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@ -197,8 +197,6 @@ class Conformer(EncoderInterface):
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x = x.permute(1, 0, 2) # (T, N, C) ->(N, T, C)
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x = x.permute(1, 0, 2) # (T, N, C) ->(N, T, C)
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layer_output = [x.permute(1, 0, 2) for x in layer_output]
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return x, lengths
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return x, lengths
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@torch.jit.export
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@torch.jit.export
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@ -695,8 +693,6 @@ class ConformerEncoder(nn.Module):
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outputs = []
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outputs = []
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layer_output = []
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for i, mod in enumerate(self.layers):
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for i, mod in enumerate(self.layers):
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output = mod(
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output = mod(
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output,
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output,
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@ -708,8 +704,6 @@ class ConformerEncoder(nn.Module):
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if i in self.aux_layers:
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if i in self.aux_layers:
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outputs.append(output)
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outputs.append(output)
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layer_output.append(output)
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output = self.combiner(outputs)
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output = self.combiner(outputs)
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return output, layer_output
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return output, layer_output
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