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| | | |
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| | | import torch |
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| | | import torch.nn.functional as F |
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| | | from typeguard import check_argument_types |
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| | | |
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| | | |
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| | | class CTC(torch.nn.Module): |
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| | |
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| | | reduce: bool = True, |
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| | | ignore_nan_grad: bool = True, |
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| | | ): |
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| | | assert check_argument_types() |
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| | | super().__init__() |
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| | | eprojs = encoder_output_size |
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| | | self.dropout_rate = dropout_rate |
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| | |
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| | | if ignore_nan_grad: |
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| | | logging.warning("ignore_nan_grad option is not supported for warp_ctc") |
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| | | self.ctc_loss = warp_ctc.CTCLoss(size_average=True, reduce=reduce) |
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| | | |
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| | | elif self.ctc_type == "gtnctc": |
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| | | from espnet.nets.pytorch_backend.gtn_ctc import GTNCTCLossFunction |
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| | | |
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| | | self.ctc_loss = GTNCTCLossFunction.apply |
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| | | else: |
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| | | raise ValueError( |
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| | | f'ctc_type must be "builtin" or "warpctc": {self.ctc_type}' |
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