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egs/librispeech/ASR/.run_v2.sh.swp
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egs/librispeech/ASR/.run_v2.sh.swp
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@ -459,7 +459,8 @@ def get_encoder_model(params: AttributeDict) -> nn.Module:
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# TODO: We can add an option to switch between Zipformer and Transformer
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def to_int_tuple(s: str):
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return tuple(map(int, s.split(",")))
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'''
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encoder = Zipformer(
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num_features=params.feature_dim,
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output_downsampling_factor=2,
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@ -474,6 +475,15 @@ def get_encoder_model(params: AttributeDict) -> nn.Module:
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cnn_module_kernels=to_int_tuple(params.cnn_module_kernels),
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num_encoder_layers=to_int_tuple(params.num_encoder_layers),
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)
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'''
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encoder = FairSeqData2VecEncoder(
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input_size=768, #params.encoder_dim,
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w2v_url='None',
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output_size=768, #params.encoder_dim,
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freeze_finetune_updates=0, #params.freeze_finetune_updates*params.accum_grads,
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additional_block=True, #params.additional_block,
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)
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return encoder
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