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Remove query from AttentionDownsample, rename to SimpleDownsample

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This commit is contained in:
Daniel Povey 2022-12-17 13:45:30 +08:00
parent ed7e01448c
commit 86bb0623e9
1 changed files with 5 additions and 5 deletions
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10
egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
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@ -209,7 +209,7 @@ class Zipformer(EncoderInterface):
# initializes self.skip_layers and self.skip_modules # initializes self.skip_layers and self.skip_modules
self._init_skip_modules() self._init_skip_modules()
self.downsample_output = AttentionDownsample(encoder_dim[-1], self.downsample_output = SimpleDownsample(encoder_dim[-1],
encoder_dim[-1], encoder_dim[-1],
downsample=output_downsampling_factor, downsample=output_downsampling_factor,
dropout=dropout) dropout=dropout)
@ -677,7 +677,7 @@ class DownsampledZipformerEncoder(nn.Module):
dropout: FloatLike): dropout: FloatLike):
super(DownsampledZipformerEncoder, self).__init__() super(DownsampledZipformerEncoder, self).__init__()
self.downsample_factor = downsample self.downsample_factor = downsample
self.downsample = AttentionDownsample(input_dim, output_dim, self.downsample = SimpleDownsample(input_dim, output_dim,
downsample, dropout) downsample, dropout)
self.encoder = encoder self.encoder = encoder
self.upsample = SimpleUpsample(output_dim, downsample) self.upsample = SimpleUpsample(output_dim, downsample)
@ -741,7 +741,7 @@ class DownsamplingZipformerEncoder(nn.Module):
downsample: int): downsample: int):
super(DownsampledZipformerEncoder, self).__init__() super(DownsampledZipformerEncoder, self).__init__()
self.downsample_factor = downsample self.downsample_factor = downsample
self.downsample = AttentionDownsample(input_dim, output_dim, downsample) self.downsample = SimpleDownsample(input_dim, output_dim, downsample)
self.encoder = encoder self.encoder = encoder
@ -785,7 +785,7 @@ class DownsamplingZipformerEncoder(nn.Module):
return src return src
class AttentionDownsample(torch.nn.Module): class SimpleDownsample(torch.nn.Module):
""" """
Does downsampling with attention, by weighted sum, and a projection.. Does downsampling with attention, by weighted sum, and a projection..
""" """
@ -797,7 +797,7 @@ class AttentionDownsample(torch.nn.Module):
""" """
Require out_channels > in_channels. Require out_channels > in_channels.
""" """
super(AttentionDownsample, self).__init__() super(SimpleDownsample, self).__init__()
self.bias = nn.Parameter(torch.zeros(downsample)) self.bias = nn.Parameter(torch.zeros(downsample))