.1", "tabulate==0.9.0", "tb-nightly==2.16.0a20231208", "tensorboard-data-server==0.7.2", "termcolor==2.4.0", "tf-keras-nightly==2.16.0.dev2023120810", "tifffile==2023.9.26", "timm==0.9.2", "tinycss2==1.2.1", "tokenizers==0.13.3", "tomesd==0.1.3", "tomli==2.0.1", "toolz==0.12.0", "torch==2.2.0.dev20231208+rocm5.6", "torchdiffeq==0.2.3", "torchmetrics==1.2.1", "torchsde==0.2.6", "torchvision==0.17.0.dev20231208+rocm5.6", "tqdm==4.66.1", "trampoline==0.1.2", "transformers==4.30.2", "typing-extensions==4.8.0", "tzdata==2023.3", "urllib3==1.26.13", "uvicorn==0.24.0.post1", "wcwidth==0.2.12", "webencodings==0.5.1", "websockets==11.0.3", "werkzeug==3.0.1", "yacs==0.1.8", "yapf==0.40.2", "yarl==1.9.4", "zipp==3.17.0" ] } ### What browsers do you use to access the UI ? Mozilla Firefox ### Console logs ```Shell ❯ ./webui.sh (base) ################################################################ Install script for stable-diffusion + Web UI Tested on Debian 11 (Bullseye) ################################################################ ################################################################ Running on ciel user ################################################################ ################################################################ Create and activate python venv ################################################################ ################################################################ Launching launch.py... ################################################################ Using TCMalloc: libtcmalloc_minimal.so.4 Python 3.11.4 (main, Jul 5 2023, 13:45:01) [GCC 11.2.0] Version: v1.7.0-RC-5-gf92d6149 Commit hash: f92d61497a426a19818625c3ccdaae9beeb82b31 Launching Web UI with arguments: no module 'xformers'. Processing without... no module 'xformers'. Processing without... No module 'xformers'. Proceeding without it. 2023-12-09 17:08:09,876 - ControlNet - INFO - ControlNet v1.1.422 ControlNet preprocessor location: /home/ciel/stable-diffusion/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/downloads 2023-12-09 17:08:09,921 - ControlNet - INFO - ControlNet v1.1.422 Loading weights [5493a0ec49] from /home/ciel/stable-diffusion/stable-diffusion-webui/models/Stable-diffusion/AOM3A1B_orangemixs.safetensors Running on local URL: http://127.0.0.1:7860 To create a public link, set `share=True` in `launch()`. Creating model from config: /home/ciel/stable-diffusion/stable-diffusion-webui/configs/v1-inference.yaml Startup time: 8.9s (prepare environment: 4.0s, import torch: 2.0s, import gradio: 0.5s, setup paths: 0.8s, other imports: 0.5s, load scripts: 0.4s, create ui: 0.4s, gradio launch: 0.2s). Loading VAE weights specified in settings: /home/ciel/stable-diffusion/stable-diffusion-webui/models/VAE/orangemix.vae.pt Applying attention optimization: Doggettx... done. Model loaded in 2.6s (load weights from disk: 0.6s, create model: 0.2s, apply weights to model: 1.4s, load VAE: 0.2s, calculate empty prompt: 0.1s). Traceback (most recent call last): File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/routes.py", line 488, in run_predict output = await app.get_blocks().process_api( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/blocks.py", line 1431, in process_api result = await self.call_function( ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/blocks.py", line 1103, in call_function prediction = await anyio.to_thread.run_sync( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/anyio/to_thread.py", line 33, in run_sync return await get_asynclib().run_sync_in_worker_thread( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread return await future ^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 807, in run result = context.run(func, args) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/utils.py", line 707, in wrapper response = f(args, *kwargs) ^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/modules/ui_prompt_styles.py", line 27, in save_style shared.prompt_styles.save_styles(shared.styles_filename) File "/home/ciel/stable-diffusion/stable-diffusion-webui/modules/styles.py", line 212, in save_styles style_paths.remove("do_not_save") KeyError: 'do_not_save' ``` ### Additional information I'm running dev branch due to the Navi3 bug, checking out master after launch seems to result in the same issue, but it could have just been jit-ed, didn't test very in-depth	null	https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14276	null	{'base_commit': 'f92d61497a426a19818625c3ccdaae9beeb82b31', 'files': [{'path': 'modules/styles.py', 'status': 'modified', 'Loc': {"('StyleDatabase', '__init__', 95)": {'mod': [101, 102, 103, 104]}, "('StyleDatabase', None, 94)": {'mod': [158, 159, 160, 161]}, "('StyleDatabase', 'get_style_paths', 158)": {'mod': [175, 177]}, "('StyleDatabase', 'save_styles', 195)": {'mod': [199, 200, 201, 202, 204, 205, 206, 207, 208, 209, 211, 212]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "modules/styles.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
home-assistant	core	c3e9c1a7e8fdc949b8e638d79ab476507ff92f18	https://github.com/home-assistant/core/issues/60067	integration: environment_canada by-code-owner	Environment Canada (EC) radar integration slowing Environment Canada servers	### The problem The `config_flow` change to the EC integration did not change the way the underlying radar retrieval works, but did enable radar for everyone. As a result the EC servers are getting far too many requests. We (the codeowners) have been working with EC to diagnose this issue and understand their concerns. We are doing two things (PR is in progress). Caching requests to the EC servers. Work so far shows that through caching we can reduce the number of requests by over 90%. This fix is in the integration dependency library. Second, we are creating the radar (camera) entity with `_attr_entity_registry_enabled_default = False` so that new radar entities are disabled by default. Many people use the integration for forecast only. Last, EC is putting a policy in place such that User Agent needs to be filled in to represent the calling library. ### What version of Home Assistant Core has the issue? 2021.12.0.dev0 ### What was the last working version of Home Assistant Core? _No response_ ### What type of installation are you running? Home Assistant Core ### Integration causing the issue Environment Canada ### Link to integration documentation on our website https://www.home-assistant.io/integrations/environment_canada/ ### Example YAML snippet _No response_ ### Anything in the logs that might be useful for us? _No response_ ### Additional information Quote from one of the email exchanges with EC: > What we observed is 1350 unique IP addresses using this code which made 23.5 million requests over 5 days. In order to respond to EC as quickly as possible we are asking for consideration to release the PR, when available, in the next dot release.	null	https://github.com/home-assistant/core/pull/60087	null	{'base_commit': 'c3e9c1a7e8fdc949b8e638d79ab476507ff92f18', 'files': [{'path': 'homeassistant/components/environment_canada/camera.py', 'status': 'modified', 'Loc': {"('ECCamera', '__init__', 49)": {'add': [57]}}}, {'path': 'homeassistant/components/environment_canada/manifest.json', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [5]}}}, {'path': 'requirements_all.txt', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [603]}}}, {'path': 'requirements_test_all.txt', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [372]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "homeassistant/components/environment_canada/camera.py", "homeassistant/components/environment_canada/manifest.json" ], "doc": [], "test": [], "config": [ "requirements_all.txt", "requirements_test_all.txt" ], "asset": [] }	1
abi	screenshot-to-code	939539611f0cad12056f7be78ef6b2128b90b779	https://github.com/abi/screenshot-to-code/issues/336	bug p2	Handle Nones in chunk.choices[0].delta	![WechatIMG434](https://github.com/abi/screenshot-to-code/assets/158557918/d2ddcd3e-f944-40cb-a74e-b54bec8938f4) There is a successful request for the openai interface, but it seems that no code is generated. backend-1 \| ERROR: Exception in ASGI application backend-1 \| Traceback (most recent call last): backend-1 \| File "/usr/local/lib/python3.12/site-packages/uvicorn/protocols/websockets/websockets_impl.py", line 250, in run_asgi backend-1 \| result = await self.app(self.scope, self.asgi_receive, self.asgi_send) backend-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 \| File "/usr/local/lib/python3.12/site-packages/uvicorn/middleware/proxy_headers.py", line 84, in __call__ backend-1 \| return await self.app(scope, receive, send) backend-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 \| File "/usr/local/lib/python3.12/site-packages/fastapi/applications.py", line 276, in __call__ backend-1 \| await super().__call__(scope, receive, send) backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/applications.py", line 122, in __call__ backend-1 \| await self.middleware_stack(scope, receive, send) backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/middleware/errors.py", line 149, in __call__ backend-1 \| await self.app(scope, receive, send) backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/middleware/cors.py", line 75, in __call__ backend-1 \| await self.app(scope, receive, send) backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/middleware/exceptions.py", line 79, in __call__ backend-1 \| raise exc backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/middleware/exceptions.py", line 68, in __call__ backend-1 \| await self.app(scope, receive, sender) backend-1 \| File "/usr/local/lib/python3.12/site-packages/fastapi/middleware/asyncexitstack.py", line 21, in __call__ backend-1 \| raise e backend-1 \| File "/usr/local/lib/python3.12/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__ backend-1 \| await self.app(scope, receive, send) backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/routing.py", line 718, in __call__ backend-1 \| await route.handle(scope, receive, send) backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/routing.py", line 341, in handle backend-1 \| await self.app(scope, receive, send) backend-1 \| File "/usr/local/lib/python3.12/site-packages/starlette/routing.py", line 82, in app backend-1 \| await func(session) backend-1 \| File "/usr/local/lib/python3.12/site-packages/fastapi/routing.py", line 289, in app backend-1 \| await dependant.call(**values) backend-1 \| File "/app/routes/generate_code.py", line 251, in stream_code backend-1 \| completion = await stream_openai_response( backend-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 \| File "/app/llm.py", line 62, in stream_openai_response backend-1 \| content = chunk.choices[0].delta.content or "" backend-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 \| AttributeError: 'NoneType' object has no attribute 'content' backend-1 \| INFO: connection closed	null	https://github.com/abi/screenshot-to-code/pull/341	null	{'base_commit': '939539611f0cad12056f7be78ef6b2128b90b779', 'files': [{'path': 'backend/llm.py', 'status': 'modified', 'Loc': {"(None, 'stream_openai_response', 32)": {'mod': [62, 63, 64]}}}, {'path': 'frontend/package.json', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [49]}}}, {'path': 'frontend/src/App.tsx', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [381]}}}, {'path': 'frontend/yarn.lock', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [5644, 5939]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "backend/llm.py", "frontend/src/App.tsx", "frontend/package.json" ], "doc": [], "test": [], "config": [ "frontend/yarn.lock" ], "asset": [] }	1
Significant-Gravitas	AutoGPT	bf895eb656dee9084273cd36395828bd06aa231d	https://github.com/Significant-Gravitas/AutoGPT/issues/6	enhancement good first issue API costs	Make Auto-GPT aware of it's running cost	Auto-GPT is expensive to run due to GPT-4's API cost. We could experiment with making it aware of this fact, by tracking tokens as they are used and converting to a dollar cost. This could also be displayed to the user to help them be more aware of exactly how much they are spending.	null	https://github.com/Significant-Gravitas/AutoGPT/pull/762	null	{'base_commit': 'bf895eb656dee9084273cd36395828bd06aa231d', 'files': [{'path': 'autogpt/chat.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [5]}, "(None, 'chat_with_ai', 54)": {'add': [135]}}}, {'path': 'autogpt/config/ai_config.py', 'status': 'modified', 'Loc': {"('AIConfig', None, 21)": {'add': [28]}, "('AIConfig', '__init__', 31)": {'add': [40, 48], 'mod': [32]}, "('AIConfig', 'load', 53)": {'add': [75], 'mod': [55, 77]}, "('AIConfig', 'save', 79)": {'add': [94]}, "('AIConfig', 'construct_full_prompt', 99)": {'add': [149], 'mod': [110]}}}, {'path': 'autogpt/llm_utils.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [9]}, "(None, 'create_chat_completion', 56)": {'mod': [99, 107]}, "(None, 'create_embedding_with_ada', 156)": {'mod': [162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172]}}}, {'path': 'autogpt/memory/base.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [5]}, "(None, 'get_ada_embedding', 11)": {'mod': [13, 14, 15, 16, 17, 18, 19, 20, 21]}}}, {'path': 'autogpt/prompts/prompt.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [2]}, "(None, 'construct_main_ai_config', 78)": {'add': [88, 100, 109]}}}, {'path': 'autogpt/setup.py', 'status': 'modified', 'Loc': {"(None, 'generate_aiconfig_automatic', 139)": {'add': [194], 'mod': [196]}, "(None, 'generate_aiconfig_manual', 70)": {'mod': [136]}}}, {'path': 'tests/unit/test_commands.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [7, 10]}, "(None, 'test_make_agent', 11)": {'mod': [17, 20]}}}, {'path': 'tests/unit/test_setup.py', 'status': 'modified', 'Loc': {"('TestAutoGPT', 'test_generate_aiconfig_automatic_fallback', 39)": {'add': [46]}, "('TestAutoGPT', 'test_prompt_user_manual_mode', 57)": {'add': [64]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "autogpt/chat.py", "autogpt/prompts/prompt.py", "autogpt/config/ai_config.py", "autogpt/memory/base.py", "autogpt/setup.py", "autogpt/llm_utils.py" ], "doc": [], "test": [ "tests/unit/test_commands.py", "tests/unit/test_setup.py" ], "config": [], "asset": [] }	1
yt-dlp	yt-dlp	3e01ce744a981d8f19ae77ec695005e7000f4703	https://github.com/yt-dlp/yt-dlp/issues/5855	bug	Generic extractor can crash if Brotli is not available	### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE - [X] I understand that I will be blocked if I remove or skip any mandatory\* field ### Checklist - [X] I'm reporting a bug unrelated to a specific site - [X] I've verified that I'm running yt-dlp version 2022.11.11 ([update instructions](https://github.com/yt-dlp/yt-dlp#update)) or later (specify commit) - [X] I've checked that all provided URLs are playable in a browser with the same IP and same login details - [X] I've checked that all URLs and arguments with special characters are [properly quoted or escaped](https://github.com/yt-dlp/yt-dlp/wiki/FAQ#video-url-contains-an-ampersand--and-im-getting-some-strange-output-1-2839-or-v-is-not-recognized-as-an-internal-or-external-command) - [X] I've searched the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar issues including closed ones. DO NOT post duplicates - [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue) ### Provide a description that is worded well enough to be understood Testing #5851 in a configuration where no Brotli decoder was available showed the crash in the log. The problem is this extractor code: https://github.com/yt-dlp/yt-dlp/blob/1fc089143c79b02b8373ae1d785d5e3a68635d4d/yt_dlp/extractor/generic.py#L2306-L2318 Normally there is a check for a supported Brotli encoder (using `SUPPORTED_ENCODINGS`). Specifying `` in the `Accept-encoding` header bypasses that check. However, I don't think that `` does what is wanted according to the comments in the above code. The code wants to get the resource with no decoding (because decoding in yt-dl[p] starts by reading the entire response), but `` still allows the server to send a compressed response. What is wanted is the `identity` encoding which is the default if no other encoding is specified. Or, to re-cast the decoding process so that the whole response stream is not read before decoding, but that means creating stream decoding methods for Brotli and zlib. Also, there could be a check for a supported encoding in `YoutubeDLHandler.http_response()`, perhaps synthesizing 416 or 406 id the server has sent an encoding that isn't supported, instead of the crash seen here. ### Provide verbose output that clearly demonstrates the problem - [X] Run your* yt-dlp command with -vU flag added (`yt-dlp -vU <your command line>`) - [X] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below ### Complete Verbose Output ```shell [debug] Command-line config: ['-vU', '-F', 'https://www.extra.cz/cauky-lidi-70-dil-babis-predstavil-pohadky-prymulanek-nebo-andrejovy-nove-saty-ac867'] [debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8 [debug] yt-dlp version 2022.11.11 [8b644025b] (source) [debug] Lazy loading extractors is disabled [debug] Plugins: ['SamplePluginIE', 'SamplePluginPP'] [debug] Git HEAD: c73355510 [debug] Python 3.9.15 (CPython i686 32bit) - Linux-4.4.0-210-generic-i686-with-glibc2.23 (OpenSSL 1.1.1s 1 Nov 2022, glibc 2.23) [debug] exe versions: ffmpeg 4.3, ffprobe 4.3 [debug] Optional libraries: Cryptodome-3.11.0, certifi-2019.11.28, secretstorage-3.2.0, sqlite3-2.6.0 [debug] Proxy map: {} [debug] Loaded 1735 extractors [debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest Latest version: 2022.11.11, Current version: 2022.11.11 yt-dlp is up to date (2022.11.11) [generic] Extracting URL: https://www.extra.cz/cauky-lidi-70-dil-babis-predstavil-pohadky-prymulanek-nebo-andrejovy-nove-saty-ac867 [generic] cauky-lidi-70-dil-babis-predstavil-pohadky-prymulanek-nebo-andrejovy-nove-saty-ac867: Downloading webpage ERROR: 'NoneType' object has no attribute 'decompress' Traceback (most recent call last): File "/home/df/Documents/src/yt-dlp/yt_dlp/YoutubeDL.py", line 1495, in wrapper return func(self, args, *kwargs) File "/home/df/Documents/src/yt-dlp/yt_dlp/YoutubeDL.py", line 1571, in __extract_info ie_result = ie.extract(url) File "/home/df/Documents/src/yt-dlp/yt_dlp/extractor/common.py", line 680, in extract ie_result = self._real_extract(url) File "/home/df/Documents/src/yt-dlp/yt_dlp/extractor/generic.py", line 2314, in _real_extract full_response = self._request_webpage(url, video_id, headers={ File "/home/df/Documents/src/yt-dlp/yt_dlp/extractor/common.py", line 807, in _request_webpage return self._downloader.urlopen(self._create_request(url_or_request, data, headers, query)) File "/home/df/Documents/src/yt-dlp/yt_dlp/YoutubeDL.py", line 3719, in urlopen return self._opener.open(req, timeout=self._socket_timeout) File "/usr/lib/python3.9/urllib/request.py", line 523, in open response = meth(req, response) File "/home/df/Documents/src/yt-dlp/yt_dlp/utils.py", line 1452, in http_response io.BytesIO(self.brotli(resp.read())), old_resp.headers, old_resp.url, old_resp.code) File "/home/df/Documents/src/yt-dlp/yt_dlp/utils.py", line 1389, in brotli return brotli.decompress(data) AttributeError: 'NoneType' object has no attribute 'decompress' ```	null	null	null	{'base_commit': '3e01ce744a981d8f19ae77ec695005e7000f4703', 'files': [{'path': 'yt_dlp/extractor/generic.py', 'status': 'modified', 'Loc': {"('GenericIE', None, 42)": {'add': [2156]}, "('GenericIE', '_real_extract', 2276)": {'mod': [2315]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "2", "loc_way": "commit", "loc_scope": "", "info_type": "" }	{ "code": [ "yt_dlp/extractor/generic.py" ], "doc": [], "test": [], "config": [], "asset": [] }	null
CorentinJ	Real-Time-Voice-Cloning	ded7b37234e229d9bde0a9a506f7c65605803731	https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/543		Lack of pre-compiled results in lost interest	so I know the first thing people are going to say is, this isn't an issue. However, it is. by not having a precompiled version to download over half the people that find their way to this GitHub are going to lose interest. Honestly, I'm one of them. I attempted to compile it but then I saw that I had to track down each module for this, yeah quickly drove me away from it. all I wanted to do was mess around and see what it can do. even if the results arent mind-blowing the concept interests me. but due to not having a ready to use executable I like many others I'm sure of, have decided it isn't even worth messing with.	null	https://github.com/CorentinJ/Real-Time-Voice-Cloning/pull/546	null	{'base_commit': 'ded7b37234e229d9bde0a9a506f7c65605803731', 'files': [{'path': 'toolbox/ui.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [0], 'mod': [11]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "toolbox/ui.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
scikit-learn	scikit-learn	96b5814de70ad2435b6db5f49b607b136921f701	https://github.com/scikit-learn/scikit-learn/issues/26948	Documentation	The copy button on install copies an extensive comman including env activation	### Describe the issue linked to the documentation https://scikit-learn.org/stable/install.html Above link will lead you to the sklearn downlanding for link . when you link copy link button it will copy `python3 -m venv sklearn-venvpython -m venv sklearn-venvpython -m venv sklearn-venvsource sklearn-venv/bin/activatesource sklearn-venv/bin/activatesklearn-venv\Scripts\activatepip install -U scikit-learnpip install -U scikit-learnpip install -U scikit-learnpip3 install -U scikit-learnconda create -n sklearn-env -c conda-forge scikit-learnconda activate sklearn-env` instead of `pip3 install -U scikit-learn` if this is the issue so please issue i want to create a pull request for it and tell in which file this issue reside Thanks ### Suggest a potential alternative/fix By resoving above issue	null	https://github.com/scikit-learn/scikit-learn/pull/27052	null	{'base_commit': '96b5814de70ad2435b6db5f49b607b136921f701', 'files': [{'path': 'doc/install.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107]}}}, {'path': 'doc/themes/scikit-learn-modern/static/css/theme.css', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [1216, 1220, 1225, 1233, 1236, 1239, 1243, 1247], 'mod': [1208, 1209]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "doc/themes/scikit-learn-modern/static/css/theme.css" ], "doc": [ "doc/install.rst" ], "test": [], "config": [], "asset": [] }	1
keras-team	keras	49b9682b3570211c7d8f619f8538c08fd5d8bdad	https://github.com/keras-team/keras/issues/10036		[API DESIGN REVIEW] sample weight in ImageDataGenerator.flow	https://docs.google.com/document/d/14anankKROhliJCpInQH-pITatdjO9UzSN6Iz0MwcDHw/edit?usp=sharing Makes it easy to use data augmentation when sample weights are available.	null	https://github.com/keras-team/keras/pull/10092	null	{'base_commit': '49b9682b3570211c7d8f619f8538c08fd5d8bdad', 'files': [{'path': 'keras/preprocessing/image.py', 'status': 'modified', 'Loc': {"('ImageDataGenerator', 'flow', 715)": {'add': [734, 759], 'mod': [754]}, "('NumpyArrayIterator', None, 1188)": {'add': [1201]}, "('NumpyArrayIterator', '__init__', 1216)": {'add': [1241, 1278], 'mod': [1217, 1218]}, "('NumpyArrayIterator', '_get_batches_of_transformed_samples', 1289)": {'add': [1313]}, "('ImageDataGenerator', None, 443)": {'mod': [715]}}}, {'path': 'tests/keras/preprocessing/image_test.py', 'status': 'modified', 'Loc': {"('TestImage', 'test_image_data_generator', 32)": {'add': [64]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "tests/keras/preprocessing/image_test.py", "keras/preprocessing/image.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
scrapy	scrapy	efb53aafdcaae058962c6189ddecb3dc62b02c31	https://github.com/scrapy/scrapy/issues/6514	enhancement	Migrate from setup.py to pyproject.toml	We should migrate to the modern declarative setuptools metadata approach as discussed in https://setuptools.pypa.io/en/latest/userguide/quickstart.html and https://setuptools.pypa.io/en/latest/userguide/pyproject_config.html, but only after the 2.12 release.	null	https://github.com/scrapy/scrapy/pull/6547	null	{'base_commit': 'efb53aafdcaae058962c6189ddecb3dc62b02c31', 'files': [{'path': '.bandit.yml', 'status': 'removed', 'Loc': {}}, {'path': '.bumpversion.cfg', 'status': 'removed', 'Loc': {}}, {'path': '.coveragerc', 'status': 'removed', 'Loc': {}}, {'path': '.isort.cfg', 'status': 'removed', 'Loc': {}}, {'path': '.pre-commit-config.yaml', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [6]}}}, {'path': 'MANIFEST.in', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [13]}}}, {'path': 'pylintrc', 'status': 'removed', 'Loc': {}}, {'path': 'pytest.ini', 'status': 'removed', 'Loc': {}}, {'path': 'setup.cfg', 'status': 'removed', 'Loc': {}}, {'path': 'setup.py', 'status': 'removed', 'Loc': {}}, {'path': 'tests/test_crawler.py', 'status': 'modified', 'Loc': {"('CrawlerProcessSubprocess', 'test_shutdown_forced', 890)": {'mod': [902]}}}, {'path': 'tests/test_spiderloader/__init__.py', 'status': 'modified', 'Loc': {"('SpiderLoaderTest', 'test_syntax_error_warning', 146)": {'mod': [147, 148, 149]}}}, {'path': 'tox.ini', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [82]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "tests/test_spiderloader/__init__.py", ".isort.cfg", ".coveragerc", "setup.cfg", "setup.py", ".bumpversion.cfg" ], "doc": [], "test": [ "tests/test_crawler.py" ], "config": [ "pytest.ini", ".pre-commit-config.yaml", "tox.ini", "pylintrc", ".bandit.yml", "MANIFEST.in" ], "asset": [] }	1
fastapi	fastapi	c6e950dc9cacefd692dbd8987a3acd12a44b506f	https://github.com/fastapi/fastapi/issues/5859	question question-migrate	FastAPI==0.89.0 Cannot use `None` as a return type when `status_code` is set to 204 with `from __future__ import annotations`	### First Check - [X] I added a very descriptive title to this issue. - [X] I used the GitHub search to find a similar issue and didn't find it. - [X] I searched the FastAPI documentation, with the integrated search. - [X] I already searched in Google "How to X in FastAPI" and didn't find any information. - [X] I already read and followed all the tutorial in the docs and didn't find an answer. - [X] I already checked if it is not related to FastAPI but to [Pydantic](https://github.com/samuelcolvin/pydantic). - [X] I already checked if it is not related to FastAPI but to [Swagger UI](https://github.com/swagger-api/swagger-ui). - [X] I already checked if it is not related to FastAPI but to [ReDoc](https://github.com/Redocly/redoc). ### Commit to Help - [X] I commit to help with one of those options 👆 ### Example Code ```python from __future__ import annotations from fastapi import FastAPI app = FastAPI() @app.get("/", status_code=204) def read_root() -> None: return {"Hello": "World"} ``` ### Description If we add: `from __future__ import annotations` It changes the annotations structure and the response model is `NoneType` instead of `None`, which causes validation of the `statuc_code` vs `response_model` and raises an exception. ```python ... File ".../site-packages/fastapi/routing.py", line 635, in decorator self.add_api_route( File ".../site-packages/fastapi/routing.py", line 574, in add_api_route route = route_class( File ".../site-packages/fastapi/routing.py", line 398, in __init__ assert is_body_allowed_for_status_code( AssertionError: Status code 204 must not have a response body ``` I am working on a fix for it right now. ### Operating System macOS ### Operating System Details _No response_ ### FastAPI Version 0.89.0 ### Python Version 3.10 ### Additional Context _No response_	null	https://github.com/fastapi/fastapi/pull/2246	null	{'base_commit': 'c6e950dc9cacefd692dbd8987a3acd12a44b506f', 'files': [{'path': '.github/workflows/preview-docs.yml', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [38]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [], "doc": [ ".github/workflows/preview-docs.yml" ], "test": [], "config": [], "asset": [] }	1
3b1b	manim	3938f81c1b4a5ee81d5bfc6563c17a225f7e5068	https://github.com/3b1b/manim/issues/1330		Error after installing manim	I installed all manim & dependecies, but when I ran `python -m manim example_scenes.py OpeningManimExample`, I got the following error: `Traceback (most recent call last): File "c:\users\jm\anaconda3\lib\runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "c:\users\jm\anaconda3\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\Users\jm\Documents\work\manim_new\manim\manim.py", line 5, in <module> manimlib.main() File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\__init__.py", line 9, in main scenes = manimlib.extract_scene.main(config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\extract_scene.py", line 113, in main scenes = get_scenes_to_render(all_scene_classes, scene_config, config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\extract_scene.py", line 74, in get_scenes_to_render scene = scene_class(scene_config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\scene\scene.py", line 44, in __init__ self.window = Window(self, self.window_config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\window.py", line 19, in __init__ super().__init__(*kwargs) File "C:\Users\jm\Envs\manim.new\lib\site-packages\moderngl_window\context\pyglet\window.py", line 51, in __init__ self._window = PygletWrapper( File "C:\Users\jm\Envs\manim.new\lib\site-packages\pyglet\window\win32\__init__.py", line 134, in __init__ super(Win32Window, self).__init__(args, **kwargs) File "C:\Users\jm\Envs\manim.new\lib\site-packages\pyglet\window\__init__.py", line 603, in __init__ config = screen.get_best_config(config) File "C:\Users\jm\Envs\manim.new\lib\site-packages\pyglet\canvas\base.py", line 194, in get_best_config raise window.NoSuchConfigException() pyglet.window.NoSuchConfigException`. Any advice? And thank you	null	https://github.com/3b1b/manim/pull/1343	null	{'base_commit': '3938f81c1b4a5ee81d5bfc6563c17a225f7e5068', 'files': [{'path': 'manimlib/window.py', 'status': 'modified', 'Loc': {"('Window', None, 10)": {'mod': [15]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "manimlib/window.py" ], "doc": [], "test": [], "config": [], "asset": [] }	null
