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Top:
   epoch
   extras
   state_dict
   arch
-------------------------------------
arch: ai85nascifarnet
-------------------------------------
extras: None
-------------------------------------
state_dict:
   conv1_1
     output_shift:         [-1.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       64
        min, max, mean: -0.09798126 ,  0.08990779 ,  0.008875869
     weight
        total # of elements, shape: 1728 , [64, 3, 3, 3]
        # of unique elements:       1728
        min, max, mean: -0.59848505 ,  0.75632256 ,  -0.0006143634
   conv1_2
     output_shift:         [-1.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 32 , [32]
        # of unique elements:       32
        min, max, mean: -0.31733915 ,  0.22386183 ,  0.10140069
     weight
        total # of elements, shape: 2048 , [32, 64, 1, 1]
        # of unique elements:       2048
        min, max, mean: -0.58420384 ,  0.40819037 ,  -0.01869129
   conv1_3
     output_shift:         [-1.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       64
        min, max, mean: -0.23203957 ,  0.51034755 ,  0.08287333
     weight
        total # of elements, shape: 18432 , [64, 32, 3, 3]
        # of unique elements:       18431
        min, max, mean: -0.59151775 ,  0.43220478 ,  -0.0057644206
   conv2_1
     output_shift:         [-3.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 32 , [32]
        # of unique elements:       32
        min, max, mean: -0.30094182 ,  0.42980048 ,  0.070355654
     weight
        total # of elements, shape: 18432 , [32, 64, 3, 3]
        # of unique elements:       18428
        min, max, mean: -0.16991019 ,  0.21769144 ,  4.4027212e-05
   conv2_2
     output_shift:         [-0.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       64
        min, max, mean: -0.5276564 ,  0.5653206 ,  0.052891113
     weight
        total # of elements, shape: 2048 , [64, 32, 1, 1]
        # of unique elements:       2048
        min, max, mean: -0.9724338 ,  1.1061882 ,  -0.018025849
   conv3_1
     output_shift:         [-3.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       128
        min, max, mean: -0.6170407 ,  0.65429825 ,  0.078679465
     weight
        total # of elements, shape: 73728 , [128, 64, 3, 3]
        # of unique elements:       73688
        min, max, mean: -0.16440398 ,  0.16517481 ,  -0.00033442382
   conv3_2
     output_shift:         [-1.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       128
        min, max, mean: -0.3768113 ,  0.6656874 ,  0.15580902
     weight
        total # of elements, shape: 16384 , [128, 128, 1, 1]
        # of unique elements:       16380
        min, max, mean: -0.58836114 ,  0.5506579 ,  -0.013571151
   conv4_1
     output_shift:         [-3.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 64 , [64]
        # of unique elements:       64
        min, max, mean: -0.6558978 ,  0.82889 ,  -0.069669336
     weight
        total # of elements, shape: 73728 , [64, 128, 3, 3]
        # of unique elements:       73680
        min, max, mean: -0.13145642 ,  0.13042527 ,  0.0003467776
   conv4_2
     output_shift:         [-2.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [2.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       128
        min, max, mean: -0.32796454 ,  0.26320904 ,  0.056867614
     weight
        total # of elements, shape: 73728 , [128, 64, 3, 3]
        # of unique elements:       73674
        min, max, mean: -0.3363212 ,  0.26312655 ,  -7.0956354e-05
   conv5_1
     output_shift:         [-1.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 128 , [128]
        # of unique elements:       128
        min, max, mean: -0.38399914 ,  0.5454449 ,  0.09726812
     weight
        total # of elements, shape: 16384 , [128, 128, 1, 1]
        # of unique elements:       16378
        min, max, mean: -0.4663344 ,  0.5532854 ,  -0.0005959581
   fc
     output_shift:         [1.]
     adjust_output_shift:  [1.]
     quantize_activation:  [1.]
     shift_quantile:       [0.985]
     weight bits:          [8.]
     bias_bits:            [8.]
     bias
        total # of elements, shape: 100 , [100]
        # of unique elements:       100
        min, max, mean: -0.198709 ,  0.18128031 ,  -0.0039853672
     weight
        total # of elements, shape: 51200 , [100, 512]
        # of unique elements:       51173
        min, max, mean: -2.3624063 ,  1.3867925 ,  -0.15939271