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@ -638,7 +638,6 @@ def compute_loss(
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ctc_loss = (1-params.interctc_weight) * ctc_loss + params.interctc_weight * inter_ctc_loss
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else:
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'''
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dense_fsa_vec = k2.DenseFsaVec(
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nnet_output,
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supervision_segments,
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@ -652,6 +651,7 @@ def compute_loss(
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reduction=params.reduction,
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use_double_scores=params.use_double_scores,
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)
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'''
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dense_fsa_vec = k2.DenseFsaVec(
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nnet_output[0],
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@ -706,6 +706,7 @@ def compute_loss(
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)
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ctc_loss = (1-params.interctc_weight) * ctc_loss + params.interctc_weight * inter_ctc_loss
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'''
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if params.att_rate > 0.0:
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with torch.set_grad_enabled(is_training):
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