keras-team	keras	84b283e6200bcb051ed976782fbb2b123bf9b8fc	https://github.com/keras-team/keras/issues/19793	type:bug/performance	model.keras format much slower to load	Anyone experiencing unreasonably slow load times when loading a keras-format saved model? I have noticed this repeated when working in ipython, where simply instantiating a model via `Model.from_config` then calling `model.load_weights` is much (several factors) faster than loading a `model.keras` file. My understanding is the keras format is simply a zip file with the config.json file and weights h5 (iirc) but weirdly enough, there's something not right going on while loading.	null	https://github.com/keras-team/keras/pull/19852	null	{'base_commit': '84b283e6200bcb051ed976782fbb2b123bf9b8fc', 'files': [{'path': 'keras/src/saving/saving_lib.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [5, 34]}, "(None, '_save_model_to_fileobj', 95)": {'mod': [112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 127, 128, 129, 130, 131, 132, 133, 134, 135]}, "(None, '_load_model_from_fileobj', 157)": {'mod': [175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 186, 187, 188, 189, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204]}, "(None, 'load_weights_only', 239)": {'mod': [253, 254, 255]}}}, {'path': 'keras/src/saving/saving_lib_test.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [614]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "keras/src/saving/saving_lib_test.py", "keras/src/saving/saving_lib.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
ansible	ansible	4cdb266dac852859f695b0555cbe49e58343e69a	https://github.com/ansible/ansible/issues/3539	bug	Bug in Conditional Include	Hi, I know that when using conditionals on an include, 'All the tasks get evaluated, but the conditional is applied to each and every task'. However this breaks when some of that tasks register variables and other tasks in the group use those variable. Example: main.yml: ``` - include: extra.yml when: do_extra is defined ``` extra.yml: ``` - name: check if we can do task A shell: check_if_task_A_possible register: A_possible ignore_errors: yes - name: task A shell: run_task_A when: A_possible.rc == 0 ``` Now if you run main.yml and 'do_extra' is not defined, the run will fail on 'task A' because when the 'when' condition is evaluated, the variable A_possible will not exist. It is not sufficient to just add the top-level include conditional above the other because right now it looks like the two conditions are compounded and tested together which will still fail because A_possible is not defined. I think you would have to run the file level conditional before the task level ones to keep this from happening.	null	https://github.com/ansible/ansible/pull/20158	null	{'base_commit': '4cdb266dac852859f695b0555cbe49e58343e69a', 'files': [{'path': 'lib/ansible/modules/windows/win_robocopy.ps1', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [25, 26, 27, 28, 73, 76, 93, 94, 95, 114, 115, 167, 168]}}}, {'path': 'lib/ansible/modules/windows/win_robocopy.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [132]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "lib/ansible/modules/windows/win_robocopy.ps1", "lib/ansible/modules/windows/win_robocopy.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
psf	requests	f5dacf84468ab7e0631cc61a3f1431a32e3e143c	https://github.com/psf/requests/issues/2654	Feature Request Contributor Friendly	utils.get_netrc_auth silently fails when netrc exists but fails to parse	My .netrc contains a line for the github auth, [like this](https://gist.github.com/wikimatze/9790374). It turns out that `netrc.netrc()` doesn't like that: ``` >>> from netrc import netrc >>> netrc() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/netrc.py", line 35, in __init__ self._parse(file, fp, default_netrc) File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/netrc.py", line 117, in _parse file, lexer.lineno) netrc.NetrcParseError: bad follower token 'protocol' (/Users/david/.netrc, line 9) ``` `get_netrc_auth` catches the `NetrcParseError` [but just ignores it](https://github.com/kennethreitz/requests/blob/master/requests/utils.py#L106). At least having it emit a warning would have saved some hair-pulling.	null	https://github.com/psf/requests/pull/2656	null	{'base_commit': 'f5dacf84468ab7e0631cc61a3f1431a32e3e143c', 'files': [{'path': 'requests/utils.py', 'status': 'modified', 'Loc': {"(None, 'get_netrc_auth', 70)": {'mod': [70, 108, 109]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "requests/utils.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
oobabooga	text-generation-webui	0877741b0350d200be7f1e6cca2780a25ee29cd0	https://github.com/oobabooga/text-generation-webui/issues/5851	bug	Inference failing using ExLlamav2 version 0.0.18	### Describe the bug Since ExLlamav2 was upgraded to version 0.0.18 in the requirements.txt, inference using it is no longer working and fails with the error in the logs below. Reverting to version 0.0.17 resolves the issue. ### Is there an existing issue for this? - [X] I have searched the existing issues ### Reproduction 1. Install latest main branch (current commit is `26d822f64f2a029306b250b69dc58468662a4fc6`) 2. Download `GPTQ` model 3. Use `ExLlamav2_HF` model loader 4. Go to `Chat` tab and ask the AI a question. 5. Observe error, even though the model loaded successfully. ### Screenshot _No response_ ### Logs ```shell 21:35:11-061459 INFO Loading "TheBloke_dolphin-2.6-mistral-7B-GPTQ" 21:35:13-842112 INFO LOADER: "ExLlamav2" 21:35:13-843422 INFO TRUNCATION LENGTH: 32768 21:35:13-844234 INFO INSTRUCTION TEMPLATE: "Alpaca" 21:35:13-845014 INFO Loaded the model in 2.78 seconds. Traceback (most recent call last): File "/workspace/text-generation-webui/modules/text_generation.py", line 429, in generate_reply_custom for reply in shared.model.generate_with_streaming(question, state): File "/workspace/text-generation-webui/modules/exllamav2.py", line 140, in generate_with_streaming self.generator.begin_stream(ids, settings, loras=self.loras) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 198, in begin_stream self.begin_stream_ex(input_ids, File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 296, in begin_stream_ex self._gen_begin_reuse(input_ids, gen_settings) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 624, in _gen_begin_reuse self._gen_begin(in_tokens, gen_settings) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 586, in _gen_begin self.model.forward(self.sequence_ids[:, :-1], File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/model.py", line 694, in forward r, ls = self._forward(input_ids = input_ids[:, chunk_begin : chunk_end], File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/model.py", line 776, in _forward x = module.forward(x, cache = cache, attn_params = attn_params, past_len = past_len, loras = loras, kwargs) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/attn.py", line 596, in forward attn_output = flash_attn_func(q_states, k_states, v_states, causal = True) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 825, in flash_attn_func return FlashAttnFunc.apply( File "/usr/local/lib/python3.10/dist-packages/torch/autograd/function.py", line 553, in apply return super().apply(args, kwargs) # type: ignore[misc] File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 507, in forward out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = _flash_attn_forward( File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 51, in _flash_attn_forward out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = flash_attn_cuda.fwd( RuntimeError: CUDA error: an illegal memory access was encountered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. ``` ### System Info Ubuntu 22.04 LTS * Nvidia A5000 GPU on Runpod * CUDA 12.1	null	null	null	{'base_commit': '0877741b0350d200be7f1e6cca2780a25ee29cd0', 'files': [{'path': 'requirements.txt', 'status': 'modified', 'Loc': {'(None, None, 59)': {'mod': [59, 60, 61, 62, 63]}}}, {'path': 'requirements_amd.txt', 'status': 'modified', 'Loc': {'(None, None, 45)': {'mod': [45, 46, 47]}}}, {'path': 'requirements_amd_noavx2.txt', 'status': 'modified', 'Loc': {'(None, None, 43)': {'mod': [43, 44, 45]}}}, {'path': 'requirements_apple_intel.txt', 'status': 'modified', 'Loc': {'(None, None, 41)': {'mod': [41]}}}, {'path': 'requirements_apple_silicon.txt', 'status': 'modified', 'Loc': {'(None, None, 43)': {'mod': [43]}}}, {'path': 'requirements_noavx2.txt', 'status': 'modified', 'Loc': {'(None, None, 59)': {'mod': [59, 60, 61, 62, 63]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "commit", "loc_scope": "", "info_type": "" }	{ "code": [], "doc": [], "test": [], "config": [ "requirements_apple_silicon.txt", "requirements_amd_noavx2.txt", "requirements_apple_intel.txt", "requirements_amd.txt", "requirements.txt", "requirements_noavx2.txt" ], "asset": [] }	null
zylon-ai	private-gpt	89477ea9d3a83181b0222b732a81c71db9edf142	https://github.com/zylon-ai/private-gpt/issues/2013	bug	[BUG] Another permissions error when installing with docker-compose	### Pre-check - [X] I have searched the existing issues and none cover this bug. ### Description This looks similar, but not the same as #1876 As for following the instructions, I've not seen any relevant guide to installing with Docker, hence working a bit blind. Background: I'm trying to run this on an Asustor NAS, which offers very little ability to customize the environment. Ideally, I'd just like to be able to run this by pasting a docker-compose file into Portainer, and having it work it's magic from there: --- ``` sal@halob:/volume1/home/sal/apps/private-gpt $ docker-compose up [+] Running 3/3 ✔ Network private-gpt_default Created 0.1s ✔ Container private-gpt-ollama-1 Created 0.1s ✔ Container private-gpt-private-gpt-1 Created 0.1s Attaching to ollama-1, private-gpt-1 ollama-1 \| Couldn't find '/root/.ollama/id_ed25519'. Generating new private key. ollama-1 \| Your new public key is: ollama-1 \| ollama-1 \| ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIBNQkShAIoUDyyueUTiCHM9/AZfZ+rxnUZgmh+YByBVB ollama-1 \| ollama-1 \| 2024/07/23 23:20:28 routes.go:1096: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://0.0.0.0:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MAX_VRAM:0 OLLAMA_MODELS:/root/.ollama/models OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://] OLLAMA_RUNNERS_DIR: OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]" ollama-1 \| time=2024-07-23T23:20:28.317Z level=INFO source=images.go:778 msg="total blobs: 0" ollama-1 \| time=2024-07-23T23:20:28.317Z level=INFO source=images.go:785 msg="total unused blobs removed: 0" ollama-1 \| time=2024-07-23T23:20:28.317Z level=INFO source=routes.go:1143 msg="Listening on [::]:11434 (version 0.2.6)" ollama-1 \| time=2024-07-23T23:20:28.318Z level=INFO source=payload.go:30 msg="extracting embedded files" dir=/tmp/ollama1112441504/runners private-gpt-1 \| 23:20:29.406 [INFO ] private_gpt.settings.settings_loader - Starting application with profiles=['default', 'docker'] ollama-1 \| time=2024-07-23T23:20:33.589Z level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cpu_avx cpu_avx2 cuda_v11 rocm_v60102 cpu]" ollama-1 \| time=2024-07-23T23:20:33.589Z level=INFO source=gpu.go:205 msg="looking for compatible GPUs" ollama-1 \| time=2024-07-23T23:20:33.589Z level=WARN source=gpu.go:225 msg="CPU does not have minimum vector extensions, GPU inference disabled" required=avx detected="no vector extensions" ollama-1 \| time=2024-07-23T23:20:33.590Z level=INFO source=types.go:105 msg="inference compute" id=0 library=cpu compute="" driver=0.0 name="" total="31.1 GiB" available="28.1 GiB" private-gpt-1 \| There was a problem when trying to write in your cache folder (/nonexistent/.cache/huggingface/hub). You should set the environment variable TRANSFORMERS_CACHE to a writable directory. private-gpt-1 \| None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used. private-gpt-1 \| 23:20:40.419 [INFO ] private_gpt.components.llm.llm_component - Initializing the LLM in mode=ollama private-gpt-1 \| Traceback (most recent call last): private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 798, in get private-gpt-1 \| return self._context[key] private-gpt-1 \| ~~~~~~~~~~~~~^^^^^ private-gpt-1 \| KeyError: <class 'private_gpt.ui.ui.PrivateGptUi'> private-gpt-1 \| private-gpt-1 \| During handling of the above exception, another exception occurred: private-gpt-1 \| private-gpt-1 \| Traceback (most recent call last): private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 798, in get private-gpt-1 \| return self._context[key] private-gpt-1 \| ~~~~~~~~~~~~~^^^^^ private-gpt-1 \| KeyError: <class 'private_gpt.server.ingest.ingest_service.IngestService'> private-gpt-1 \| private-gpt-1 \| During handling of the above exception, another exception occurred: private-gpt-1 \| private-gpt-1 \| Traceback (most recent call last): private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 798, in get private-gpt-1 \| return self._context[key] private-gpt-1 \| ~~~~~~~~~~~~~^^^^^ private-gpt-1 \| KeyError: <class 'private_gpt.components.vector_store.vector_store_component.VectorStoreComponent'> private-gpt-1 \| private-gpt-1 \| During handling of the above exception, another exception occurred: private-gpt-1 \| private-gpt-1 \| Traceback (most recent call last): private-gpt-1 \| File "<frozen runpy>", line 198, in _run_module_as_main private-gpt-1 \| File "<frozen runpy>", line 88, in _run_code private-gpt-1 \| File "/home/worker/app/private_gpt/__main__.py", line 5, in <module> private-gpt-1 \| from private_gpt.main import app private-gpt-1 \| File "/home/worker/app/private_gpt/main.py", line 6, in <module> private-gpt-1 \| app = create_app(global_injector) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/private_gpt/launcher.py", line 63, in create_app private-gpt-1 \| ui = root_injector.get(PrivateGptUi) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 974, in get private-gpt-1 \| provider_instance = scope_instance.get(interface, binding.provider) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 800, in get private-gpt-1 \| instance = self._get_instance(key, provider, self.injector) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance private-gpt-1 \| return provider.get(injector) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 264, in get private-gpt-1 \| return injector.create_object(self._cls) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object private-gpt-1 \| self.call_with_injection(init, self_=instance, kwargs=additional_kwargs) private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1031, in call_with_injection private-gpt-1 \| dependencies = self.args_to_inject( private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1079, in args_to_inject private-gpt-1 \| instance: Any = self.get(interface) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 974, in get private-gpt-1 \| provider_instance = scope_instance.get(interface, binding.provider) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 800, in get private-gpt-1 \| instance = self._get_instance(key, provider, self.injector) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance private-gpt-1 \| return provider.get(injector) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 264, in get private-gpt-1 \| return injector.create_object(self._cls) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object private-gpt-1 \| self.call_with_injection(init, self_=instance, kwargs=additional_kwargs) private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1031, in call_with_injection private-gpt-1 \| dependencies = self.args_to_inject( private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1079, in args_to_inject private-gpt-1 \| instance: Any = self.get(interface) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 974, in get private-gpt-1 \| provider_instance = scope_instance.get(interface, binding.provider) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 \| return function(args, *kwargs) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 800, in get private-gpt-1 \| instance = self._get_instance(key, provider, self.injector) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance private-gpt-1 \| return provider.get(injector) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 264, in get private-gpt-1 \| return injector.create_object(self._cls) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object private-gpt-1 \| self.call_with_injection(init, self_=instance, kwargs=additional_kwargs) private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1040, in call_with_injection private-gpt-1 \| return callable(full_args, **dependencies) private-gpt-1 \| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/private_gpt/components/vector_store/vector_store_component.py", line 114, in __init__ private-gpt-1 \| client = QdrantClient( private-gpt-1 \| ^^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/qdrant_client/qdrant_client.py", line 117, in __init__ private-gpt-1 \| self._client = QdrantLocal( private-gpt-1 \| ^^^^^^^^^^^^ private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/qdrant_client/local/qdrant_local.py", line 66, in __init__ private-gpt-1 \| self._load() private-gpt-1 \| File "/home/worker/app/.venv/lib/python3.11/site-packages/qdrant_client/local/qdrant_local.py", line 97, in _load private-gpt-1 \| os.makedirs(self.location, exist_ok=True) private-gpt-1 \| File "<frozen os>", line 215, in makedirs private-gpt-1 \| File "<frozen os>", line 225, in makedirs private-gpt-1 \| PermissionError: [Errno 13] Permission denied: 'local_data/private_gpt' ^CGracefully stopping... (press Ctrl+C again to force) [+] Stopping 2/2 ✔ Container private-gpt-private-gpt-1 Stopped 0.3s ✔ Container private-gpt-ollama-1 Stopped ``` ### Steps to Reproduce 1. Clone the repo 2. docker-compose build 3. docker-compose up ### Expected Behavior It should just run ### Actual Behavior Error, as reported above ### Environment Running on an Asustor router, docker 25.0.5 ### Additional Information _No response_ ### Version latest ### Setup Checklist - [X] Confirm that you have followed the installation instructions in the project’s documentation. - [X] Check that you are using the latest version of the project. - [X] Verify disk space availability for model storage and data processing. - [X] Ensure that you have the necessary permissions to run the project. ### NVIDIA GPU Setup Checklist - [ ] Check that the all CUDA dependencies are installed and are compatible with your GPU (refer to [CUDA's documentation](https://docs.nvidia.com/deploy/cuda-compatibility/#frequently-asked-questions)) - [ ] Ensure an NVIDIA GPU is installed and recognized by the system (run `nvidia-smi` to verify). - [ ] Ensure proper permissions are set for accessing GPU resources. - [ ] Docker users - Verify that the NVIDIA Container Toolkit is configured correctly (e.g. run `sudo docker run --rm --gpus all nvidia/cuda:11.0.3-base-ubuntu20.04 nvidia-smi`)	null	https://github.com/zylon-ai/private-gpt/pull/2059	null	{'base_commit': '89477ea9d3a83181b0222b732a81c71db9edf142', 'files': [{'path': 'Dockerfile.llamacpp-cpu', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [3, 23, 30]}}}, {'path': 'Dockerfile.ollama', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [1, 13, 20]}}}, {'path': 'docker-compose.yaml', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [10, 29, 34], 'mod': [15, 47, 60]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [], "doc": [ "docker-compose.yaml" ], "test": [], "config": [ "Dockerfile.ollama", "Dockerfile.llamacpp-cpu" ], "asset": [] }	1
scikit-learn	scikit-learn	e04b8e70e60df88751af5cd667cafb66dc32b397	https://github.com/scikit-learn/scikit-learn/issues/26590	Bug	KNNImputer add_indicator fails to persist where missing data had been present in training	### Describe the bug Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense matrix. I would have expected it to return a 2x3 matrix rather than 2x2, with `missingindicator_A = False` for all cases. Reproduction steps below. Any help much appreciated :) ### Steps/Code to Reproduce ```python >>> import pandas as pd >>> from sklearn.impute import KNNImputer >>> knn = KNNImputer(add_indicator=True) >>> df = pd.DataFrame({'A': [0, None], 'B': [1, 2]}) >>> df A B 0 0.0 1 1 NaN 2 >>> knn.fit(df) KNNImputer(add_indicator=True) >>> pd.DataFrame(knn.transform(df), columns=knn.get_feature_names_out()) A B missingindicator_A 0 0.0 1.0 0.0 1 0.0 2.0 1.0 >>> df['A'] = 0 >>> pd.DataFrame(knn.transform(df), columns=knn.get_feature_names_out()) ``` ### Expected Results ``` A B missingindicator_A 0 0.0 1.0 0.0 1 0.0 2.0 0.0 ``` ### Actual Results ```pytb --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[30], line 1 ----> 1 pd.DataFrame(knn.transform(df), columns=knn.get_feature_names_out()) File /opt/conda/lib/python3.10/site-packages/pandas/core/frame.py:694, in DataFrame.__init__(self, data, index, columns, dtype, copy) 684 mgr = dict_to_mgr( 685 # error: Item "ndarray" of "Union[ndarray, Series, Index]" has no 686 # attribute "name" (...) 691 typ=manager, 692 ) 693 else: --> 694 mgr = ndarray_to_mgr( 695 data, 696 index, 697 columns, 698 dtype=dtype, 699 copy=copy, 700 typ=manager, 701 ) 703 # For data is list-like, or Iterable (will consume into list) 704 elif is_list_like(data): File /opt/conda/lib/python3.10/site-packages/pandas/core/internals/construction.py:351, in ndarray_to_mgr(values, index, columns, dtype, copy, typ) 346 # _prep_ndarray ensures that values.ndim == 2 at this point 347 index, columns = _get_axes( 348 values.shape[0], values.shape[1], index=index, columns=columns 349 ) --> 351 _check_values_indices_shape_match(values, index, columns) 353 if typ == "array": 355 if issubclass(values.dtype.type, str): File /opt/conda/lib/python3.10/site-packages/pandas/core/internals/construction.py:422, in _check_values_indices_shape_match(values, index, columns) 420 passed = values.shape 421 implied = (len(index), len(columns)) --> 422 raise ValueError(f"Shape of passed values is {passed}, indices imply {implied}") ValueError: Shape of passed values is (2, 2), indices imply (2, 3) ``` ### Versions ```shell python3, sklearn = 1.2.1 ```	null	https://github.com/scikit-learn/scikit-learn/pull/26600	null	{'base_commit': 'e04b8e70e60df88751af5cd667cafb66dc32b397', 'files': [{'path': 'doc/whats_new/v1.3.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [14]}}}, {'path': 'sklearn/impute/_knn.py', 'status': 'modified', 'Loc': {"('KNNImputer', 'transform', 242)": {'mod': [285]}}}, {'path': 'sklearn/impute/tests/test_common.py', 'status': 'modified', 'Loc': {"(None, 'test_keep_empty_features', 171)": {'add': [183]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "sklearn/impute/_knn.py" ], "doc": [ "doc/whats_new/v1.3.rst" ], "test": [ "sklearn/impute/tests/test_common.py" ], "config": [], "asset": [] }	1
nvbn	thefuck	9660ec7813a0e77ec3411682b0084d07b540084e	https://github.com/nvbn/thefuck/issues/543		Adding sudo works for `aura -Sy` but not `aura -Ay`	`fuck` is unable to add `sudo` to an `aura -Ay` command: ``` $ aura -Ay foobar-beta-git # from AUR aura >>= You have to use `sudo` for that. $ fuck No fucks given ``` But works as expected for `aura -Sy`: ``` $ aura -Sy foobar # pacman alias error: you cannot perform this operation unless you are root. aura >>= Please check your input. $ fuck sudo aura -Sy foobar [enter/↑/↓/ctrl+c] ``` It's slightly annoying anyway that the `aura` outut is different in these cases, but is it possible for `thefuck` to work-around? Or is the only way for `aura` to give a stderr message containing "root"?	null	https://github.com/nvbn/thefuck/pull/557	null	{'base_commit': '9660ec7813a0e77ec3411682b0084d07b540084e', 'files': [{'path': 'thefuck/rules/sudo.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [22]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "thefuck/rules/sudo.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
scikit-learn	scikit-learn	2707099b23a0a8580731553629566c1182d26f48	https://github.com/scikit-learn/scikit-learn/issues/29294	Moderate help wanted	ConvergenceWarnings cannot be turned off	Hi, I'm unable to turn off convergence warnings from `GraphicalLassoCV`. I've tried most of the solutions from, and none of them worked (see below for actual implementations): https://stackoverflow.com/questions/879173/how-to-ignore-deprecation-warnings-in-python https://stackoverflow.com/questions/32612180/eliminating-warnings-from-scikit-learn/33812427#33812427 https://stackoverflow.com/questions/53968004/how-to-silence-all-sklearn-warning https://stackoverflow.com/questions/14463277/how-to-disable-python-warnings Contrary to what the designers of the sklearn's exceptions must have thought when it was implemented, some of us actually use stdout to log important information of the host program for diagnostics purposes. Flooding it with garbage that cannot be turned off, as is in the case with cross-validation, is not ok. To briefly speak to the severity of the issue, the above sklearn-specific questions relating to suppressing warnings have been viewed ~500K times with combined ~400 upvotes, and dates back 7 years. I've tried the following (`n_jobs` parameter does not appear to affect the result): ```py from sklearn.covariance import GraphicalLassoCV import warnings warnings.filterwarnings("ignore", category=ConvergenceWarning) model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py from sklearn.covariance import GraphicalLassoCV import warnings warnings.filterwarnings(action='ignore') model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py import warnings with warnings.catch_warnings(): warnings.simplefilter("ignore", ConvergenceWarning) model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py from sklearn.covariance import GraphicalLassoCV def warn(args, *kwargs): pass import warnings warnings.warn = warn model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py import contextlib import os, sys @contextlib.contextmanager def suppress_stdout(): with open(os.devnull, 'w') as fnull: old_stdout = sys.stdout sys.stdout = fnull try: yield finally: sys.stdout = old_stdout with suppress_stdout(): model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py import logging logging.captureWarnings(True) logging.getLogger("py.warnings").setLevel(logging.ERROR) model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ```	null	https://github.com/scikit-learn/scikit-learn/pull/30380	null	{'base_commit': '2707099b23a0a8580731553629566c1182d26f48', 'files': [{'path': 'sklearn/utils/parallel.py', 'status': 'modified', 'Loc': {"('_FuncWrapper', 'with_config', 121)": {'add': [122]}, "(None, '_with_config', 24)": {'mod': [24, 26, 27]}, "('Parallel', '__call__', 54)": {'mod': [73, 74, 77]}, "('_FuncWrapper', None, 114)": {'mod': [121]}, "('_FuncWrapper', '__call__', 125)": {'mod': [126, 127, 137, 138]}}}, {'path': 'sklearn/utils/tests/test_parallel.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [1, 11]}, "(None, 'test_dispatch_config_parallel', 56)": {'add': [100]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "sklearn/utils/parallel.py" ], "doc": [], "test": [ "sklearn/utils/tests/test_parallel.py" ], "config": [], "asset": [] }	1
