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@@ -89,7 +89,7 @@ class LCBNet(nn.Module):
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text_encoder = text_encoder_class(input_size=vocab_size, **text_encoder_conf)
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fusion_encoder_class = tables.encoder_classes.get(fusion_encoder)
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fusion_encoder = fusion_encoder_class(**fusion_encoder_conf)
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- bias_predictor_class = tables.encoder_classes.get_class(bias_predictor)
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+ bias_predictor_class = tables.encoder_classes.get(bias_predictor)
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bias_predictor = bias_predictor_class(bias_predictor_conf)
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if decoder is not None:
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@@ -414,7 +414,7 @@ class LCBNet(nn.Module):
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self.init_beam_search(**kwargs)
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self.nbest = kwargs.get("nbest", 1)
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pdb.set_trace()
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-
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+
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meta_data = {}
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if isinstance(data_in, torch.Tensor) and kwargs.get("data_type", "sound") == "fbank": # fbank
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speech, speech_lengths = data_in, data_lengths
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