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from lhotse import CutSet, load_manifest_lazy |
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import torch |
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manifest_path = "data/fbank/cuts_debug.jsonl.gz" |
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manifest_path = "data/fbank_voice_assistant_cosy2_hdf5/cuts_debug_h5py.jsonl.gz" |
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cuts_manifest = load_manifest_lazy(manifest_path) |
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|
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for i, cut in enumerate(cuts_manifest): |
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feats = cut.load_features() |
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feats = torch.from_numpy(feats) |
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if torch.isnan(feats).any() or torch.isinf(feats).any(): |
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print("cut.load_features() nan or inf, index: ", i) |
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nan_indices = torch.where(torch.isnan(feats)) |
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inf_indices = torch.where(torch.isinf(feats)) |
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print(feats[nan_indices]) |
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print(feats[inf_indices]) |
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print("fbank nan or inf") |
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print(f"nan_indices: {nan_indices}, inf_indices: {inf_indices}") |
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exit() |
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