All-Hands-AI	OpenHands	7b2b1eff57e41364b4b427e36e766607e7eed3a0	https://github.com/All-Hands-AI/OpenHands/issues/20		Control Loop: long term planning and execution	The biggest, most complicated aspect of Devin is long-term planning and execution. I'd like to start a discussion about how this might work in OpenDevin. There's some [recent prior work from Microsoft](https://arxiv.org/pdf/2403.08299.pdf) with some impressive results. I'll summarize here, with some commentary. ## Overall Flow * User specifies objective and associated settings * Conversation Manager kicks in * Sends convo to Agent Scheduler * Agents execute commands * Output is placed back into the conversation * Rinse and repeat ## Configuraiton * A YAML file defines a set of actions/commands the bot can take (e.g. `npm test`) * comment: why not just leave it open-ended? * You can have different agents with different capabilities, e.g. a "dev agent" and a "reviewer agent", who work collaboratively * comment: this sounds like MetaGPT ## Components ### Conversation Manager * maintains message history and command outputs * decides when to interrupt the conversation * comment: for what? more info from the user? * decides when the conversation is over, i.e. task has been completed * agent can send a "stop" command, max tokens can be reached, problems w/ execution environment ### Parser * interprets agent output and turns it into commands, file edits, etc * in case of parsing failure, a message is sent back to the agent to rewrite its command ### Output Organizer * Takes command output and selectively places it into the conversation history * sometimes summarizes the content first * comment: why not just drop everything back into the conversation history (maybe truncating really long CLI output) ### Agent Scheduler * orchestrates different agents * uses different algos for deciding who gets to go next * round-robin: everyone takes turns in order * token-based: agent gets to keep going until it says it's done * priority-based: agents go based on (user defined?) priority ### Tools Library * file editing (can edit entire file, or specify start line and end line) * retrieval (file contents, `ls`, `grep`). Seems to use vector search as well * build and execution: abstracts away the implementation in favor of simple commands like `build foo` * testing and validation: includes linters and bug-finding utils * git: can commit, push, merge * communication: can as human for input/feedback, can talk to other agents ### Evaluation Environment * runs in Docker	null	https://github.com/All-Hands-AI/OpenHands/pull/3771	null	{'base_commit': '7b2b1eff57e41364b4b427e36e766607e7eed3a0', 'files': [{'path': '.gitignore', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [230]}}}, {'path': 'containers/runtime/README.md', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [1, 3, 5, 9]}}}, {'path': 'frontend/src/components/AgentStatusBar.tsx', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [20, 92], 'mod': [94, 95, 96, 97, 98, 99, 100]}}}, {'path': 'frontend/src/i18n/translation.json', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [465, 482], 'mod': [75, 81, 87, 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All-Hands-AI	OpenHands	2242702cf94eab7275f2cb148859135018d9b280	https://github.com/All-Hands-AI/OpenHands/issues/1251	enhancement	Sandbox Capabilities Framework	Summary We have an existing use case for a Jupyter-aware agent, which always runs in a sandbox where Jupyter is available. There are some other scenarios I can think of where an agent might want some guarantees about what it can do with the sandbox: * We might want a "postgres migration writer", which needs access to a postgres instance * We might have a "cypress test creator" agent, which would need access to cypress * Further down the road, we might want to have an [Open Interpreter](https://github.com/OpenInterpreter/open-interpreter) agent, which needs access to osascript * etc etc This proposal would allow agents to guarantee that certain programs are available in the sandbox, or that certain services are running in a predictable way. What if we did something like this: Motivation We want agents to be able to have certain guarantees about the sandbox environment. But we also want our sandbox interface to be generic--something like "you have a bash terminal". The latter is especially important, because we want users to be able to bring their own sandbox images. E.g. you might use an off-the-shelf haskell image if your project uses haskell--otherwise you'd need to go through the install process every time you start OpenDevin, or maintain a fork of the sandbox. Technical Design * For every requirement we support (e.g. jupyter, postgres, cypress), we have a bash script that * checks if it's installed * if not, installs it * maybe starts something in the background * Let agents specify a list of requirements * e.g. CodeActAgent could say requirements: ['jupyter'] * When we start the Agent+Sandbox pair, we run the necessary bash scripts * should be pretty quick if the requirement is already built into the image * Then the agent has some guarantees about the requirement being met, and how it's running * e.g. we can put in the prompt "there's a postgres server running on port 5432, user foo, password bar" * If there are specific ways of interacting with that env (e.g. for jupyter, it seems we have to write to a websocket that's open in the sandbox?) the agent can implement custom Actions, like run_in_jupyter Alternatives to Consider * Building a bunch of stuff into one big sandbox * Building special sandboxes that are required by certain agents (e.g. a JupyterSandbox) Additional context https://opendevin.slack.com/archives/C06QKSD9UBA/p1713552591042089	null	https://github.com/All-Hands-AI/OpenHands/pull/1255	null	{'base_commit': '2242702cf94eab7275f2cb148859135018d9b280', 'files': [{'path': 'Makefile', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [220]}}}, {'path': 'agenthub/codeact_agent/codeact_agent.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [17]}, "('CodeActAgent', None, 66)": {'add': [71]}}}, {'path': 'opendevin/agent.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [8]}, "('Agent', None, 11)": {'add': [19]}}}, {'path': 'opendevin/config.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [4, 20]}, "(None, 'get', 140)": {'add': [147]}}}, {'path': 'opendevin/controller/action_manager.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [16]}, "('ActionManager', None, 19)": {'add': [43]}}}, {'path': 'opendevin/controller/agent_controller.py', 'status': 'modified', 'Loc': {"('AgentController', '__init__', 41)": {'add': [55]}}}, {'path': 'opendevin/sandbox/docker/exec_box.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [6]}, "('DockerExecBox', None, 36)": {'add': [124]}}}, {'path': 'opendevin/sandbox/docker/local_box.py', 'status': 'modified', 'Loc': {"('LocalBox', None, 25)": {'add': [41]}}}, {'path': 'opendevin/sandbox/docker/ssh_box.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [6, 17, 357], 'mod': [359]}, "('DockerSSHBox', 'setup_user', 95)": {'add': [139]}, "('DockerSSHBox', None, 46)": {'add': [210]}, "('DockerSSHBox', 'restart_docker_container', 271)": {'add': [309]}}}, {'path': 'opendevin/sandbox/e2b/sandbox.py', 'status': 'modified', 'Loc': {"('E2BBox', None, 14)": {'add': [63]}}}, {'path': 'opendevin/sandbox/sandbox.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [5]}, "('Sandbox', 'close', 28)": {'add': [29]}, "('Sandbox', None, 8)": {'mod': [8]}}}, {'path': 'opendevin/schema/config.py', 'status': 'modified', 'Loc': {"('ConfigType', None, 4)": {'add': [10]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "opendevin/sandbox/docker/ssh_box.py", "opendevin/schema/config.py", "agenthub/codeact_agent/codeact_agent.py", "opendevin/controller/action_manager.py", "opendevin/sandbox/docker/local_box.py", "opendevin/sandbox/e2b/sandbox.py", "opendevin/sandbox/sandbox.py", "opendevin/sandbox/docker/exec_box.py", "opendevin/agent.py", "opendevin/config.py", "opendevin/controller/agent_controller.py" ], "doc": [], "test": [], "config": [ "Makefile" ], "asset": [] }	1
deepfakes	faceswap	0ea743029db0d47f09d33ef90f50ad84c20b085f	https://github.com/deepfakes/faceswap/issues/263		Very slow extraction with scripts vs fakeapp 1.1	1080ti + OC'd 2600k using winpython 3.6.2 cuda 9.0 and tensorflow 1.6 Training utilizes ~50% of the GPU now (which is better than the ~25% utilized with FA 1.1) but extraction doesn't seem to utilize the GPU at all (getting around 1.33it/s) wheras with FA 1.1 I get around 17it/s - tried CNN and it dropped down to taking nearly a minute per file. Although I say it doesn't utilize the GPU it still seems to use all 11GB of RAM on the GPU, just none of the compute cores or processor are in use. CPU is using about 17%. Tried using extracted data from FA 1.1 with .py -convert but it just says 'no alignment found for file: x" for every file even tho --alignments points to the path with alignments.json I would've thought the alignments.json from FA 1.1 was compatible so I'm not sure if the above is a separate issue or not.	null	https://github.com/deepfakes/faceswap/pull/259	null	{'base_commit': '0ea743029db0d47f09d33ef90f50ad84c20b085f', 'files': [{'path': 'lib/FaceLandmarksExtractor/FaceLandmarksExtractor.py', 'status': 'modified', 'Loc': {"(None, 'initialize', 108)": {'add': [126], 'mod': [108, 117, 123, 124, 125]}, "(None, 'extract', 137)": {'mod': [137, 138, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 183]}}}, {'path': 'lib/cli.py', 'status': 'modified', 'Loc': {"('DirectoryProcessor', 'get_faces_alignments', 140)": {'mod': [149]}, "('DirectoryProcessor', 'get_faces', 159)": {'mod': [161, 165]}}}, {'path': 'lib/faces_detect.py', 'status': 'modified', 'Loc': {"(None, 'detect_faces', 3)": {'mod': [3, 4]}}}, {'path': 'scripts/extract.py', 'status': 'modified', 'Loc': {"('ExtractTrainingData', 'add_optional_arguments', 22)": {'mod': [25]}, "('ExtractTrainingData', 'process', 79)": {'mod': [95]}, "('ExtractTrainingData', 'processFiles', 100)": {'mod': [105]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "lib/faces_detect.py", "lib/cli.py", "lib/FaceLandmarksExtractor/FaceLandmarksExtractor.py", "scripts/extract.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
fastapi	fastapi	ef176c663195489b44030bfe1fb94a317762c8d5	https://github.com/fastapi/fastapi/issues/3323	feature reviewed	Support PEP 593 `Annotated` for specifying dependencies and parameters	### First check * [x] I added a very descriptive title to this issue. * [x] I used the GitHub search to find a similar issue and didn't find it. * [x] I searched the FastAPI documentation, with the integrated search. * [x] I already searched in Google "How to X in FastAPI" and didn't find any information. * [x] I already read and followed all the tutorial in the docs and didn't find an answer. * [x] I already checked if it is not related to FastAPI but to [Pydantic](https://github.com/samuelcolvin/pydantic). * [x] I already checked if it is not related to FastAPI but to [Swagger UI](https://github.com/swagger-api/swagger-ui). * [x] I already checked if it is not related to FastAPI but to [ReDoc](https://github.com/Redocly/redoc). * [x] After submitting this, I commit to: * Read open issues with questions until I find 2 issues where I can help someone and add a comment to help there. * Or, I already hit the "watch" button in this repository to receive notifications and I commit to help at least 2 people that ask questions in the future. * Implement a Pull Request for a confirmed bug. ### Example I propse to allow transforming: <!-- Replace the code below with your own self-contained, minimal, reproducible, example --> ```Python from typing import Optional from fastapi import Depends, FastAPI app = FastAPI() async def common_parameters(q: Optional[str] = None, skip: int = 0, limit: int = 100): return {"q": q, "skip": skip, "limit": limit} @app.get("/items/") async def read_items(commons: dict = Depends(common_parameters)): return commons ``` to ```Python from typing import Annotated, Optional from fastapi import Depends, FastAPI app = FastAPI() async def common_parameters(q: Optional[str] = None, skip: int = 0, limit: int = 100): return {"q": q, "skip": skip, "limit": limit} @app.get("/items/") async def read_items(commons: Annotated[dict, Depends(common_parameters)]): return commons ``` ### Discussion [PEP 593](https://www.python.org/dev/peps/pep-0593/) Added `Annotated` for adding additional annotations beyond type annotations. I think FastAPI's `Depends`, `Query`, `Body` and the likes fit well with the kind of additional annotations this supports. This would also make default values less awkward: ```python @app.get("/items/") async def read_items(q: Optional[str] = Query(None, max_length=50)): pass ``` Could become ```python @app.get("/items/") async def read_items(q: Annotated[Optional[str], Query(max_length=50)] = None): pass ``` This will also solve the issue mentioned [in the docs](https://fastapi.tiangolo.com/tutorial/path-params-numeric-validations/#order-the-parameters-as-you-need) of parameter ordering. Finally, it is sometimes convenient to use the same function as both a FastAPI dependency and a regular function. In these cases, because `= Depends(...)` is a default parameter value, if you forget to pass a parameter the error is not caught by your IDE. Worse, it is not caught at runtime because Python will just pass along the `Depends` object. This will probably cause an error down the road, but may silently succeed in some cases. I'm willing to implement this if you think it's a good idea.	null	https://github.com/fastapi/fastapi/pull/4871	null	{'base_commit': 'ef176c663195489b44030bfe1fb94a317762c8d5', 'files': [{'path': 'fastapi/dependencies/utils.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [58], 'mod': [51]}, "(None, 'get_dependant', 282)": {'add': [336], 'mod': [301, 303, 307, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335]}, "(None, 'get_param_sub_dependant', 114)": {'mod': [115, 117, 118, 119, 120, 121, 124, 126]}, "(None, 'add_non_field_param_to_dependency', 340)": {'mod': [341, 343, 344, 346, 347, 349, 350, 352, 353, 355, 356, 358, 359]}, "(None, 'get_param_field', 364)": {'mod': [364, 366, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 416]}}}, {'path': 'fastapi/param_functions.py', 'status': 'modified', 'Loc': {"(None, 'Path', 7)": {'mod': [8]}}}, {'path': 'fastapi/params.py', 'status': 'modified', 'Loc': {"('Path', '__init__', 63)": {'add': [82], 'mod': [65, 85]}, "('Form', '__init__', 280)": {'mod': [282]}, "('File', '__init__', 320)": {'mod': [322]}}}, {'path': 'fastapi/utils.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [1]}, "(None, 'create_response_field', 60)": {'mod': [76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 88]}}}, {'path': 'tests/main.py', 'status': 'modified', 'Loc': {"(None, 'get_path_param_id', 52)": {'mod': [52, 53, 56, 57]}}}, {'path': 'tests/test_application.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257]}}}, {'path': 'tests/test_params_repr.py', 'status': 'modified', 'Loc': {"(None, 'test_path_repr', 22)": {'mod': [22, 23]}}}, {'path': 'tests/test_path.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [196]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "fastapi/dependencies/utils.py", "fastapi/utils.py", "fastapi/param_functions.py", "tests/main.py", "fastapi/params.py" ], "doc": [], "test": [ "tests/test_params_repr.py", "tests/test_application.py", "tests/test_path.py" ], "config": [], "asset": [] }	1
python	cpython	e01eeb7b4b8d00b9f5c6acb48957f46ac4e252c0	https://github.com/python/cpython/issues/92417	docs	Many references to unsupported Python versions in the stdlib docs	Documentation There are currently many places in the stdlib docs where there are needless comments about how to maintain compatibility with Python versions that are now end-of-life. Many of these can now be removed, to improve brevity and clarity in the documentation. I plan to submit a number of PRs to fix these. PRs: - #92418 - #92419 - #92420 - #92421 - #92422 - #92423 - #92424 - #92425 - https://github.com/python/cpython/pull/92502 - #92538 - #92539 - #92543 - #92544 - [More to come] Backports: - https://github.com/python/cpython/pull/92459 - https://github.com/python/cpython/pull/92460 - https://github.com/python/cpython/pull/92461 - https://github.com/python/cpython/pull/92462 - https://github.com/python/cpython/pull/92463 - https://github.com/python/cpython/pull/92491 - https://github.com/python/cpython/pull/92467 - https://github.com/python/cpython/pull/92468 - https://github.com/python/cpython/pull/92492 - https://github.com/python/cpython/pull/92464 - https://github.com/python/cpython/pull/92465 - https://github.com/python/cpython/pull/92466 - https://github.com/python/cpython/pull/92472 - https://github.com/python/cpython/pull/92473 - https://github.com/python/cpython/pull/92474 - https://github.com/python/cpython/pull/92485 - https://github.com/python/cpython/pull/92486 - https://github.com/python/cpython/pull/92487 - https://github.com/python/cpython/pull/92606 - https://github.com/python/cpython/pull/92607	null	https://github.com/python/cpython/pull/92539	null	{'base_commit': 'e01eeb7b4b8d00b9f5c6acb48957f46ac4e252c0', 'files': [{'path': 'Doc/library/unittest.mock-examples.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [663]}}}, {'path': 'Doc/library/unittest.mock.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [2384]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": " ", "info_type": "" }	{ "code": [], "doc": [ "Doc/library/unittest.mock-examples.rst", "Doc/library/unittest.mock.rst" ], "test": [], "config": [], "asset": [] }	1
scikit-learn	scikit-learn	23d8761615d0417eef5f52cc796518e44d41ca2a	https://github.com/scikit-learn/scikit-learn/issues/19248	Documentation module:cluster	Birch should be called BIRCH	C.f. the original paper. Zhang, T.; Ramakrishnan, R.; Livny, M. (1996). "BIRCH: an efficient data clustering method for very large databases". Proceedings of the 1996 ACM SIGMOD international conference on Management of data - SIGMOD '96. pp. 103–114. doi:10.1145/233269.233324	null	https://github.com/scikit-learn/scikit-learn/pull/19368	null	{'base_commit': '23d8761615d0417eef5f52cc796518e44d41ca2a', 'files': [{'path': 'doc/modules/clustering.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [106, 946, 965, 999, 1001, 1005]}}}, {'path': 'examples/cluster/plot_birch_vs_minibatchkmeans.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [6, 39, 48, 58, 78]}}}, {'path': 'examples/cluster/plot_cluster_comparison.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [146]}}}, {'path': 'sklearn/cluster/_birch.py', 'status': 'modified', 'Loc': {"('Birch', None, 335)": {'mod': [336]}, "('Birch', '_global_clustering', 648)": {'mod': [677]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "examples/cluster/plot_birch_vs_minibatchkmeans.py", "sklearn/cluster/_birch.py", "examples/cluster/plot_cluster_comparison.py" ], "doc": [ "doc/modules/clustering.rst" ], "test": [], "config": [], "asset": [] }	1
localstack	localstack	65b807e4e95fe6da3e30f13e4271dc9dcfaa334e	https://github.com/localstack/localstack/issues/402	type: bug	Dynamodbstreams Use Kinesis Shard Identifiers	<!-- Love localstack? Please consider supporting our collective: 👉 https://opencollective.com/localstack/donate --> Dynamodbstreams seem to be making use of Kinesis shard identifiers which are considered invalid by botocore request validators. Error response from boto3 when attempting to `get_shard_iterator` from shard ids returned from `describe_stream`: ``` [test-integration:L51:27s] exception = ParamValidationError(u'Parameter validation failed:\nInvalid length for parameter ShardId, value: 20, valid range: 28-inf',) [test-integration:L52:27s] [test-integration:L53:27s] def _reraise_exception(self, exception): [test-integration:L54:27s] if hasattr(exception, 'response'): [test-integration:L55:27s] code = exception.response['Error']['Code'] [test-integration:L56:27s] [test-integration:L57:27s] if code == 'TrimmedDataAccessException': [test-integration:L58:27s] raise TrimmedRecordsException() [test-integration:L59:27s] elif code == 'ResourceNotFoundException': [test-integration:L60:27s] raise ResourceDNEException() [test-integration:L61:27s] [test-integration:L62:27s] > raise exception [test-integration:L63:27s] E ParamValidationError: Parameter validation failed: [test-integration:L64:27s] E Invalid length for parameter ShardId, value: 20, valid range: 28-inf [test-integration:L65:27s] [test-integration:L66:27s] .tox/py27/lib/python2.7/site-packages/pyrokinesis/dynamodbstreams_ingress_backend.py:111: ParamValidationError ``` The following is the response object I am getting back when I `describe_stream` on the stream's ARN: ``` [test-integration:L68:27s] {'ResponseMetadata': {'HTTPStatusCode': 200, 'RetryAttempts': 0, 'HTTPHeaders': {'content-length': '692', 'access-control-allow-origin': '', 'date': 'Fri, 13 Oct 2017 12:47:00 GMT', 'server': 'Werkzeug/0.12.2 Python/2.7.13', 'content-type': 'application/json'}}, u'StreamDescription': {u'StreamLabel': u'TODO', u'StreamArn': u'arn:aws:dynamodb:us-east-1:000000000000:table/DynamoTest/stream/2017-10-13T12:47:00', u'Shards': [{u'ShardId': u'shardId-000000000000', u'SequenceNumberRange': {u'StartingSequenceNumber': u'49577893583130519883135457518096755974321873497073123330'}}], u'KeySchema': [{u'KeyType': u'HASH', u'AttributeName': u'ID'}], u'TableName': u'DynamoTest', u'StreamStatus': u'ENABLED'}} ``` My localstack setup: ``` localstack 0.7.3 [localstack:L2:1s] 2017-10-13 15:10:35,915 INFO spawned: 'dashboard' with pid 13 [localstack:L3:1s] 2017-10-13 15:10:35,917 INFO spawned: 'infra' with pid 14 [localstack:L4:1s] (. .venv/bin/activate; bin/localstack web --port=8080) [localstack:L5:1s] (. .venv/bin/activate; exec bin/localstack start) [localstack:L6:1s] Starting local dev environment. CTRL-C to quit. [localstack:L7:1s] Running on http://0.0.0.0:8080/ (Press CTRL+C to quit) [localstack:L8:1s] * Restarting with stat [localstack:L9:1s] Starting mock Kinesis (http port 4568)... [localstack:L10:1s] Starting mock S3 (http port 4572)... [localstack:L11:1s] Starting mock DynamoDB (http port 4569)... [localstack:L12:1s] * Debugger is active! [localstack:L13:2s] * Debugger PIN: 281-540-735 [localstack:L14:2s] 2017-10-13 15:10:37,123 INFO success: dashboard entered RUNNING state, process has stayed up for > than 1 seconds (startsecs) [localstack:L15:2s] 2017-10-13 15:10:37,123 INFO success: infra entered RUNNING state, process has stayed up for > than 1 seconds (startsecs) [localstack:L16:2s] Starting mock DynamoDB Streams service (http port 4570)... [localstack:L17:2s] Listening at http://:::4565 [localstack:L18:2s] Initializing DynamoDB Local with the following configuration: [localstack:L19:2s] Port: 4564 [localstack:L20:2s] InMemory: false [localstack:L21:2s] DbPath: /tmp/localstack/dynamodb [localstack:L22:2s] SharedDb: true [localstack:L23:2s] shouldDelayTransientStatuses: false [localstack:L24:2s] CorsParams: * [localstack:L25:2s] [localstack:L26:2s] * Running on http://0.0.0.0:4563/ (Press CTRL+C to quit) ```	null	https://github.com/localstack/localstack/pull/403	null	{'base_commit': '65b807e4e95fe6da3e30f13e4271dc9dcfaa334e', 'files': [{'path': 'localstack/services/dynamodbstreams/dynamodbstreams_api.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [1, 119]}, "(None, 'post_request', 47)": {'add': [76], 'mod': [70, 78]}}}]}	[]	[]	[]	{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "localstack/services/dynamodbstreams/dynamodbstreams_api.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
pallets	flask	ee76129812419d473eb62434051e81d5855255b6	https://github.com/pallets/flask/issues/602		Misspelling in docs @ flask.Flask.handle_exception	`Default exception handling that kicks in when an exception occours that is not caught. In debug mode the exception will be re-raised immediately, otherwise it is logged and the handler for a 500 internal server error is used. If no such handler exists, a default 500 internal server error message is displayed.` Occours should be occurs. I looked around in the project code to see if i could update this, but it looks like the docs subdir is no longer used? I could be wrong, if you let me know where this is at I'll update it and send a PR :)	null	https://github.com/pallets/flask/pull/603	null	{'base_commit': 'ee76129812419d473eb62434051e81d5855255b6', 'files': [{'path': 'flask/app.py', 'status': 'modified', 'Loc': {"('Flask', 'handle_exception', 1266)": {'mod': [1268]}}}]}	[]	[]	[]	{ "iss_type": "3", "iss_reason": "1", "loc_way": "pr", "loc_scope": "不太确定问题类别，因为是开发者询问typo error", "info_type": "" }	{ "code": [ "flask/app.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
ansible	ansible	79d00adc52a091d0ddd1d8a96b06adf2f67f161b	https://github.com/ansible/ansible/issues/36378	cloud aws module affects_2.4 support:certified docs	Documentation Error for ec2_vpc_nacl rules	##### ISSUE TYPE - Documentation Report ##### COMPONENT NAME ec2_vpc_nacl ##### ANSIBLE VERSION ``` ansible 2.4.3.0 config file = None configured module search path = [u'/home/ubuntu/.ansible/plugins/modules', u'/usr/share/ansible/plugins/modules'] ansible python module location = /usr/local/lib/python2.7/dist-packages/ansible executable location = /usr/local/bin/ansible python version = 2.7.12 (default, Dec 4 2017, 14:50:18) [GCC 5.4.0 20160609] ``` ##### CONFIGURATION ##### OS / ENVIRONMENT N/A ##### SUMMARY The example documentation is the wrong way round for ec2_vpc_nacl with respect to the icmp code and type. ##### STEPS TO REPRODUCE https://github.com/ansible/ansible/blob/devel/lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py#L87 has the order of the `icmp_code` and `icmp_type` inverted compared to the code that parses it https://github.com/ansible/ansible/blob/devel/lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py#L298 ##### EXPECTED RESULTS ##### ACTUAL RESULTS	null	https://github.com/ansible/ansible/pull/36380	null	{'base_commit': '79d00adc52a091d0ddd1d8a96b06adf2f67f161b', 'files': [{'path': 'lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [87]}}}]}	[]	[]	[]	{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py" ], "doc": [], "test": [], "config": [], "asset": [] }	1
geekan	MetaGPT	a32e238801d0a8f3c1bd97b98d038b40977a8cc6	https://github.com/geekan/MetaGPT/issues/1174		New provider: Amazon Bedrock (AWS)	Feature description Please include support for Amazon Bedrock models. These models can be from Amazon, Anthropic, AI21, Cohere, Mistral, or Meta Llama 2. Your Feature 1. Create a new LLM Provides under [metagpt/provider](https://github.com/geekan/MetaGPT/tree/db65554c4931d4a95e20331b770cf4f7e5202264/metagpt/provider) for Amazon Bedrock 2. Include it in the [LLMType](https://github.com/geekan/MetaGPT/blob/db65554c4931d4a95e20331b770cf4f7e5202264/metagpt/configs/llm_config.py#L17) available	null	https://github.com/geekan/MetaGPT/pull/1231	null	{'base_commit': 'a32e238801d0a8f3c1bd97b98d038b40977a8cc6', 'files': [{'path': 'config/puppeteer-config.json', 'status': 'modified', 'Loc': {}}, {'path': 'metagpt/configs/llm_config.py', 'status': 'modified', 'Loc': {"('LLMType', None, 17)": {'add': [34]}, "('LLMConfig', None, 40)": {'add': [80], 'mod': [77]}}}, {'path': 'metagpt/provider/__init__.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [19, 32]}}}, {'path': 'metagpt/utils/token_counter.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [212]}}}, {'path': 'requirements.txt', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [72]}}}, {'path': 'tests/metagpt/provider/mock_llm_config.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [62]}}}, {'path': 'tests/metagpt/provider/req_resp_const.py', 'status': 'modified', 'Loc': {"(None, 'llm_general_chat_funcs_test', 174)": {'add': [185]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": null, "info_type": null }	{ "code": [ "metagpt/utils/token_counter.py", "metagpt/provider/__init__.py", "metagpt/configs/llm_config.py", "config/puppeteer-config.json", "tests/metagpt/provider/mock_llm_config.py", "tests/metagpt/provider/req_resp_const.py" ], "doc": [], "test": [], "config": [ "requirements.txt" ], "asset": [] }	1
pandas-dev	pandas	862cd05df4452592a99dd1a4fa10ce8cfb3766f7	https://github.com/pandas-dev/pandas/issues/37494	Enhancement Groupby ExtensionArray NA - MaskedArrays Closing Candidate	ENH: improve the resulting dtype for groupby operations on nullable dtypes	Follow-up on https://github.com/pandas-dev/pandas/pull/37433, and partly related to https://github.com/pandas-dev/pandas/issues/37493 Currently, after groupby operations we try to cast back to the original dtype when possible (at least in case of extension arrays). But this is not always correct, and also not done consistently. Some examples using the test case from the mentioned PR using a nullable Int64 column as input: ``` In [1]: df = DataFrame( ...: { ...: "A": ["A", "B"] * 5, ...: "B": pd.array([1, 2, 3, 4, 5, 6, 7, 8, 9, pd.NA], dtype="Int64"), ...: } ...: ) In [2]: df.groupby("A")["B"].sum() Out[2]: A A 25 B 20 Name: B, dtype: Int64 In [3]: df.groupby("A")["B"].std() Out[3]: A A 3.162278 B 2.581989 Name: B, dtype: float64 In [4]: df.groupby("A")["B"].mean() Out[4]: A A 5 B 5 Name: B, dtype: Int64 In [5]: df.groupby("A")["B"].count() Out[5]: A A 5 B 4 Name: B, dtype: int64 ``` So some observations: * For `sum()`, we correctly have Int64 for the result * For `std()`, we could use the nullable Float64 instead of float64 dtype * For `mean()`, we incorrectly cast back to Int64 dtype, as the result of mean should always be floating (in this case the casting just happened to work because the means were rounded numbers) * For `count()`, we did not create a nullable Int64 dtype for the result, while this could be done in the input is nullable	null	https://github.com/pandas-dev/pandas/pull/38291	null	{'base_commit': '862cd05df4452592a99dd1a4fa10ce8cfb3766f7', 'files': [{'path': 'pandas/core/dtypes/cast.py', 'status': 'modified', 'Loc': {"(None, 'maybe_cast_result_dtype', 342)": {'mod': [360, 362, 363, 364, 365]}}}, {'path': 'pandas/core/groupby/ops.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [47]}, "('BaseGrouper', '_ea_wrap_cython_operation', 493)": {'mod': [524]}}}, {'path': 'pandas/tests/arrays/integer/test_arithmetic.py', 'status': 'modified', 'Loc': {"(None, 'test_reduce_to_float', 261)": {'mod': [280]}}}, {'path': 'pandas/tests/groupby/aggregate/test_cython.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [7]}, "(None, 'test_cython_agg_nullable_int', 297)": {'add': [314]}}}, {'path': 'pandas/tests/groupby/test_function.py', 'status': 'modified', 'Loc': {"(None, 'test_apply_to_nullable_integer_returns_float', 1091)": {'mod': [1096]}}}, {'path': 'pandas/tests/resample/test_datetime_index.py', 'status': 'modified', 'Loc': {"(None, 'test_resample_integerarray', 112)": {'mod': [127]}}}]}	[]	[]	[]	{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }	{ "code": [ "pandas/core/dtypes/cast.py", "pandas/core/groupby/ops.py" ], "doc": [], "test": [ "pandas/tests/groupby/aggregate/test_cython.py", "pandas/tests/arrays/integer/test_arithmetic.py", "pandas/tests/resample/test_datetime_index.py", "pandas/tests/groupby/test_function.py" ], "config": [], "asset": [] }	1

scikit-learn

559609fe98ec2145788133687e64a6e87766bc77

https://github.com/scikit-learn/scikit-learn/issues/25525

Bug module:feature_extraction

Extend SequentialFeatureSelector example to demonstrate how to use negative tol

### Describe the bug I utilized the **SequentialFeatureSelector** for feature selection in my code, with the direction set to "backward." The tolerance value is negative and the selection process stops when the decrease in the metric, AUC in this case, is less than the specified tolerance. Generally, increasing the number of features results in a higher AUC, but sacrificing some features, especially correlated ones that offer little contribution, can produce a pessimistic model with a lower AUC. The code worked as expected in **sklearn 1.1.1**, but when I updated to **sklearn 1.2.1**, I encountered the following error. ### Steps/Code to Reproduce ```python from sklearn.datasets import load_breast_cancer from sklearn.linear_model import LogisticRegression from sklearn.feature_selection import SequentialFeatureSelector from sklearn.preprocessing import StandardScaler from sklearn.pipeline import Pipeline X, y = load_breast_cancer(return_X_y=True) TOL = -0.001 feature_selector = SequentialFeatureSelector( LogisticRegression(max_iter=1000), n_features_to_select="auto", direction="backward", scoring="roc_auc", tol=TOL ) pipe = Pipeline( [('scaler', StandardScaler()), ('feature_selector', feature_selector), ('log_reg', LogisticRegression(max_iter=1000))] ) if __name__ == "__main__": pipe.fit(X, y) print(pipe['log_reg'].coef_[0]) ``` ### Expected Results ``` $ python sfs_tol.py [-2.0429818 0.5364346 -1.35765488 -2.85009904 -2.84603016] ``` ### Actual Results ```python-traceback $ python sfs_tol.py Traceback (most recent call last): File "/home/modelling/users-workspace/nsofinij/lab/open-source/sfs_tol.py", line 28, in <module> pipe.fit(X, y) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/pipeline.py", line 401, in fit Xt = self._fit(X, y, **fit_params_steps) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/pipeline.py", line 359, in _fit X, fitted_transformer = fit_transform_one_cached( File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/joblib/memory.py", line 349, in __call__ return self.func(*args, **kwargs) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/pipeline.py", line 893, in _fit_transform_one res = transformer.fit_transform(X, y, **fit_params) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/utils/_set_output.py", line 142, in wrapped data_to_wrap = f(self, X, *args, **kwargs) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/base.py", line 862, in fit_transform return self.fit(X, y, **fit_params).transform(X) File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/feature_selection/_sequential.py", line 201, in fit self._validate_params() File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/base.py", line 581, in _validate_params validate_parameter_constraints( File "/home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/sklearn/utils/_param_validation.py", line 97, in validate_parameter_constraints raise InvalidParameterError( sklearn.utils._param_validation.InvalidParameterError: The 'tol' parameter of SequentialFeatureSelector must be None or a float in the range (0, inf). Got -0.001 instead. ``` ### Versions ```shell System: python: 3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:26:04) [GCC 10.4.0] executable: /home/modelling/opt/anaconda3/envs/py310/bin/python machine: Linux-4.14.301-224.520.amzn2.x86_64-x86_64-with-glibc2.26 Python dependencies: sklearn: 1.2.1 pip: 23.0 setuptools: 66.1.1 numpy: 1.24.1 scipy: 1.10.0 Cython: None pandas: 1.5.3 matplotlib: 3.6.3 joblib: 1.2.0 threadpoolctl: 3.1.0 Built with OpenMP: True threadpoolctl info: user_api: openmp internal_api: openmp prefix: libgomp filepath: /home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/scikit_learn.libs/libgomp-a34b3233.so.1.0.0 version: None num_threads: 64 user_api: blas internal_api: openblas prefix: libopenblas filepath: /home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/numpy.libs/libopenblas64_p-r0-15028c96.3.21.so version: 0.3.21 threading_layer: pthreads architecture: SkylakeX num_threads: 64 user_api: blas internal_api: openblas prefix: libopenblas filepath: /home/modelling/opt/anaconda3/envs/py310/lib/python3.10/site-packages/scipy.libs/libopenblasp-r0-41284840.3.18.so version: 0.3.18 threading_layer: pthreads architecture: SkylakeX num_threads: 64 ```

null

https://github.com/scikit-learn/scikit-learn/pull/26205

null

{'base_commit': '559609fe98ec2145788133687e64a6e87766bc77', 'files': [{'path': 'examples/feature_selection/plot_select_from_model_diabetes.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [145], 'mod': [123, 124, 125]}}}]}

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{ "code": [ "examples/feature_selection/plot_select_from_model_diabetes.py" ], "doc": [], "test": [], "config": [], "asset": [] }

null

pallets

flask

cb94f4c5d3d4e1797207fd03d20d06c7bc0d05b4

https://github.com/pallets/flask/issues/2264

cli

Handle app factory in FLASK_APP

`FLASK_APP=myproject.app:create_app('dev')` [ Gunicorn does this with `eval`](https://github.com/benoitc/gunicorn/blob/fbd151e9841e2c87a18512d71475bcff863a5171/gunicorn/util.py#L364), which I'm not super happy with. Instead, we could use `literal_eval` to allow a simple list of arguments. The line should never be so complicated that `eval` would be necessary anyway. ~~~python # might need to fix this regex m = re.search(r'(\w+)($.*$)', app_obj) if m: app = getattr(mod, m.group(1))(*literal_eval(m.group(2))) ~~~

null

https://github.com/pallets/flask/pull/2326

null

{'base_commit': 'cb94f4c5d3d4e1797207fd03d20d06c7bc0d05b4', 'files': [{'path': 'flask/cli.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [11, 12]}, "(None, 'find_best_app', 32)": {'mod': [58, 62, 69, 71]}, "(None, 'call_factory', 82)": {'mod': [82, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93]}, "(None, 'locate_app', 125)": {'mod': [151, 153, 154, 155, 156, 158]}}}, {'path': 'tests/test_cli.py', 'status': 'modified', 'Loc': {"(None, 'test_locate_app', 148)": {'add': [152], 'mod': [154, 155, 156, 157, 158, 159, 160, 161]}}}]}

[]

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{ "code": [ "flask/cli.py" ], "doc": [], "test": [ "tests/test_cli.py" ], "config": [], "asset": [] }

1

localstack

737ca72b7bce6e377dd6876eacee63338fa8c30c

https://github.com/localstack/localstack/issues/894

ERROR:localstack.services.generic_proxy: Error forwarding request:

Starting local dev environment. CTRL-C to quit. Starting mock API Gateway (http port 4567)... Starting mock DynamoDB (http port 4569)... Starting mock SES (http port 4579)... Starting mock Kinesis (http port 4568)... Starting mock Redshift (http port 4577)... Starting mock S3 (http port 4572)... Starting mock CloudWatch (http port 4582)... Starting mock CloudFormation (http port 4581)... Starting mock SSM (http port 4583)... Starting mock SQS (http port 4576)... Starting local Elasticsearch (http port 4571)... Starting mock SNS (http port 4575)... Starting mock DynamoDB Streams service (http port 4570)... Starting mock Firehose service (http port 4573)... Starting mock Route53 (http port 4580)... Starting mock ES service (http port 4578)... Starting mock Lambda service (http port 4574)... 2018-08-11T13:33:08:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d442415d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, **send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d442415d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) 2018-08-11T13:34:08:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425fa10>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, **send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425fa10>: Failed to establish a new connection: [Errno 111] Connection refused',)) 2018-08-11T13:35:09:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4429c3d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, **send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4429c3d0>: Failed to establish a new connection: [Errno 111] Connection refused',)) 2018-08-11T13:36:09:ERROR:localstack.services.generic_proxy: Error forwarding request: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425f910>: Failed to establish a new connection: [Errno 111] Connection refused',)) Traceback (most recent call last): File "/home/maruf/.local/lib/python2.7/site-packages/localstack/services/generic_proxy.py", line 201, in forward headers=forward_headers) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 112, in post return request('post', url, data=data, json=json, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/api.py", line 58, in request return session.request(method=method, url=url, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 508, in request resp = self.send(prep, **send_kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/sessions.py", line 618, in send r = adapter.send(request, **kwargs) File "/home/maruf/.local/lib/python2.7/site-packages/requests/adapters.py", line 508, in send raise ConnectionError(e, request=request) ConnectionError: HTTPConnectionPool(host='127.0.0.1', port=4564): Max retries exceeded with url: / (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f4d4425f910>: Failed to establish a new connection: [Errno 111] Connection refused',))

null

https://github.com/localstack/localstack/pull/1526

null

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[]

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{ "code": [ "localstack/config.py", "localstack/services/kinesis/kinesis_starter.py" ], "doc": [ "README.md" ], "test": [], "config": [], "asset": [] }

1

huggingface

transformers

d2871b29754abd0f72cf42c299bb1c041519f7bc

https://github.com/huggingface/transformers/issues/30

[Feature request] Add example of finetuning the pretrained models on custom corpus

null

https://github.com/huggingface/transformers/pull/25107

null

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1

pandas-dev

pandas

51a70dcb7133bc7cb8e6bea5da39a2cf58fa8319

https://github.com/pandas-dev/pandas/issues/11080

Indexing Performance

PERF: checking is_monotonic_increasing/decreasing before sorting on an index

We don't keep the sortedness state in an index per-se, but it is rather cheap to check - `is_monotonic_increasing` or `is_monotonic_decreasing` on a reg-index - MultiIndex should check `is_lexsorted` (this might be done already) ``` In [8]: df = DataFrame(np.random.randn(1000000,2),columns=list('AB')) In [9]: %timeit df.sort_index() 10 loops, best of 3: 37.1 ms per loop In [10]: %timeit -n 1 -r 1 df.index.is_monotonic_increasing 1 loops, best of 1: 2.01 ms per loop In [11]: %timeit -n 1 -r 1 df.index.is_monotonic_increasin^C KeyboardInterrupt In [11]: %timeit df.set_index('A').sort_index() 10 loops, best of 3: 175 ms per loop In [12]: %timeit -n 1 -r 1 df.set_index('A').index.is_monotonic_increasing 1 loops, best of 1: 9.54 ms per loop ```

null

https://github.com/pandas-dev/pandas/pull/11294

null

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1

zylon-ai

private-gpt

fdb45741e521d606b028984dbc2f6ac57755bb88

https://github.com/zylon-ai/private-gpt/issues/10

Suggestions for speeding up ingestion?

I presume I must be doing something wrong, as it is taking hours to ingest a 500kbyte text on an i9-12900 with 128GB. In fact it's not even done yet. Using models are recommended. Help? Thanks Some output: llama_print_timings: load time = 674.34 ms llama_print_timings: sample time = 0.00 ms / 1 runs ( 0.00 ms per run) llama_print_timings: prompt eval time = 12526.78 ms / 152 tokens ( 82.41 ms per token) llama_print_timings: eval time = 157.46 ms / 1 runs ( 157.46 ms per run) llama_print_timings: total time = 12715.48 ms

null

https://github.com/zylon-ai/private-gpt/pull/224

null

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1

huggingface

transformers

9fef668338b15e508bac99598dd139546fece00b

https://github.com/huggingface/transformers/issues/9

Crash at the end of training

Hi, I tried running the Squad model this morning (on a single GPU with gradient accumulation over 3 steps) but after 3 hours of training, my job failed with the following output: I was running the code, unmodified, from commit 3bfbc21376af691b912f3b6256bbeaf8e0046ba8 Is this an issue you know about? ``` 11/08/2018 17:50:03 - INFO - __main__ - device cuda n_gpu 1 distributed training False 11/08/2018 17:50:18 - INFO - __main__ - *** Example *** 11/08/2018 17:50:18 - INFO - __main__ - unique_id: 1000000000 11/08/2018 17:50:18 - INFO - __main__ - example_index: 0 11/08/2018 17:50:18 - INFO - __main__ - doc_span_index: 0 11/08/2018 17:50:18 - INFO - __main__ - tokens: [CLS] to whom did the virgin mary allegedly appear in 1858 in lou ##rdes france ? [SEP] architectural ##ly , the school has a catholic character . atop the main building ' s gold dome is a golden statue of the virgin mary . immediately in front of the main building and facing it , is a copper statue of christ with arms up ##rai ##sed with the legend " ve ##ni ##te ad me om ##nes " . next to the main building is the basilica of the sacred heart . immediately behind the basilica is the gr ##otto , a marian place of prayer and reflection . it is a replica of the gr ##otto at lou ##rdes , france where the virgin mary reputed ##ly appeared to saint bern ##ade ##tte so ##ub ##iro ##us in 1858 . at the end of the main drive ( and in a direct line that connects through 3 statues and the gold dome ) , is a simple , modern stone statue of mary . [SEP] 11/08/2018 17:50:18 - INFO - __main__ - token_to_orig_map: 17:0 18:0 19:0 20:1 21:2 22:3 23:4 24:5 25:6 26:6 27:7 28:8 29:9 30:10 31:10 32:10 33:11 34:12 35:13 36:14 37:15 38:16 39:17 40:18 41:19 42:20 43:20 44:21 45:22 46:23 47:24 48:25 49:26 50:27 51:28 52:29 53:30 54:30 55:31 56:32 57:33 58:34 59:35 60:36 61:37 62:38 63:39 64:39 65:39 66:40 67:41 68:42 69:43 70:43 71:43 72:43 73:44 74:45 75:46 76:46 77:46 78:46 79:47 80:48 81:49 82:50 83:51 84:52 85:53 86:54 87:55 88:56 89:57 90:58 91:58 92:59 93:60 94:61 95:62 96:63 97:64 98:65 99:65 100:65 101:66 102:67 103:68 104:69 105:70 106:71 107:72 108:72 109:73 110:74 111:75 112:76 113:77 114:78 115:79 116:79 117:80 118:81 119:81 120:81 121:82 122:83 123:84 124:85 125:86 126:87 127:87 128:88 129:89 130:90 131:91 132:91 133:91 134:92 135:92 136:92 137:92 138:93 139:94 140:94 141:95 142:96 143:97 144:98 145:99 146:100 147:101 148:102 149:102 150:103 151:104 152:105 153:106 154:107 155:108 156:109 157:110 158:111 159:112 160:113 161:114 162:115 163:115 164:115 165:116 166:117 167:118 168:118 169:119 170:120 171:121 172:122 173:123 174:123 11/08/2018 17:50:18 - INFO - __main__ - token_is_max_context: 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 11/08/2018 17:50:18 - INFO - __main__ - input_ids: 101 2000 3183 2106 1996 6261 2984 9382 3711 1999 8517 1999 10223 26371 2605 1029 102 6549 2135 1010 1996 2082 2038 1037 3234 2839 1012 10234 1996 2364 2311 1005 1055 2751 8514 2003 1037 3585 6231 1997 1996 6261 2984 1012 3202 1999 2392 1997 1996 2364 2311 1998 5307 2009 1010 2003 1037 6967 6231 1997 4828 2007 2608 2039 14995 6924 2007 1996 5722 1000 2310 3490 2618 4748 2033 18168 5267 1000 1012 2279 2000 1996 2364 2311 2003 1996 13546 1997 1996 6730 2540 1012 3202 2369 1996 13546 2003 1996 24665 23052 1010 1037 14042 2173 1997 7083 1998 9185 1012 2009 2003 1037 15059 1997 1996 24665 23052 2012 10223 26371 1010 2605 2073 1996 6261 2984 22353 2135 2596 2000 3002 16595 9648 4674 2061 12083 9711 2271 1999 8517 1012 2012 1996 2203 1997 1996 2364 3298 1006 1998 1999 1037 3622 2240 2008 8539 2083 1017 11342 1998 1996 2751 8514 1007 1010 2003 1037 3722 1010 2715 2962 6231 1997 2984 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11/08/2018 17:50:18 - INFO - __main__ - input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... [truncated] ... Iteration: 100%|█████████▉| 29314/29324 [3:27:55<00:04, 2.36it/s][A Iteration: 100%|█████████▉| 29315/29324 [3:27:55<00:03, 2.44it/s][A Iteration: 100%|█████████▉| 29316/29324 [3:27:56<00:03, 2.26it/s][A Iteration: 100%|█████████▉| 29317/29324 [3:27:56<00:02, 2.35it/s][A Iteration: 100%|█████████▉| 29318/29324 [3:27:56<00:02, 2.44it/s][A Iteration: 100%|█████████▉| 29319/29324 [3:27:57<00:02, 2.25it/s][A Iteration: 100%|█████████▉| 29320/29324 [3:27:57<00:01, 2.35it/s][A Iteration: 100%|█████████▉| 29321/29324 [3:27:58<00:01, 2.41it/s][A Iteration: 100%|█████████▉| 29322/29324 [3:27:58<00:00, 2.25it/s][A Iteration: 100%|█████████▉| 29323/29324 [3:27:59<00:00, 2.36it/s][ATraceback (most recent call last): File "code/run_squad.py", line 929, in <module> main() File "code/run_squad.py", line 862, in main loss = model(input_ids, segment_ids, input_mask, start_positions, end_positions) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 477, in __call__ result = self.forward(*input, **kwargs) File "/0x0d4ff90d01fa4168983197b17d73bb0c_dependencies/code/modeling.py", line 467, in forward start_loss = loss_fct(start_logits, start_positions) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 477, in __call__ result = self.forward(*input, **kwargs) File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/loss.py", line 862, in forward ignore_index=self.ignore_index, reduction=self.reduction) File "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py", line 1550, in cross_entropy return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction) File "/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py", line 1403, in nll_loss if input.size(0) != target.size(0): RuntimeError: dimension specified as 0 but tensor has no dimensions Exception ignored in: <bound method tqdm.__del__ of Iteration: 100%|█████████▉| 29323/29324 [3:27:59<00:00, 2.36it/s]> Traceback (most recent call last): File "/usr/local/lib/python3.6/dist-packages/tqdm/_tqdm.py", line 931, in __del__ self.close() File "/usr/local/lib/python3.6/dist-packages/tqdm/_tqdm.py", line 1133, in close self._decr_instances(self) File "/usr/local/lib/python3.6/dist-packages/tqdm/_tqdm.py", line 496, in _decr_instances cls.monitor.exit() File "/usr/local/lib/python3.6/dist-packages/tqdm/_monitor.py", line 52, in exit self.join() File "/usr/lib/python3.6/threading.py", line 1053, in join raise RuntimeError("cannot join current thread") RuntimeError: cannot join current thread ```

null

https://github.com/huggingface/transformers/pull/16310

null

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1

psf

requests

ccabcf1fca906bfa6b65a3189c1c41061e6c1042

https://github.com/psf/requests/issues/3698

AttributeError: 'NoneType' object has no attribute 'read'

Hello :) After a recent upgrade for our [coala](https://github.com/coala/coala) project to `requests` 2.12.1 we encounter an exception in our test suites which seems to be caused by `requests`. Build: https://ci.appveyor.com/project/coala/coala-bears/build/1.0.3537/job/1wm7b4u9yhgkxkgn Relevant part: ``` ================================== FAILURES =================================== _________________ InvalidLinkBearTest.test_redirect_threshold _________________ self = <tests.general.InvalidLinkBearTest.InvalidLinkBearTest testMethod=test_redirect_threshold> def test_redirect_threshold(self): long_url_redirect = """ https://bitbucket.org/api/301 https://bitbucket.org/api/302 """.splitlines() short_url_redirect = """ http://httpbin.org/status/301 """.splitlines() self.assertResult(valid_file=long_url_redirect, invalid_file=short_url_redirect, > settings={'follow_redirects': 'yeah'}) tests\general\InvalidLinkBearTest.py:157: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests\general\InvalidLinkBearTest.py:75: in assertResult out = list(uut.run("valid", valid_file, **settings)) bears\general\InvalidLinkBear.py:80: in run file, timeout, link_ignore_regex): bears\general\InvalidLinkBear.py:53: in find_links_in_file code = InvalidLinkBear.get_status_code(link, timeout) bears\general\InvalidLinkBear.py:37: in get_status_code timeout=timeout).status_code C:\Python34\lib\site-packages\requests\api.py:96: in head return request('head', url, **kwargs) C:\Python34\lib\site-packages\requests\api.py:56: in request return session.request(method=method, url=url, **kwargs) C:\Python34\lib\site-packages\requests\sessions.py:488: in request resp = self.send(prep, **send_kwargs) C:\Python34\lib\site-packages\requests_mock\mocker.py:69: in _fake_send return self._real_send(session, request, **kwargs) C:\Python34\lib\site-packages\requests\sessions.py:641: in send r.content C:\Python34\lib\site-packages\requests\models.py:772: in content self._content = bytes().join(self.iter_content(CONTENT_CHUNK_SIZE)) or bytes() _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ def generate(): # Special case for urllib3. if hasattr(self.raw, 'stream'): try: for chunk in self.raw.stream(chunk_size, decode_content=True): yield chunk except ProtocolError as e: raise ChunkedEncodingError(e) except DecodeError as e: raise ContentDecodingError(e) except ReadTimeoutError as e: raise ConnectionError(e) else: # Standard file-like object. while True: > chunk = self.raw.read(chunk_size) E AttributeError: 'NoneType' object has no attribute 'read' C:\Python34\lib\site-packages\requests\models.py:705: AttributeError ``` happens on Windows and Linux. Thanks in advance :)

null

https://github.com/psf/requests/pull/3718

null

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1

AntonOsika

gpt-engineer

fc805074be7b3b507bc1699e537f9b691c6f91b9

https://github.com/AntonOsika/gpt-engineer/issues/674

bug documentation

ModuleNotFoundError: No module named 'tkinter'

**Bug description** When running `gpt-engineer --improve` (using the recent version from PyPI), I get the following output: ``` $ gpt-engineer --improve Traceback (most recent call last): File "/home/.../.local/bin/gpt-engineer", line 5, in <module> from gpt_engineer.main import app File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/main.py", line 12, in <module> from gpt_engineer.collect import collect_learnings File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/collect.py", line 5, in <module> from gpt_engineer import steps File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/steps.py", line 19, in <module> from gpt_engineer.file_selector import FILE_LIST_NAME, ask_for_files File "/home/.../.local/pipx/venvs/gpt-engineer/lib/python3.10/site-packages/gpt_engineer/file_selector.py", line 4, in <module> import tkinter as tk ModuleNotFoundError: No module named 'tkinter' ``` **Expected behavior** No error. In https://github.com/AntonOsika/gpt-engineer/pull/465, no changes where made to the required packages, so tkinter might be added there. (Or made optional.) EDIT: The error happens always, regardless of the command line parameter.

null

https://github.com/AntonOsika/gpt-engineer/pull/675

null

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1

pallets

flask

85dce2c836fe03aefc07b7f4e0aec575e170f1cd

https://github.com/pallets/flask/issues/593

blueprints

Nestable blueprints

I'd like to be able to register "sub-blueprints" using `Blueprint.register_blueprint(*args, **kwargs)`. This would register the nested blueprints with an app when the "parent" is registered with it. All parameters are preserved, other than `url_prefix`, which is handled similarly to in `add_url_rule`. A naíve implementation could look like this: ``` python class Blueprint(object): ... def register_blueprint(self, blueprint, **options): def deferred(state): url_prefix = options.get('url_prefix') if url_prefix is None: url_prefix = blueprint.url_prefix if 'url_prefix' in options: del options['url_prefix'] state.app.register_blueprint(blueprint, url_prefix, **options) self.record(deferred) ```

null

https://github.com/pallets/flask/pull/3923

null

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[]

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null

AUTOMATIC1111

stable-diffusion-webui

f92d61497a426a19818625c3ccdaae9beeb82b31

https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/14263

bug

[Bug]: KeyError: "do_not_save" when trying to save a prompt

### Is there an existing issue for this? - [X] I have searched the existing issues and checked the recent builds/commits ### What happened? When I try to save a prompt, it errors in the console saying ``` File "/home/ciel/stable-diffusion/stable-diffusion-webui/modules/styles.py", line 212, in save_styles style_paths.remove("do_not_save") KeyError: 'do_not_save' ``` and the file is not modified I manually commented it out and it doesn't seem to break anything, except that it is saved to styles.csv.csv instead of styles.csv ### Steps to reproduce the problem Try to save a prompt ### What should have happened? Save into style.csv with no error ### Sysinfo { "Platform": "Linux-6.6.4-zen1-1-zen-x86_64-with-glibc2.38", "Python": "3.11.4", "Version": "v1.7.0-RC-5-gf92d6149", "Commit": "f92d61497a426a19818625c3ccdaae9beeb82b31", "Script path": "/home/ciel/stable-diffusion/stable-diffusion-webui", "Data path": "/home/ciel/stable-diffusion/stable-diffusion-webui", "Extensions dir": "/home/ciel/stable-diffusion/stable-diffusion-webui/extensions", "Checksum": "e15aad6adb98a2a0ad13cad2b45b61b03565ef4f258783021da82b4ef7f37fa9", "Commandline": [ "launch.py" ], "Torch env info": { "torch_version": "2.2.0", "is_debug_build": "False", "cuda_compiled_version": "N/A", "gcc_version": "(GCC) 13.2.1 20230801", "clang_version": "16.0.6", "cmake_version": "version 3.26.4", "os": "Arch Linux (x86_64)", "libc_version": "glibc-2.38", "python_version": "3.11.4 (main, Jul 5 2023, 13:45:01) [GCC 11.2.0] (64-bit runtime)", "python_platform": "Linux-6.6.4-zen1-1-zen-x86_64-with-glibc2.38", "is_cuda_available": "True", 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0.00016260147094726562, "load scripts/lvminthin.py": 0.0001952648162841797, "load scripts/movie2movie.py": 0.00022029876708984375, "load scripts/processor.py": 0.00023818016052246094, "load scripts/utils.py": 0.00011324882507324219, "load scripts/xyz_grid_support.py": 0.0003902912139892578, "load scripts/ultimate-upscale.py": 0.00045228004455566406, "load scripts/refiner.py": 0.00011444091796875, "load scripts/seed.py": 0.00012302398681640625, "load scripts": 0.41962695121765137, "load upscalers": 0.001577138900756836, "refresh VAE": 0.0006160736083984375, "refresh textual inversion templates": 2.86102294921875e-05, "scripts list_optimizers": 0.00027680397033691406, "scripts list_unets": 4.76837158203125e-06, "reload hypernetworks": 0.0027685165405273438, "initialize extra networks": 0.004837512969970703, "scripts before_ui_callback": 0.00041604042053222656, "create ui": 0.4426920413970947, "gradio launch": 0.23865938186645508, "add APIs": 0.003912210464477539, "app_started_callback/lora_script.py": 0.0001537799835205078, "app_started_callback/clip_interrogator_ext.py": 0.0003566741943359375, "app_started_callback/api.py": 0.0010819435119628906, "app_started_callback": 0.001596689224243164 } }, "Packages": [ "absl-py==2.0.0", "accelerate==0.21.0", "addict==2.4.0", "aenum==3.1.15", "aiofiles==23.2.1", "aiohttp==3.9.1", "aiosignal==1.3.1", "altair==5.2.0", "antlr4-python3-runtime==4.9.3", "anyio==3.7.1", "attrs==23.1.0", "basicsr==1.4.2", "beautifulsoup4==4.12.2", "blendmodes==2022", "boltons==23.1.1", "cachetools==5.3.2", "certifi==2022.12.7", "cffi==1.16.0", "charset-normalizer==2.1.1", "clean-fid==0.1.35", "click==8.1.7", "clip-interrogator==0.6.0", "clip==1.0", "contourpy==1.2.0", "cssselect2==0.7.0", "cycler==0.12.1", "deprecation==2.1.0", "einops==0.4.1", "facexlib==0.3.0", "fastapi==0.94.0", "ffmpy==0.3.1", "filelock==3.9.0", "filterpy==1.4.5", "flatbuffers==23.5.26", "fonttools==4.46.0", "frozenlist==1.4.0", "fsspec==2023.12.1", "ftfy==6.1.3", "future==0.18.3", "fvcore==0.1.5.post20221221", "gdown==4.7.1", "gfpgan==1.3.8", "gitdb==4.0.11", "gitpython==3.1.32", "google-auth-oauthlib==1.1.0", "google-auth==2.25.1", "gradio-client==0.5.0", "gradio==3.41.2", "grpcio==1.60.0", "h11==0.12.0", "httpcore==0.15.0", "httpx==0.24.1", "huggingface-hub==0.19.4", "idna==3.4", "imageio==2.33.0", "importlib-metadata==7.0.0", "importlib-resources==6.1.1", "inflection==0.5.1", "iopath==0.1.9", "jinja2==3.1.2", "jsonmerge==1.8.0", "jsonschema-specifications==2023.11.2", "jsonschema==4.20.0", "kiwisolver==1.4.5", "kornia==0.6.7", "lark==1.1.2", "lazy-loader==0.3", "lightning-utilities==0.10.0", "llvmlite==0.41.1", "lmdb==1.4.1", "lpips==0.1.4", "lxml==4.9.3", "markdown==3.5.1", "markupsafe==2.1.3", "matplotlib==3.8.2", "mediapipe==0.10.8", "mpmath==1.2.1", "multidict==6.0.4", "networkx==3.0rc1", "numba==0.58.1", "numpy==1.23.5", "oauthlib==3.2.2", "omegaconf==2.2.3", "open-clip-torch==2.20.0", "opencv-contrib-python==4.8.1.78", "opencv-python==4.8.1.78", "orjson==3.9.10", "packaging==23.2", "pandas==2.1.4", "piexif==1.1.3", "pillow==9.5.0", "pip==23.1.2", "platformdirs==4.1.0", "portalocker==2.8.2", "protobuf==3.20.0", "psutil==5.9.5", "pyasn1-modules==0.3.0", "pyasn1==0.5.1", "pycparser==2.21", "pydantic==1.10.13", "pydub==0.25.1", "pyparsing==3.1.1", "pysocks==1.7.1", "python-dateutil==2.8.2", "python-multipart==0.0.6", "pytorch-lightning==1.9.4", "pytorch-triton-rocm==2.1.0+dafe145982", "pytz==2023.3.post1", "pywavelets==1.5.0", "pyyaml==6.0.1", "realesrgan==0.3.0", "referencing==0.32.0", "regex==2023.10.3", "reportlab==4.0.7", "requests-oauthlib==1.3.1", "requests==2.28.1", "resize-right==0.0.2", "rpds-py==0.13.2", "rsa==4.9", "safetensors==0.3.1", "scikit-image==0.21.0", "scipy==1.11.4", "semantic-version==2.10.0", "sentencepiece==0.1.99", "setuptools==65.5.0", "six==1.16.0", "smmap==5.0.1", "sniffio==1.3.0", "sounddevice==0.4.6", "soupsieve==2.5", "starlette==0.26.1", "svglib==1.5.1", "sympy==1.11.1", "tabulate==0.9.0", "tb-nightly==2.16.0a20231208", "tensorboard-data-server==0.7.2", "termcolor==2.4.0", "tf-keras-nightly==2.16.0.dev2023120810", "tifffile==2023.9.26", "timm==0.9.2", "tinycss2==1.2.1", "tokenizers==0.13.3", "tomesd==0.1.3", "tomli==2.0.1", "toolz==0.12.0", "torch==2.2.0.dev20231208+rocm5.6", "torchdiffeq==0.2.3", "torchmetrics==1.2.1", "torchsde==0.2.6", "torchvision==0.17.0.dev20231208+rocm5.6", "tqdm==4.66.1", "trampoline==0.1.2", "transformers==4.30.2", "typing-extensions==4.8.0", "tzdata==2023.3", "urllib3==1.26.13", "uvicorn==0.24.0.post1", "wcwidth==0.2.12", "webencodings==0.5.1", "websockets==11.0.3", "werkzeug==3.0.1", "yacs==0.1.8", "yapf==0.40.2", "yarl==1.9.4", "zipp==3.17.0" ] } ### What browsers do you use to access the UI ? Mozilla Firefox ### Console logs ```Shell ❯ ./webui.sh (base) ################################################################ Install script for stable-diffusion + Web UI Tested on Debian 11 (Bullseye) ################################################################ ################################################################ Running on ciel user ################################################################ ################################################################ Create and activate python venv ################################################################ ################################################################ Launching launch.py... ################################################################ Using TCMalloc: libtcmalloc_minimal.so.4 Python 3.11.4 (main, Jul 5 2023, 13:45:01) [GCC 11.2.0] Version: v1.7.0-RC-5-gf92d6149 Commit hash: f92d61497a426a19818625c3ccdaae9beeb82b31 Launching Web UI with arguments: no module 'xformers'. Processing without... no module 'xformers'. Processing without... No module 'xformers'. Proceeding without it. 2023-12-09 17:08:09,876 - ControlNet - INFO - ControlNet v1.1.422 ControlNet preprocessor location: /home/ciel/stable-diffusion/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/downloads 2023-12-09 17:08:09,921 - ControlNet - INFO - ControlNet v1.1.422 Loading weights [5493a0ec49] from /home/ciel/stable-diffusion/stable-diffusion-webui/models/Stable-diffusion/AOM3A1B_orangemixs.safetensors Running on local URL: http://127.0.0.1:7860 To create a public link, set `share=True` in `launch()`. Creating model from config: /home/ciel/stable-diffusion/stable-diffusion-webui/configs/v1-inference.yaml Startup time: 8.9s (prepare environment: 4.0s, import torch: 2.0s, import gradio: 0.5s, setup paths: 0.8s, other imports: 0.5s, load scripts: 0.4s, create ui: 0.4s, gradio launch: 0.2s). Loading VAE weights specified in settings: /home/ciel/stable-diffusion/stable-diffusion-webui/models/VAE/orangemix.vae.pt Applying attention optimization: Doggettx... done. Model loaded in 2.6s (load weights from disk: 0.6s, create model: 0.2s, apply weights to model: 1.4s, load VAE: 0.2s, calculate empty prompt: 0.1s). Traceback (most recent call last): File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/routes.py", line 488, in run_predict output = await app.get_blocks().process_api( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/blocks.py", line 1431, in process_api result = await self.call_function( ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/blocks.py", line 1103, in call_function prediction = await anyio.to_thread.run_sync( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/anyio/to_thread.py", line 33, in run_sync return await get_asynclib().run_sync_in_worker_thread( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 877, in run_sync_in_worker_thread return await future ^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 807, in run result = context.run(func, *args) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/venv/lib/python3.11/site-packages/gradio/utils.py", line 707, in wrapper response = f(*args, **kwargs) ^^^^^^^^^^^^^^^^^^ File "/home/ciel/stable-diffusion/stable-diffusion-webui/modules/ui_prompt_styles.py", line 27, in save_style shared.prompt_styles.save_styles(shared.styles_filename) File "/home/ciel/stable-diffusion/stable-diffusion-webui/modules/styles.py", line 212, in save_styles style_paths.remove("do_not_save") KeyError: 'do_not_save' ``` ### Additional information I'm running dev branch due to the Navi3 bug, checking out master after launch seems to result in the same issue, but it could have just been jit-ed, didn't test very in-depth

null

https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14276

null

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1

home-assistant

core

c3e9c1a7e8fdc949b8e638d79ab476507ff92f18

https://github.com/home-assistant/core/issues/60067

integration: environment_canada by-code-owner

Environment Canada (EC) radar integration slowing Environment Canada servers

### The problem The `config_flow` change to the EC integration did not change the way the underlying radar retrieval works, but did enable radar for everyone. As a result the EC servers are getting far too many requests. We (the codeowners) have been working with EC to diagnose this issue and understand their concerns. We are doing two things (PR is in progress). Caching requests to the EC servers. Work so far shows that through caching we can reduce the number of requests by over 90%. This fix is in the integration dependency library. Second, we are creating the radar (camera) entity with `_attr_entity_registry_enabled_default = False` so that new radar entities are disabled by default. Many people use the integration for forecast only. Last, EC is putting a policy in place such that User Agent needs to be filled in to represent the calling library. ### What version of Home Assistant Core has the issue? 2021.12.0.dev0 ### What was the last working version of Home Assistant Core? _No response_ ### What type of installation are you running? Home Assistant Core ### Integration causing the issue Environment Canada ### Link to integration documentation on our website https://www.home-assistant.io/integrations/environment_canada/ ### Example YAML snippet _No response_ ### Anything in the logs that might be useful for us? _No response_ ### Additional information Quote from one of the email exchanges with EC: > What we observed is 1350 unique IP addresses using this code which made 23.5 million requests over 5 days. In order to respond to EC as quickly as possible we are asking for consideration to release the PR, when available, in the next dot release.

null

https://github.com/home-assistant/core/pull/60087

null

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1

abi

screenshot-to-code

939539611f0cad12056f7be78ef6b2128b90b779

https://github.com/abi/screenshot-to-code/issues/336

bug p2

Handle Nones in chunk.choices[0].delta

![WechatIMG434](https://github.com/abi/screenshot-to-code/assets/158557918/d2ddcd3e-f944-40cb-a74e-b54bec8938f4) There is a successful request for the openai interface, but it seems that no code is generated. backend-1 | ERROR: Exception in ASGI application backend-1 | Traceback (most recent call last): backend-1 | File "/usr/local/lib/python3.12/site-packages/uvicorn/protocols/websockets/websockets_impl.py", line 250, in run_asgi backend-1 | result = await self.app(self.scope, self.asgi_receive, self.asgi_send) backend-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 | File "/usr/local/lib/python3.12/site-packages/uvicorn/middleware/proxy_headers.py", line 84, in __call__ backend-1 | return await self.app(scope, receive, send) backend-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 | File "/usr/local/lib/python3.12/site-packages/fastapi/applications.py", line 276, in __call__ backend-1 | await super().__call__(scope, receive, send) backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/applications.py", line 122, in __call__ backend-1 | await self.middleware_stack(scope, receive, send) backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/middleware/errors.py", line 149, in __call__ backend-1 | await self.app(scope, receive, send) backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/middleware/cors.py", line 75, in __call__ backend-1 | await self.app(scope, receive, send) backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/middleware/exceptions.py", line 79, in __call__ backend-1 | raise exc backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/middleware/exceptions.py", line 68, in __call__ backend-1 | await self.app(scope, receive, sender) backend-1 | File "/usr/local/lib/python3.12/site-packages/fastapi/middleware/asyncexitstack.py", line 21, in __call__ backend-1 | raise e backend-1 | File "/usr/local/lib/python3.12/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__ backend-1 | await self.app(scope, receive, send) backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/routing.py", line 718, in __call__ backend-1 | await route.handle(scope, receive, send) backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/routing.py", line 341, in handle backend-1 | await self.app(scope, receive, send) backend-1 | File "/usr/local/lib/python3.12/site-packages/starlette/routing.py", line 82, in app backend-1 | await func(session) backend-1 | File "/usr/local/lib/python3.12/site-packages/fastapi/routing.py", line 289, in app backend-1 | await dependant.call(**values) backend-1 | File "/app/routes/generate_code.py", line 251, in stream_code backend-1 | completion = await stream_openai_response( backend-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 | File "/app/llm.py", line 62, in stream_openai_response backend-1 | content = chunk.choices[0].delta.content or "" backend-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ backend-1 | AttributeError: 'NoneType' object has no attribute 'content' backend-1 | INFO: connection closed

null

https://github.com/abi/screenshot-to-code/pull/341

null

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1

Significant-Gravitas

AutoGPT

bf895eb656dee9084273cd36395828bd06aa231d

https://github.com/Significant-Gravitas/AutoGPT/issues/6

enhancement good first issue API costs

Make Auto-GPT aware of it's running cost

Auto-GPT is expensive to run due to GPT-4's API cost. We could experiment with making it aware of this fact, by tracking tokens as they are used and converting to a dollar cost. This could also be displayed to the user to help them be more aware of exactly how much they are spending.

null

https://github.com/Significant-Gravitas/AutoGPT/pull/762

null

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{ "code": [ "autogpt/chat.py", "autogpt/prompts/prompt.py", "autogpt/config/ai_config.py", "autogpt/memory/base.py", "autogpt/setup.py", "autogpt/llm_utils.py" ], "doc": [], "test": [ "tests/unit/test_commands.py", "tests/unit/test_setup.py" ], "config": [], "asset": [] }

1

yt-dlp

3e01ce744a981d8f19ae77ec695005e7000f4703

https://github.com/yt-dlp/yt-dlp/issues/5855

bug

Generic extractor can crash if Brotli is not available

### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE - [X] I understand that I will be **blocked** if I remove or skip any mandatory\* field ### Checklist - [X] I'm reporting a bug unrelated to a specific site - [X] I've verified that I'm running yt-dlp version **2022.11.11** ([update instructions](https://github.com/yt-dlp/yt-dlp#update)) or later (specify commit) - [X] I've checked that all provided URLs are playable in a browser with the same IP and same login details - [X] I've checked that all URLs and arguments with special characters are [properly quoted or escaped](https://github.com/yt-dlp/yt-dlp/wiki/FAQ#video-url-contains-an-ampersand--and-im-getting-some-strange-output-1-2839-or-v-is-not-recognized-as-an-internal-or-external-command) - [X] I've searched the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar issues **including closed ones**. DO NOT post duplicates - [X] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue) ### Provide a description that is worded well enough to be understood Testing #5851 in a configuration where no Brotli decoder was available showed the crash in the log. The problem is this extractor code: https://github.com/yt-dlp/yt-dlp/blob/1fc089143c79b02b8373ae1d785d5e3a68635d4d/yt_dlp/extractor/generic.py#L2306-L2318 Normally there is a check for a supported Brotli encoder (using `SUPPORTED_ENCODINGS`). Specifying `*` in the `Accept-encoding` header bypasses that check. However, I don't think that `*` does what is wanted according to the comments in the above code. The code wants to get the resource with no decoding (because decoding in yt-dl[p] starts by reading the entire response), but `*` still allows the server to send a compressed response. What is wanted is the `identity` encoding which is the default if no other encoding is specified. Or, to re-cast the decoding process so that the whole response stream is not read before decoding, but that means creating stream decoding methods for Brotli and zlib. Also, there could be a check for a supported encoding in `YoutubeDLHandler.http_response()`, perhaps synthesizing 416 or 406 id the server has sent an encoding that isn't supported, instead of the crash seen here. ### Provide verbose output that clearly demonstrates the problem - [X] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`) - [X] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below ### Complete Verbose Output ```shell [debug] Command-line config: ['-vU', '-F', 'https://www.extra.cz/cauky-lidi-70-dil-babis-predstavil-pohadky-prymulanek-nebo-andrejovy-nove-saty-ac867'] [debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8 [debug] yt-dlp version 2022.11.11 [8b644025b] (source) [debug] Lazy loading extractors is disabled [debug] Plugins: ['SamplePluginIE', 'SamplePluginPP'] [debug] Git HEAD: c73355510 [debug] Python 3.9.15 (CPython i686 32bit) - Linux-4.4.0-210-generic-i686-with-glibc2.23 (OpenSSL 1.1.1s 1 Nov 2022, glibc 2.23) [debug] exe versions: ffmpeg 4.3, ffprobe 4.3 [debug] Optional libraries: Cryptodome-3.11.0, certifi-2019.11.28, secretstorage-3.2.0, sqlite3-2.6.0 [debug] Proxy map: {} [debug] Loaded 1735 extractors [debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest Latest version: 2022.11.11, Current version: 2022.11.11 yt-dlp is up to date (2022.11.11) [generic] Extracting URL: https://www.extra.cz/cauky-lidi-70-dil-babis-predstavil-pohadky-prymulanek-nebo-andrejovy-nove-saty-ac867 [generic] cauky-lidi-70-dil-babis-predstavil-pohadky-prymulanek-nebo-andrejovy-nove-saty-ac867: Downloading webpage ERROR: 'NoneType' object has no attribute 'decompress' Traceback (most recent call last): File "/home/df/Documents/src/yt-dlp/yt_dlp/YoutubeDL.py", line 1495, in wrapper return func(self, *args, **kwargs) File "/home/df/Documents/src/yt-dlp/yt_dlp/YoutubeDL.py", line 1571, in __extract_info ie_result = ie.extract(url) File "/home/df/Documents/src/yt-dlp/yt_dlp/extractor/common.py", line 680, in extract ie_result = self._real_extract(url) File "/home/df/Documents/src/yt-dlp/yt_dlp/extractor/generic.py", line 2314, in _real_extract full_response = self._request_webpage(url, video_id, headers={ File "/home/df/Documents/src/yt-dlp/yt_dlp/extractor/common.py", line 807, in _request_webpage return self._downloader.urlopen(self._create_request(url_or_request, data, headers, query)) File "/home/df/Documents/src/yt-dlp/yt_dlp/YoutubeDL.py", line 3719, in urlopen return self._opener.open(req, timeout=self._socket_timeout) File "/usr/lib/python3.9/urllib/request.py", line 523, in open response = meth(req, response) File "/home/df/Documents/src/yt-dlp/yt_dlp/utils.py", line 1452, in http_response io.BytesIO(self.brotli(resp.read())), old_resp.headers, old_resp.url, old_resp.code) File "/home/df/Documents/src/yt-dlp/yt_dlp/utils.py", line 1389, in brotli return brotli.decompress(data) AttributeError: 'NoneType' object has no attribute 'decompress' ```

null

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[]

{ "iss_type": "1", "iss_reason": "2", "loc_way": "commit", "loc_scope": "", "info_type": "" }

{ "code": [ "yt_dlp/extractor/generic.py" ], "doc": [], "test": [], "config": [], "asset": [] }

null

CorentinJ

Real-Time-Voice-Cloning

ded7b37234e229d9bde0a9a506f7c65605803731

https://github.com/CorentinJ/Real-Time-Voice-Cloning/issues/543

Lack of pre-compiled results in lost interest

so I know the first thing people are going to say is, this isn't an issue. However, it is. by not having a precompiled version to download over half the people that find their way to this GitHub are going to lose interest. Honestly, I'm one of them. I attempted to compile it but then I saw that I had to track down each module for this, yeah quickly drove me away from it. all I wanted to do was mess around and see what it can do. even if the results arent mind-blowing the concept interests me. but due to not having a ready to use executable I like many others I'm sure of, have decided it isn't even worth messing with.

null

https://github.com/CorentinJ/Real-Time-Voice-Cloning/pull/546

null

{'base_commit': 'ded7b37234e229d9bde0a9a506f7c65605803731', 'files': [{'path': 'toolbox/ui.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [0], 'mod': [11]}}}]}

[]

{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "toolbox/ui.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

scikit-learn

96b5814de70ad2435b6db5f49b607b136921f701

https://github.com/scikit-learn/scikit-learn/issues/26948

Documentation

The copy button on install copies an extensive comman including env activation

### Describe the issue linked to the documentation https://scikit-learn.org/stable/install.html Above link will lead you to the sklearn downlanding for link . when you link copy link button it will copy `python3 -m venv sklearn-venvpython -m venv sklearn-venvpython -m venv sklearn-venvsource sklearn-venv/bin/activatesource sklearn-venv/bin/activatesklearn-venv\Scripts\activatepip install -U scikit-learnpip install -U scikit-learnpip install -U scikit-learnpip3 install -U scikit-learnconda create -n sklearn-env -c conda-forge scikit-learnconda activate sklearn-env` instead of `pip3 install -U scikit-learn` if this is the issue so please issue i want to create a pull request for it and tell in which file this issue reside Thanks ### Suggest a potential alternative/fix By resoving above issue

null

https://github.com/scikit-learn/scikit-learn/pull/27052

null

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[]

{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "doc/themes/scikit-learn-modern/static/css/theme.css" ], "doc": [ "doc/install.rst" ], "test": [], "config": [], "asset": [] }

1

keras-team

keras

49b9682b3570211c7d8f619f8538c08fd5d8bdad

https://github.com/keras-team/keras/issues/10036

[API DESIGN REVIEW] sample weight in ImageDataGenerator.flow

https://docs.google.com/document/d/14anankKROhliJCpInQH-pITatdjO9UzSN6Iz0MwcDHw/edit?usp=sharing Makes it easy to use data augmentation when sample weights are available.

null

https://github.com/keras-team/keras/pull/10092

null

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[]

{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "tests/keras/preprocessing/image_test.py", "keras/preprocessing/image.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

scrapy

efb53aafdcaae058962c6189ddecb3dc62b02c31

https://github.com/scrapy/scrapy/issues/6514

enhancement

Migrate from setup.py to pyproject.toml

We should migrate to the modern declarative setuptools metadata approach as discussed in https://setuptools.pypa.io/en/latest/userguide/quickstart.html and https://setuptools.pypa.io/en/latest/userguide/pyproject_config.html, but only after the 2.12 release.

null

https://github.com/scrapy/scrapy/pull/6547

null

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[]

{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "tests/test_spiderloader/__init__.py", ".isort.cfg", ".coveragerc", "setup.cfg", "setup.py", ".bumpversion.cfg" ], "doc": [], "test": [ "tests/test_crawler.py" ], "config": [ "pytest.ini", ".pre-commit-config.yaml", "tox.ini", "pylintrc", ".bandit.yml", "MANIFEST.in" ], "asset": [] }

1

fastapi

c6e950dc9cacefd692dbd8987a3acd12a44b506f

https://github.com/fastapi/fastapi/issues/5859

question question-migrate

FastAPI==0.89.0 Cannot use `None` as a return type when `status_code` is set to 204 with `from __future__ import annotations`

### First Check - [X] I added a very descriptive title to this issue. - [X] I used the GitHub search to find a similar issue and didn't find it. - [X] I searched the FastAPI documentation, with the integrated search. - [X] I already searched in Google "How to X in FastAPI" and didn't find any information. - [X] I already read and followed all the tutorial in the docs and didn't find an answer. - [X] I already checked if it is not related to FastAPI but to [Pydantic](https://github.com/samuelcolvin/pydantic). - [X] I already checked if it is not related to FastAPI but to [Swagger UI](https://github.com/swagger-api/swagger-ui). - [X] I already checked if it is not related to FastAPI but to [ReDoc](https://github.com/Redocly/redoc). ### Commit to Help - [X] I commit to help with one of those options 👆 ### Example Code ```python from __future__ import annotations from fastapi import FastAPI app = FastAPI() @app.get("/", status_code=204) def read_root() -> None: return {"Hello": "World"} ``` ### Description If we add: `from __future__ import annotations` It changes the annotations structure and the response model is `NoneType` instead of `None`, which causes validation of the `statuc_code` vs `response_model` and raises an exception. ```python ... File ".../site-packages/fastapi/routing.py", line 635, in decorator self.add_api_route( File ".../site-packages/fastapi/routing.py", line 574, in add_api_route route = route_class( File ".../site-packages/fastapi/routing.py", line 398, in __init__ assert is_body_allowed_for_status_code( AssertionError: Status code 204 must not have a response body ``` I am working on a fix for it right now. ### Operating System macOS ### Operating System Details _No response_ ### FastAPI Version 0.89.0 ### Python Version 3.10 ### Additional Context _No response_

null

https://github.com/fastapi/fastapi/pull/2246

null

{'base_commit': 'c6e950dc9cacefd692dbd8987a3acd12a44b506f', 'files': [{'path': '.github/workflows/preview-docs.yml', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [38]}}}]}

[]

{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [], "doc": [ ".github/workflows/preview-docs.yml" ], "test": [], "config": [], "asset": [] }

1

3b1b

manim

3938f81c1b4a5ee81d5bfc6563c17a225f7e5068

https://github.com/3b1b/manim/issues/1330

Error after installing manim

I installed all manim & dependecies, but when I ran `python -m manim example_scenes.py OpeningManimExample`, I got the following error: `Traceback (most recent call last): File "c:\users\jm\anaconda3\lib\runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "c:\users\jm\anaconda3\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\Users\jm\Documents\work\manim_new\manim\manim.py", line 5, in <module> manimlib.main() File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\__init__.py", line 9, in main scenes = manimlib.extract_scene.main(config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\extract_scene.py", line 113, in main scenes = get_scenes_to_render(all_scene_classes, scene_config, config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\extract_scene.py", line 74, in get_scenes_to_render scene = scene_class(**scene_config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\scene\scene.py", line 44, in __init__ self.window = Window(self, **self.window_config) File "C:\Users\jm\Documents\work\manim_new\manim\manimlib\window.py", line 19, in __init__ super().__init__(**kwargs) File "C:\Users\jm\Envs\manim.new\lib\site-packages\moderngl_window\context\pyglet\window.py", line 51, in __init__ self._window = PygletWrapper( File "C:\Users\jm\Envs\manim.new\lib\site-packages\pyglet\window\win32\__init__.py", line 134, in __init__ super(Win32Window, self).__init__(*args, **kwargs) File "C:\Users\jm\Envs\manim.new\lib\site-packages\pyglet\window\__init__.py", line 603, in __init__ config = screen.get_best_config(config) File "C:\Users\jm\Envs\manim.new\lib\site-packages\pyglet\canvas\base.py", line 194, in get_best_config raise window.NoSuchConfigException() pyglet.window.NoSuchConfigException`. Any advice? And thank you

null

https://github.com/3b1b/manim/pull/1343

null

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[]

{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }

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null

keras-team

keras

84b283e6200bcb051ed976782fbb2b123bf9b8fc

https://github.com/keras-team/keras/issues/19793

type:bug/performance

model.keras format much slower to load

Anyone experiencing unreasonably slow load times when loading a keras-format saved model? I have noticed this repeated when working in ipython, where simply instantiating a model via `Model.from_config` then calling `model.load_weights` is much (several factors) faster than loading a `model.keras` file. My understanding is the keras format is simply a zip file with the config.json file and weights h5 (iirc) but weirdly enough, there's something not right going on while loading.

null

https://github.com/keras-team/keras/pull/19852

null

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[]

{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "keras/src/saving/saving_lib_test.py", "keras/src/saving/saving_lib.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

ansible

4cdb266dac852859f695b0555cbe49e58343e69a

https://github.com/ansible/ansible/issues/3539

bug

Bug in Conditional Include

Hi, I know that when using conditionals on an include, 'All the tasks get evaluated, but the conditional is applied to each and every task'. However this breaks when some of that tasks register variables and other tasks in the group use those variable. Example: main.yml: ``` - include: extra.yml when: do_extra is defined ``` extra.yml: ``` - name: check if we can do task A shell: check_if_task_A_possible register: A_possible ignore_errors: yes - name: task A shell: run_task_A when: A_possible.rc == 0 ``` Now if you run main.yml and 'do_extra' is not defined, the run will fail on 'task A' because when the 'when' condition is evaluated, the variable A_possible will not exist. It is not sufficient to just add the top-level include conditional above the other because right now it looks like the two conditions are compounded and tested together which will still fail because A_possible is not defined. I think you would have to run the file level conditional before the task level ones to keep this from happening.

null

https://github.com/ansible/ansible/pull/20158

null

{'base_commit': '4cdb266dac852859f695b0555cbe49e58343e69a', 'files': [{'path': 'lib/ansible/modules/windows/win_robocopy.ps1', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [25, 26, 27, 28, 73, 76, 93, 94, 95, 114, 115, 167, 168]}}}, {'path': 'lib/ansible/modules/windows/win_robocopy.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [132]}}}]}

[]

{ "iss_type": "1", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "lib/ansible/modules/windows/win_robocopy.ps1", "lib/ansible/modules/windows/win_robocopy.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

psf

requests

f5dacf84468ab7e0631cc61a3f1431a32e3e143c

https://github.com/psf/requests/issues/2654

Feature Request Contributor Friendly

utils.get_netrc_auth silently fails when netrc exists but fails to parse

My .netrc contains a line for the github auth, [like this](https://gist.github.com/wikimatze/9790374). It turns out that `netrc.netrc()` doesn't like that: ``` >>> from netrc import netrc >>> netrc() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/netrc.py", line 35, in __init__ self._parse(file, fp, default_netrc) File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/netrc.py", line 117, in _parse file, lexer.lineno) netrc.NetrcParseError: bad follower token 'protocol' (/Users/david/.netrc, line 9) ``` `get_netrc_auth` catches the `NetrcParseError` [but just ignores it](https://github.com/kennethreitz/requests/blob/master/requests/utils.py#L106). At least having it emit a warning would have saved some hair-pulling.

null

https://github.com/psf/requests/pull/2656

null

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[]

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{ "code": [ "requests/utils.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

oobabooga

text-generation-webui

0877741b0350d200be7f1e6cca2780a25ee29cd0

https://github.com/oobabooga/text-generation-webui/issues/5851

bug

Inference failing using ExLlamav2 version 0.0.18

### Describe the bug Since ExLlamav2 was upgraded to version 0.0.18 in the requirements.txt, inference using it is no longer working and fails with the error in the logs below. Reverting to version 0.0.17 resolves the issue. ### Is there an existing issue for this? - [X] I have searched the existing issues ### Reproduction 1. Install latest main branch (current commit is `26d822f64f2a029306b250b69dc58468662a4fc6`) 2. Download `GPTQ` model 3. Use `ExLlamav2_HF` model loader 4. Go to `Chat` tab and ask the AI a question. 5. Observe error, even though the model loaded successfully. ### Screenshot _No response_ ### Logs ```shell 21:35:11-061459 INFO Loading "TheBloke_dolphin-2.6-mistral-7B-GPTQ" 21:35:13-842112 INFO LOADER: "ExLlamav2" 21:35:13-843422 INFO TRUNCATION LENGTH: 32768 21:35:13-844234 INFO INSTRUCTION TEMPLATE: "Alpaca" 21:35:13-845014 INFO Loaded the model in 2.78 seconds. Traceback (most recent call last): File "/workspace/text-generation-webui/modules/text_generation.py", line 429, in generate_reply_custom for reply in shared.model.generate_with_streaming(question, state): File "/workspace/text-generation-webui/modules/exllamav2.py", line 140, in generate_with_streaming self.generator.begin_stream(ids, settings, loras=self.loras) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 198, in begin_stream self.begin_stream_ex(input_ids, File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 296, in begin_stream_ex self._gen_begin_reuse(input_ids, gen_settings) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 624, in _gen_begin_reuse self._gen_begin(in_tokens, gen_settings) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/generator/streaming.py", line 586, in _gen_begin self.model.forward(self.sequence_ids[:, :-1], File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/model.py", line 694, in forward r, ls = self._forward(input_ids = input_ids[:, chunk_begin : chunk_end], File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/model.py", line 776, in _forward x = module.forward(x, cache = cache, attn_params = attn_params, past_len = past_len, loras = loras, **kwargs) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/exllamav2/attn.py", line 596, in forward attn_output = flash_attn_func(q_states, k_states, v_states, causal = True) File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 825, in flash_attn_func return FlashAttnFunc.apply( File "/usr/local/lib/python3.10/dist-packages/torch/autograd/function.py", line 553, in apply return super().apply(*args, **kwargs) # type: ignore[misc] File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 507, in forward out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = _flash_attn_forward( File "/workspace/venvs/text-generation-webui/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 51, in _flash_attn_forward out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = flash_attn_cuda.fwd( RuntimeError: CUDA error: an illegal memory access was encountered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. ``` ### System Info * Ubuntu 22.04 LTS * Nvidia A5000 GPU on Runpod * CUDA 12.1

null

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[]

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null

zylon-ai

private-gpt

89477ea9d3a83181b0222b732a81c71db9edf142

https://github.com/zylon-ai/private-gpt/issues/2013

bug

[BUG] Another permissions error when installing with docker-compose

### Pre-check - [X] I have searched the existing issues and none cover this bug. ### Description This looks similar, but not the same as #1876 As for following the instructions, I've not seen any relevant guide to installing with Docker, hence working a bit blind. Background: I'm trying to run this on an Asustor NAS, which offers very little ability to customize the environment. Ideally, I'd just like to be able to run this by pasting a docker-compose file into Portainer, and having it work it's magic from there: --- ``` sal@halob:/volume1/home/sal/apps/private-gpt $ docker-compose up [+] Running 3/3 ✔ Network private-gpt_default Created 0.1s ✔ Container private-gpt-ollama-1 Created 0.1s ✔ Container private-gpt-private-gpt-1 Created 0.1s Attaching to ollama-1, private-gpt-1 ollama-1 | Couldn't find '/root/.ollama/id_ed25519'. Generating new private key. ollama-1 | Your new public key is: ollama-1 | ollama-1 | ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIBNQkShAIoUDyyueUTiCHM9/AZfZ+rxnUZgmh+YByBVB ollama-1 | ollama-1 | 2024/07/23 23:20:28 routes.go:1096: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://0.0.0.0:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MAX_VRAM:0 OLLAMA_MODELS:/root/.ollama/models OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://*] OLLAMA_RUNNERS_DIR: OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]" ollama-1 | time=2024-07-23T23:20:28.317Z level=INFO source=images.go:778 msg="total blobs: 0" ollama-1 | time=2024-07-23T23:20:28.317Z level=INFO source=images.go:785 msg="total unused blobs removed: 0" ollama-1 | time=2024-07-23T23:20:28.317Z level=INFO source=routes.go:1143 msg="Listening on [::]:11434 (version 0.2.6)" ollama-1 | time=2024-07-23T23:20:28.318Z level=INFO source=payload.go:30 msg="extracting embedded files" dir=/tmp/ollama1112441504/runners private-gpt-1 | 23:20:29.406 [INFO ] private_gpt.settings.settings_loader - Starting application with profiles=['default', 'docker'] ollama-1 | time=2024-07-23T23:20:33.589Z level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cpu_avx cpu_avx2 cuda_v11 rocm_v60102 cpu]" ollama-1 | time=2024-07-23T23:20:33.589Z level=INFO source=gpu.go:205 msg="looking for compatible GPUs" ollama-1 | time=2024-07-23T23:20:33.589Z level=WARN source=gpu.go:225 msg="CPU does not have minimum vector extensions, GPU inference disabled" required=avx detected="no vector extensions" ollama-1 | time=2024-07-23T23:20:33.590Z level=INFO source=types.go:105 msg="inference compute" id=0 library=cpu compute="" driver=0.0 name="" total="31.1 GiB" available="28.1 GiB" private-gpt-1 | There was a problem when trying to write in your cache folder (/nonexistent/.cache/huggingface/hub). You should set the environment variable TRANSFORMERS_CACHE to a writable directory. private-gpt-1 | None of PyTorch, TensorFlow >= 2.0, or Flax have been found. Models won't be available and only tokenizers, configuration and file/data utilities can be used. private-gpt-1 | 23:20:40.419 [INFO ] private_gpt.components.llm.llm_component - Initializing the LLM in mode=ollama private-gpt-1 | Traceback (most recent call last): private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 798, in get private-gpt-1 | return self._context[key] private-gpt-1 | ~~~~~~~~~~~~~^^^^^ private-gpt-1 | KeyError: <class 'private_gpt.ui.ui.PrivateGptUi'> private-gpt-1 | private-gpt-1 | During handling of the above exception, another exception occurred: private-gpt-1 | private-gpt-1 | Traceback (most recent call last): private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 798, in get private-gpt-1 | return self._context[key] private-gpt-1 | ~~~~~~~~~~~~~^^^^^ private-gpt-1 | KeyError: <class 'private_gpt.server.ingest.ingest_service.IngestService'> private-gpt-1 | private-gpt-1 | During handling of the above exception, another exception occurred: private-gpt-1 | private-gpt-1 | Traceback (most recent call last): private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 798, in get private-gpt-1 | return self._context[key] private-gpt-1 | ~~~~~~~~~~~~~^^^^^ private-gpt-1 | KeyError: <class 'private_gpt.components.vector_store.vector_store_component.VectorStoreComponent'> private-gpt-1 | private-gpt-1 | During handling of the above exception, another exception occurred: private-gpt-1 | private-gpt-1 | Traceback (most recent call last): private-gpt-1 | File "<frozen runpy>", line 198, in _run_module_as_main private-gpt-1 | File "<frozen runpy>", line 88, in _run_code private-gpt-1 | File "/home/worker/app/private_gpt/__main__.py", line 5, in <module> private-gpt-1 | from private_gpt.main import app private-gpt-1 | File "/home/worker/app/private_gpt/main.py", line 6, in <module> private-gpt-1 | app = create_app(global_injector) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/private_gpt/launcher.py", line 63, in create_app private-gpt-1 | ui = root_injector.get(PrivateGptUi) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 974, in get private-gpt-1 | provider_instance = scope_instance.get(interface, binding.provider) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 800, in get private-gpt-1 | instance = self._get_instance(key, provider, self.injector) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance private-gpt-1 | return provider.get(injector) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 264, in get private-gpt-1 | return injector.create_object(self._cls) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object private-gpt-1 | self.call_with_injection(init, self_=instance, kwargs=additional_kwargs) private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1031, in call_with_injection private-gpt-1 | dependencies = self.args_to_inject( private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1079, in args_to_inject private-gpt-1 | instance: Any = self.get(interface) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 974, in get private-gpt-1 | provider_instance = scope_instance.get(interface, binding.provider) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 800, in get private-gpt-1 | instance = self._get_instance(key, provider, self.injector) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance private-gpt-1 | return provider.get(injector) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 264, in get private-gpt-1 | return injector.create_object(self._cls) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object private-gpt-1 | self.call_with_injection(init, self_=instance, kwargs=additional_kwargs) private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1031, in call_with_injection private-gpt-1 | dependencies = self.args_to_inject( private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1079, in args_to_inject private-gpt-1 | instance: Any = self.get(interface) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 974, in get private-gpt-1 | provider_instance = scope_instance.get(interface, binding.provider) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 91, in wrapper private-gpt-1 | return function(*args, **kwargs) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 800, in get private-gpt-1 | instance = self._get_instance(key, provider, self.injector) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 811, in _get_instance private-gpt-1 | return provider.get(injector) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 264, in get private-gpt-1 | return injector.create_object(self._cls) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 998, in create_object private-gpt-1 | self.call_with_injection(init, self_=instance, kwargs=additional_kwargs) private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/injector/__init__.py", line 1040, in call_with_injection private-gpt-1 | return callable(*full_args, **dependencies) private-gpt-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/private_gpt/components/vector_store/vector_store_component.py", line 114, in __init__ private-gpt-1 | client = QdrantClient( private-gpt-1 | ^^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/qdrant_client/qdrant_client.py", line 117, in __init__ private-gpt-1 | self._client = QdrantLocal( private-gpt-1 | ^^^^^^^^^^^^ private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/qdrant_client/local/qdrant_local.py", line 66, in __init__ private-gpt-1 | self._load() private-gpt-1 | File "/home/worker/app/.venv/lib/python3.11/site-packages/qdrant_client/local/qdrant_local.py", line 97, in _load private-gpt-1 | os.makedirs(self.location, exist_ok=True) private-gpt-1 | File "<frozen os>", line 215, in makedirs private-gpt-1 | File "<frozen os>", line 225, in makedirs private-gpt-1 | PermissionError: [Errno 13] Permission denied: 'local_data/private_gpt' ^CGracefully stopping... (press Ctrl+C again to force) [+] Stopping 2/2 ✔ Container private-gpt-private-gpt-1 Stopped 0.3s ✔ Container private-gpt-ollama-1 Stopped ``` ### Steps to Reproduce 1. Clone the repo 2. docker-compose build 3. docker-compose up ### Expected Behavior It should just run ### Actual Behavior Error, as reported above ### Environment Running on an Asustor router, docker 25.0.5 ### Additional Information _No response_ ### Version latest ### Setup Checklist - [X] Confirm that you have followed the installation instructions in the project’s documentation. - [X] Check that you are using the latest version of the project. - [X] Verify disk space availability for model storage and data processing. - [X] Ensure that you have the necessary permissions to run the project. ### NVIDIA GPU Setup Checklist - [ ] Check that the all CUDA dependencies are installed and are compatible with your GPU (refer to [CUDA's documentation](https://docs.nvidia.com/deploy/cuda-compatibility/#frequently-asked-questions)) - [ ] Ensure an NVIDIA GPU is installed and recognized by the system (run `nvidia-smi` to verify). - [ ] Ensure proper permissions are set for accessing GPU resources. - [ ] Docker users - Verify that the NVIDIA Container Toolkit is configured correctly (e.g. run `sudo docker run --rm --gpus all nvidia/cuda:11.0.3-base-ubuntu20.04 nvidia-smi`)

null

https://github.com/zylon-ai/private-gpt/pull/2059

null

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[]

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1

scikit-learn

e04b8e70e60df88751af5cd667cafb66dc32b397

https://github.com/scikit-learn/scikit-learn/issues/26590

Bug

KNNImputer add_indicator fails to persist where missing data had been present in training

### Describe the bug Hello, I've encountered an issue where the KNNImputer fails to record the fields where there were missing data at the time when `.fit` is called, but not recognised if `.transform` is called on a dense matrix. I would have expected it to return a 2x3 matrix rather than 2x2, with `missingindicator_A = False` for all cases. Reproduction steps below. Any help much appreciated :) ### Steps/Code to Reproduce ```python >>> import pandas as pd >>> from sklearn.impute import KNNImputer >>> knn = KNNImputer(add_indicator=True) >>> df = pd.DataFrame({'A': [0, None], 'B': [1, 2]}) >>> df A B 0 0.0 1 1 NaN 2 >>> knn.fit(df) KNNImputer(add_indicator=True) >>> pd.DataFrame(knn.transform(df), columns=knn.get_feature_names_out()) A B missingindicator_A 0 0.0 1.0 0.0 1 0.0 2.0 1.0 >>> df['A'] = 0 >>> pd.DataFrame(knn.transform(df), columns=knn.get_feature_names_out()) ``` ### Expected Results ``` A B missingindicator_A 0 0.0 1.0 0.0 1 0.0 2.0 0.0 ``` ### Actual Results ```pytb --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[30], line 1 ----> 1 pd.DataFrame(knn.transform(df), columns=knn.get_feature_names_out()) File /opt/conda/lib/python3.10/site-packages/pandas/core/frame.py:694, in DataFrame.__init__(self, data, index, columns, dtype, copy) 684 mgr = dict_to_mgr( 685 # error: Item "ndarray" of "Union[ndarray, Series, Index]" has no 686 # attribute "name" (...) 691 typ=manager, 692 ) 693 else: --> 694 mgr = ndarray_to_mgr( 695 data, 696 index, 697 columns, 698 dtype=dtype, 699 copy=copy, 700 typ=manager, 701 ) 703 # For data is list-like, or Iterable (will consume into list) 704 elif is_list_like(data): File /opt/conda/lib/python3.10/site-packages/pandas/core/internals/construction.py:351, in ndarray_to_mgr(values, index, columns, dtype, copy, typ) 346 # _prep_ndarray ensures that values.ndim == 2 at this point 347 index, columns = _get_axes( 348 values.shape[0], values.shape[1], index=index, columns=columns 349 ) --> 351 _check_values_indices_shape_match(values, index, columns) 353 if typ == "array": 355 if issubclass(values.dtype.type, str): File /opt/conda/lib/python3.10/site-packages/pandas/core/internals/construction.py:422, in _check_values_indices_shape_match(values, index, columns) 420 passed = values.shape 421 implied = (len(index), len(columns)) --> 422 raise ValueError(f"Shape of passed values is {passed}, indices imply {implied}") ValueError: Shape of passed values is (2, 2), indices imply (2, 3) ``` ### Versions ```shell python3, sklearn = 1.2.1 ```

null

https://github.com/scikit-learn/scikit-learn/pull/26600

null

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[]

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1

nvbn

thefuck

9660ec7813a0e77ec3411682b0084d07b540084e

https://github.com/nvbn/thefuck/issues/543

Adding sudo works for `aura -Sy` but not `aura -Ay`

`fuck` is unable to add `sudo` to an `aura -Ay` command: ``` $ aura -Ay foobar-beta-git # from AUR aura >>= You have to use `sudo` for that. $ fuck No fucks given ``` But works as expected for `aura -Sy`: ``` $ aura -Sy foobar # pacman alias error: you cannot perform this operation unless you are root. aura >>= Please check your input. $ fuck sudo aura -Sy foobar [enter/↑/↓/ctrl+c] ``` It's slightly annoying anyway that the `aura` outut is different in these cases, but is it possible for `thefuck` to work-around? Or is the only way for `aura` to give a stderr message containing "root"?

null

https://github.com/nvbn/thefuck/pull/557

null

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[]

{ "iss_type": "2", "iss_reason": "1", "loc_way": "pr", "loc_scope": "", "info_type": "" }

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1

scikit-learn

2707099b23a0a8580731553629566c1182d26f48

https://github.com/scikit-learn/scikit-learn/issues/29294

Moderate help wanted

ConvergenceWarnings cannot be turned off

Hi, I'm unable to turn off convergence warnings from `GraphicalLassoCV`. I've tried most of the solutions from, and none of them worked (see below for actual implementations): https://stackoverflow.com/questions/879173/how-to-ignore-deprecation-warnings-in-python https://stackoverflow.com/questions/32612180/eliminating-warnings-from-scikit-learn/33812427#33812427 https://stackoverflow.com/questions/53968004/how-to-silence-all-sklearn-warning https://stackoverflow.com/questions/14463277/how-to-disable-python-warnings Contrary to what the designers of the sklearn's exceptions must have thought when it was implemented, some of us actually use stdout to log important information of the host program for diagnostics purposes. Flooding it with garbage that cannot be turned off, as is in the case with cross-validation, is not ok. To briefly speak to the severity of the issue, the above sklearn-specific questions relating to suppressing warnings have been viewed ~500K times with combined ~400 upvotes, and dates back 7 years. I've tried the following (`n_jobs` parameter does not appear to affect the result): ```py from sklearn.covariance import GraphicalLassoCV import warnings warnings.filterwarnings("ignore", category=ConvergenceWarning) model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py from sklearn.covariance import GraphicalLassoCV import warnings warnings.filterwarnings(action='ignore') model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py import warnings with warnings.catch_warnings(): warnings.simplefilter("ignore", ConvergenceWarning) model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py from sklearn.covariance import GraphicalLassoCV def warn(*args, **kwargs): pass import warnings warnings.warn = warn model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py import contextlib import os, sys @contextlib.contextmanager def suppress_stdout(): with open(os.devnull, 'w') as fnull: old_stdout = sys.stdout sys.stdout = fnull try: yield finally: sys.stdout = old_stdout with suppress_stdout(): model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ``` ```py import logging logging.captureWarnings(True) logging.getLogger("py.warnings").setLevel(logging.ERROR) model = GraphicalLassoCV(n_jobs=4) model = model.fit(data) ```

null

https://github.com/scikit-learn/scikit-learn/pull/30380

null

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{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

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1

All-Hands-AI

OpenHands

7b2b1eff57e41364b4b427e36e766607e7eed3a0

https://github.com/All-Hands-AI/OpenHands/issues/20

Control Loop: long term planning and execution

The biggest, most complicated aspect of Devin is long-term planning and execution. I'd like to start a discussion about how this might work in OpenDevin. There's some [recent prior work from Microsoft](https://arxiv.org/pdf/2403.08299.pdf) with some impressive results. I'll summarize here, with some commentary. ## Overall Flow * User specifies objective and associated settings * Conversation Manager kicks in * Sends convo to Agent Scheduler * Agents execute commands * Output is placed back into the conversation * Rinse and repeat ## Configuraiton * A YAML file defines a set of actions/commands the bot can take (e.g. `npm test`) * comment: why not just leave it open-ended? * You can have different agents with different capabilities, e.g. a "dev agent" and a "reviewer agent", who work collaboratively * comment: this sounds like MetaGPT ## Components ### Conversation Manager * maintains message history and command outputs * decides when to interrupt the conversation * comment: for what? more info from the user? * decides when the conversation is over, i.e. task has been completed * agent can send a "stop" command, max tokens can be reached, problems w/ execution environment ### Parser * interprets agent output and turns it into commands, file edits, etc * in case of parsing failure, a message is sent back to the agent to rewrite its command ### Output Organizer * Takes command output and selectively places it into the conversation history * sometimes summarizes the content first * comment: why not just drop everything back into the conversation history (maybe truncating really long CLI output) ### Agent Scheduler * orchestrates different agents * uses different algos for deciding who gets to go next * round-robin: everyone takes turns in order * token-based: agent gets to keep going until it says it's done * priority-based: agents go based on (user defined?) priority ### Tools Library * file editing (can edit entire file, or specify start line and end line) * retrieval (file contents, `ls`, `grep`). Seems to use vector search as well * build and execution: abstracts away the implementation in favor of simple commands like `build foo` * testing and validation: includes linters and bug-finding utils * git: can commit, push, merge * communication: can as human for input/feedback, can talk to other agents ### Evaluation Environment * runs in Docker

null

https://github.com/All-Hands-AI/OpenHands/pull/3771

null

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[]

{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

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1

All-Hands-AI

OpenHands

2242702cf94eab7275f2cb148859135018d9b280

https://github.com/All-Hands-AI/OpenHands/issues/1251

enhancement

Sandbox Capabilities Framework

**Summary** We have an existing use case for a Jupyter-aware agent, which always runs in a sandbox where Jupyter is available. There are some other scenarios I can think of where an agent might want some guarantees about what it can do with the sandbox: * We might want a "postgres migration writer", which needs access to a postgres instance * We might have a "cypress test creator" agent, which would need access to cypress * Further down the road, we might want to have an [Open Interpreter](https://github.com/OpenInterpreter/open-interpreter) agent, which needs access to osascript * etc etc This proposal would allow agents to guarantee that certain programs are available in the sandbox, or that certain services are running in a predictable way. What if we did something like this: **Motivation** We want agents to be able to have certain guarantees about the sandbox environment. But we also want our sandbox interface to be generic--something like "you have a bash terminal". The latter is especially important, because we want users to be able to bring their own sandbox images. E.g. you might use an off-the-shelf haskell image if your project uses haskell--otherwise you'd need to go through the install process every time you start OpenDevin, or maintain a fork of the sandbox. **Technical Design** * For every requirement we support (e.g. jupyter, postgres, cypress), we have a bash script that * checks if it's installed * if not, installs it * maybe starts something in the background * Let agents specify a list of requirements * e.g. CodeActAgent could say requirements: ['jupyter'] * When we start the Agent+Sandbox pair, we run the necessary bash scripts * should be pretty quick if the requirement is already built into the image * Then the agent has some guarantees about the requirement being met, and how it's running * e.g. we can put in the prompt "there's a postgres server running on port 5432, user foo, password bar" * If there are specific ways of interacting with that env (e.g. for jupyter, it seems we have to write to a websocket that's open in the sandbox?) the agent can implement custom Actions, like run_in_jupyter **Alternatives to Consider** * Building a bunch of stuff into one big sandbox * Building special sandboxes that are required by certain agents (e.g. a JupyterSandbox) **Additional context** https://opendevin.slack.com/archives/C06QKSD9UBA/p1713552591042089

null

https://github.com/All-Hands-AI/OpenHands/pull/1255

null

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[]

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1

deepfakes

faceswap

0ea743029db0d47f09d33ef90f50ad84c20b085f

https://github.com/deepfakes/faceswap/issues/263

Very slow extraction with scripts vs fakeapp 1.1

1080ti + OC'd 2600k using winpython 3.6.2 cuda 9.0 and tensorflow 1.6 **Training** utilizes ~50% of the GPU now (which is better than the ~25% utilized with FA 1.1) but extraction doesn't seem to utilize the GPU at all (getting around 1.33it/s) wheras with FA 1.1 I get around 17it/s - tried CNN and it dropped down to taking nearly a minute per file. Although I say it doesn't utilize the GPU it still seems to use all 11GB of RAM on the GPU, just none of the compute cores or processor are in use. CPU is using about 17%. Tried using extracted data from FA 1.1 with .py -convert but it just says 'no alignment found for file: x" for every file even tho --alignments points to the path with alignments.json I would've thought the alignments.json from FA 1.1 was compatible so I'm not sure if the above is a separate issue or not.

null

https://github.com/deepfakes/faceswap/pull/259

null

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1

fastapi

ef176c663195489b44030bfe1fb94a317762c8d5

https://github.com/fastapi/fastapi/issues/3323

feature reviewed

Support PEP 593 `Annotated` for specifying dependencies and parameters

### First check * [x] I added a very descriptive title to this issue. * [x] I used the GitHub search to find a similar issue and didn't find it. * [x] I searched the FastAPI documentation, with the integrated search. * [x] I already searched in Google "How to X in FastAPI" and didn't find any information. * [x] I already read and followed all the tutorial in the docs and didn't find an answer. * [x] I already checked if it is not related to FastAPI but to [Pydantic](https://github.com/samuelcolvin/pydantic). * [x] I already checked if it is not related to FastAPI but to [Swagger UI](https://github.com/swagger-api/swagger-ui). * [x] I already checked if it is not related to FastAPI but to [ReDoc](https://github.com/Redocly/redoc). * [x] After submitting this, I commit to: * Read open issues with questions until I find 2 issues where I can help someone and add a comment to help there. * Or, I already hit the "watch" button in this repository to receive notifications and I commit to help at least 2 people that ask questions in the future. * Implement a Pull Request for a confirmed bug. ### Example I propse to allow transforming:  ```Python from typing import Optional from fastapi import Depends, FastAPI app = FastAPI() async def common_parameters(q: Optional[str] = None, skip: int = 0, limit: int = 100): return {"q": q, "skip": skip, "limit": limit} @app.get("/items/") async def read_items(commons: dict = Depends(common_parameters)): return commons ``` to ```Python from typing import Annotated, Optional from fastapi import Depends, FastAPI app = FastAPI() async def common_parameters(q: Optional[str] = None, skip: int = 0, limit: int = 100): return {"q": q, "skip": skip, "limit": limit} @app.get("/items/") async def read_items(commons: Annotated[dict, Depends(common_parameters)]): return commons ``` ### Discussion [PEP 593](https://www.python.org/dev/peps/pep-0593/) Added `Annotated` for adding additional annotations beyond type annotations. I think FastAPI's `Depends`, `Query`, `Body` and the likes fit well with the kind of additional annotations this supports. This would also make default values less awkward: ```python @app.get("/items/") async def read_items(q: Optional[str] = Query(None, max_length=50)): pass ``` Could become ```python @app.get("/items/") async def read_items(q: Annotated[Optional[str], Query(max_length=50)] = None): pass ``` This will also solve the issue mentioned [in the docs](https://fastapi.tiangolo.com/tutorial/path-params-numeric-validations/#order-the-parameters-as-you-need) of parameter ordering. Finally, it is sometimes convenient to use the same function as both a FastAPI dependency and a regular function. In these cases, because `= Depends(...)` is a default parameter value, if you forget to pass a parameter the error is not caught by your IDE. Worse, it is not caught at runtime because Python will just pass along the `Depends` object. This will probably cause an error down the road, but may silently succeed in some cases. I'm willing to implement this if you think it's a good idea.

null

https://github.com/fastapi/fastapi/pull/4871

null

{'base_commit': 'ef176c663195489b44030bfe1fb94a317762c8d5', 'files': [{'path': 'fastapi/dependencies/utils.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [58], 'mod': [51]}, "(None, 'get_dependant', 282)": {'add': [336], 'mod': [301, 303, 307, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335]}, "(None, 'get_param_sub_dependant', 114)": {'mod': [115, 117, 118, 119, 120, 121, 124, 126]}, "(None, 'add_non_field_param_to_dependency', 340)": {'mod': [341, 343, 344, 346, 347, 349, 350, 352, 353, 355, 356, 358, 359]}, "(None, 'get_param_field', 364)": {'mod': [364, 366, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 416]}}}, {'path': 'fastapi/param_functions.py', 'status': 'modified', 'Loc': {"(None, 'Path', 7)": {'mod': [8]}}}, {'path': 'fastapi/params.py', 'status': 'modified', 'Loc': {"('Path', '__init__', 63)": {'add': [82], 'mod': [65, 85]}, "('Form', '__init__', 280)": {'mod': [282]}, "('File', '__init__', 320)": {'mod': [322]}}}, {'path': 'fastapi/utils.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [1]}, "(None, 'create_response_field', 60)": {'mod': [76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 88]}}}, {'path': 'tests/main.py', 'status': 'modified', 'Loc': {"(None, 'get_path_param_id', 52)": {'mod': [52, 53, 56, 57]}}}, {'path': 'tests/test_application.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257]}}}, {'path': 'tests/test_params_repr.py', 'status': 'modified', 'Loc': {"(None, 'test_path_repr', 22)": {'mod': [22, 23]}}}, {'path': 'tests/test_path.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [196]}}}]}

[]

{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "fastapi/dependencies/utils.py", "fastapi/utils.py", "fastapi/param_functions.py", "tests/main.py", "fastapi/params.py" ], "doc": [], "test": [ "tests/test_params_repr.py", "tests/test_application.py", "tests/test_path.py" ], "config": [], "asset": [] }

1

python

cpython

e01eeb7b4b8d00b9f5c6acb48957f46ac4e252c0

https://github.com/python/cpython/issues/92417

docs

Many references to unsupported Python versions in the stdlib docs

**Documentation** There are currently many places in the stdlib docs where there are needless comments about how to maintain compatibility with Python versions that are now end-of-life. Many of these can now be removed, to improve brevity and clarity in the documentation. I plan to submit a number of PRs to fix these. PRs: - #92418 - #92419 - #92420 - #92421 - #92422 - #92423 - #92424 - #92425 - https://github.com/python/cpython/pull/92502 - #92538 - #92539 - #92543 - #92544 - [More to come] Backports: - https://github.com/python/cpython/pull/92459 - https://github.com/python/cpython/pull/92460 - https://github.com/python/cpython/pull/92461 - https://github.com/python/cpython/pull/92462 - https://github.com/python/cpython/pull/92463 - https://github.com/python/cpython/pull/92491 - https://github.com/python/cpython/pull/92467 - https://github.com/python/cpython/pull/92468 - https://github.com/python/cpython/pull/92492 - https://github.com/python/cpython/pull/92464 - https://github.com/python/cpython/pull/92465 - https://github.com/python/cpython/pull/92466 - https://github.com/python/cpython/pull/92472 - https://github.com/python/cpython/pull/92473 - https://github.com/python/cpython/pull/92474 - https://github.com/python/cpython/pull/92485 - https://github.com/python/cpython/pull/92486 - https://github.com/python/cpython/pull/92487 - https://github.com/python/cpython/pull/92606 - https://github.com/python/cpython/pull/92607

null

https://github.com/python/cpython/pull/92539

null

{'base_commit': 'e01eeb7b4b8d00b9f5c6acb48957f46ac4e252c0', 'files': [{'path': 'Doc/library/unittest.mock-examples.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [663]}}}, {'path': 'Doc/library/unittest.mock.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [2384]}}}]}

[]

{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": " ", "info_type": "" }

{ "code": [], "doc": [ "Doc/library/unittest.mock-examples.rst", "Doc/library/unittest.mock.rst" ], "test": [], "config": [], "asset": [] }

1

scikit-learn

23d8761615d0417eef5f52cc796518e44d41ca2a

https://github.com/scikit-learn/scikit-learn/issues/19248

Documentation module:cluster

Birch should be called BIRCH

C.f. the original paper. Zhang, T.; Ramakrishnan, R.; Livny, M. (1996). "BIRCH: an efficient data clustering method for very large databases". Proceedings of the 1996 ACM SIGMOD international conference on Management of data - SIGMOD '96. pp. 103–114. doi:10.1145/233269.233324

null

https://github.com/scikit-learn/scikit-learn/pull/19368

null

{'base_commit': '23d8761615d0417eef5f52cc796518e44d41ca2a', 'files': [{'path': 'doc/modules/clustering.rst', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [106, 946, 965, 999, 1001, 1005]}}}, {'path': 'examples/cluster/plot_birch_vs_minibatchkmeans.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [6, 39, 48, 58, 78]}}}, {'path': 'examples/cluster/plot_cluster_comparison.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [146]}}}, {'path': 'sklearn/cluster/_birch.py', 'status': 'modified', 'Loc': {"('Birch', None, 335)": {'mod': [336]}, "('Birch', '_global_clustering', 648)": {'mod': [677]}}}]}

[]

{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "examples/cluster/plot_birch_vs_minibatchkmeans.py", "sklearn/cluster/_birch.py", "examples/cluster/plot_cluster_comparison.py" ], "doc": [ "doc/modules/clustering.rst" ], "test": [], "config": [], "asset": [] }

1

localstack

65b807e4e95fe6da3e30f13e4271dc9dcfaa334e

https://github.com/localstack/localstack/issues/402

type: bug

Dynamodbstreams Use Kinesis Shard Identifiers

Dynamodbstreams seem to be making use of Kinesis shard identifiers which are considered invalid by botocore request validators. Error response from boto3 when attempting to `get_shard_iterator` from shard ids returned from `describe_stream`: ``` [test-integration:L51:27s] exception = ParamValidationError(u'Parameter validation failed:\nInvalid length for parameter ShardId, value: 20, valid range: 28-inf',) [test-integration:L52:27s] [test-integration:L53:27s] def _reraise_exception(self, exception): [test-integration:L54:27s] if hasattr(exception, 'response'): [test-integration:L55:27s] code = exception.response['Error']['Code'] [test-integration:L56:27s] [test-integration:L57:27s] if code == 'TrimmedDataAccessException': [test-integration:L58:27s] raise TrimmedRecordsException() [test-integration:L59:27s] elif code == 'ResourceNotFoundException': [test-integration:L60:27s] raise ResourceDNEException() [test-integration:L61:27s] [test-integration:L62:27s] > raise exception [test-integration:L63:27s] E ParamValidationError: Parameter validation failed: [test-integration:L64:27s] E Invalid length for parameter ShardId, value: 20, valid range: 28-inf [test-integration:L65:27s] [test-integration:L66:27s] .tox/py27/lib/python2.7/site-packages/pyrokinesis/dynamodbstreams_ingress_backend.py:111: ParamValidationError ``` The following is the response object I am getting back when I `describe_stream` on the stream's ARN: ``` [test-integration:L68:27s] {'ResponseMetadata': {'HTTPStatusCode': 200, 'RetryAttempts': 0, 'HTTPHeaders': {'content-length': '692', 'access-control-allow-origin': '*', 'date': 'Fri, 13 Oct 2017 12:47:00 GMT', 'server': 'Werkzeug/0.12.2 Python/2.7.13', 'content-type': 'application/json'}}, u'StreamDescription': {u'StreamLabel': u'TODO', u'StreamArn': u'arn:aws:dynamodb:us-east-1:000000000000:table/DynamoTest/stream/2017-10-13T12:47:00', u'Shards': [{u'ShardId': u'shardId-000000000000', u'SequenceNumberRange': {u'StartingSequenceNumber': u'49577893583130519883135457518096755974321873497073123330'}}], u'KeySchema': [{u'KeyType': u'HASH', u'AttributeName': u'ID'}], u'TableName': u'DynamoTest', u'StreamStatus': u'ENABLED'}} ``` My localstack setup: ``` localstack 0.7.3 [localstack:L2:1s] 2017-10-13 15:10:35,915 INFO spawned: 'dashboard' with pid 13 [localstack:L3:1s] 2017-10-13 15:10:35,917 INFO spawned: 'infra' with pid 14 [localstack:L4:1s] (. .venv/bin/activate; bin/localstack web --port=8080) [localstack:L5:1s] (. .venv/bin/activate; exec bin/localstack start) [localstack:L6:1s] Starting local dev environment. CTRL-C to quit. [localstack:L7:1s] * Running on http://0.0.0.0:8080/ (Press CTRL+C to quit) [localstack:L8:1s] * Restarting with stat [localstack:L9:1s] Starting mock Kinesis (http port 4568)... [localstack:L10:1s] Starting mock S3 (http port 4572)... [localstack:L11:1s] Starting mock DynamoDB (http port 4569)... [localstack:L12:1s] * Debugger is active! [localstack:L13:2s] * Debugger PIN: 281-540-735 [localstack:L14:2s] 2017-10-13 15:10:37,123 INFO success: dashboard entered RUNNING state, process has stayed up for > than 1 seconds (startsecs) [localstack:L15:2s] 2017-10-13 15:10:37,123 INFO success: infra entered RUNNING state, process has stayed up for > than 1 seconds (startsecs) [localstack:L16:2s] Starting mock DynamoDB Streams service (http port 4570)... [localstack:L17:2s] Listening at http://:::4565 [localstack:L18:2s] Initializing DynamoDB Local with the following configuration: [localstack:L19:2s] Port: 4564 [localstack:L20:2s] InMemory: false [localstack:L21:2s] DbPath: /tmp/localstack/dynamodb [localstack:L22:2s] SharedDb: true [localstack:L23:2s] shouldDelayTransientStatuses: false [localstack:L24:2s] CorsParams: * [localstack:L25:2s] [localstack:L26:2s] * Running on http://0.0.0.0:4563/ (Press CTRL+C to quit) ```

null

https://github.com/localstack/localstack/pull/403

null

{'base_commit': '65b807e4e95fe6da3e30f13e4271dc9dcfaa334e', 'files': [{'path': 'localstack/services/dynamodbstreams/dynamodbstreams_api.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'add': [1, 119]}, "(None, 'post_request', 47)": {'add': [76], 'mod': [70, 78]}}}]}

[]

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{ "code": [ "localstack/services/dynamodbstreams/dynamodbstreams_api.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

pallets

flask

ee76129812419d473eb62434051e81d5855255b6

https://github.com/pallets/flask/issues/602

Misspelling in docs @ flask.Flask.handle_exception

`Default exception handling that kicks in when an exception occours that is not caught. In debug mode the exception will be re-raised immediately, otherwise it is logged and the handler for a 500 internal server error is used. If no such handler exists, a default 500 internal server error message is displayed.` Occours should be occurs. I looked around in the project code to see if i could update this, but it looks like the docs subdir is no longer used? I could be wrong, if you let me know where this is at I'll update it and send a PR :)

null

https://github.com/pallets/flask/pull/603

null

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[]

{ "iss_type": "3", "iss_reason": "1", "loc_way": "pr", "loc_scope": "不太确定问题类别，因为是开发者询问typo error", "info_type": "" }

{ "code": [ "flask/app.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

ansible

79d00adc52a091d0ddd1d8a96b06adf2f67f161b

https://github.com/ansible/ansible/issues/36378

cloud aws module affects_2.4 support:certified docs

Documentation Error for ec2_vpc_nacl rules

##### ISSUE TYPE - Documentation Report ##### COMPONENT NAME ec2_vpc_nacl ##### ANSIBLE VERSION ``` ansible 2.4.3.0 config file = None configured module search path = [u'/home/ubuntu/.ansible/plugins/modules', u'/usr/share/ansible/plugins/modules'] ansible python module location = /usr/local/lib/python2.7/dist-packages/ansible executable location = /usr/local/bin/ansible python version = 2.7.12 (default, Dec 4 2017, 14:50:18) [GCC 5.4.0 20160609] ``` ##### CONFIGURATION ##### OS / ENVIRONMENT N/A ##### SUMMARY The example documentation is the wrong way round for ec2_vpc_nacl with respect to the icmp code and type. ##### STEPS TO REPRODUCE https://github.com/ansible/ansible/blob/devel/lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py#L87 has the order of the `icmp_code` and `icmp_type` inverted compared to the code that parses it https://github.com/ansible/ansible/blob/devel/lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py#L298 ##### EXPECTED RESULTS ##### ACTUAL RESULTS

null

https://github.com/ansible/ansible/pull/36380

null

{'base_commit': '79d00adc52a091d0ddd1d8a96b06adf2f67f161b', 'files': [{'path': 'lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py', 'status': 'modified', 'Loc': {'(None, None, None)': {'mod': [87]}}}]}

[]

{ "iss_type": "2", "iss_reason": "2", "loc_way": "pr", "loc_scope": "", "info_type": "" }

{ "code": [ "lib/ansible/modules/cloud/amazon/ec2_vpc_nacl.py" ], "doc": [], "test": [], "config": [], "asset": [] }

1

geekan

MetaGPT

a32e238801d0a8f3c1bd97b98d038b40977a8cc6

https://github.com/geekan/MetaGPT/issues/1174

New provider: Amazon Bedrock (AWS)

**Feature description** Please include support for Amazon Bedrock models. These models can be from Amazon, Anthropic, AI21, Cohere, Mistral, or Meta Llama 2. **Your Feature** 1. Create a new LLM Provides under [metagpt/provider](https://github.com/geekan/MetaGPT/tree/db65554c4931d4a95e20331b770cf4f7e5202264/metagpt/provider) for Amazon Bedrock 2. Include it in the [LLMType](https://github.com/geekan/MetaGPT/blob/db65554c4931d4a95e20331b770cf4f7e5202264/metagpt/configs/llm_config.py#L17) available

null

https://github.com/geekan/MetaGPT/pull/1231

null

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[]

{ "iss_type": "4", "iss_reason": "2", "loc_way": "pr", "loc_scope": null, "info_type": null }

{ "code": [ "metagpt/utils/token_counter.py", "metagpt/provider/__init__.py", "metagpt/configs/llm_config.py", "config/puppeteer-config.json", "tests/metagpt/provider/mock_llm_config.py", "tests/metagpt/provider/req_resp_const.py" ], "doc": [], "test": [], "config": [ "requirements.txt" ], "asset": [] }

1

pandas-dev

pandas

862cd05df4452592a99dd1a4fa10ce8cfb3766f7

https://github.com/pandas-dev/pandas/issues/37494

Enhancement Groupby ExtensionArray NA - MaskedArrays Closing Candidate

ENH: improve the resulting dtype for groupby operations on nullable dtypes

Follow-up on https://github.com/pandas-dev/pandas/pull/37433, and partly related to https://github.com/pandas-dev/pandas/issues/37493 Currently, after groupby operations we try to cast back to the original dtype when possible (at least in case of extension arrays). But this is not always correct, and also not done consistently. Some examples using the test case from the mentioned PR using a nullable Int64 column as input: ``` In [1]: df = DataFrame( ...: { ...: "A": ["A", "B"] * 5, ...: "B": pd.array([1, 2, 3, 4, 5, 6, 7, 8, 9, pd.NA], dtype="Int64"), ...: } ...: ) In [2]: df.groupby("A")["B"].sum() Out[2]: A A 25 B 20 Name: B, dtype: Int64 In [3]: df.groupby("A")["B"].std() Out[3]: A A 3.162278 B 2.581989 Name: B, dtype: float64 In [4]: df.groupby("A")["B"].mean() Out[4]: A A 5 B 5 Name: B, dtype: Int64 In [5]: df.groupby("A")["B"].count() Out[5]: A A 5 B 4 Name: B, dtype: int64 ``` So some observations: * For `sum()`, we correctly have Int64 for the result * For `std()`, we could use the nullable Float64 instead of float64 dtype * For `mean()`, we incorrectly cast back to Int64 dtype, as the result of mean should always be floating (in this case the casting just happened to work because the means were rounded numbers) * For `count()`, we did not create a nullable Int64 dtype for the result, while this could be done in the input is nullable

null

https://github.com/pandas-dev/pandas/pull/38291

null

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[]

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{ "code": [ "pandas/core/dtypes/cast.py", "pandas/core/groupby/ops.py" ], "doc": [], "test": [ "pandas/tests/groupby/aggregate/test_cython.py", "pandas/tests/arrays/integer/test_arithmetic.py", "pandas/tests/resample/test_datetime_index.py", "pandas/tests/groupby/test_function.py" ], "config": [], "asset": [] }

1

Datasets:

somethingone
/

MULocBench

1. Downloads

2. How to Use DataSet

3. Data Instances