Remove unused variable

This commit is contained in:
Daniel Povey 2023-05-18 14:17:31 +08:00
parent a514d23df7
commit e976af699e

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@ -805,17 +805,11 @@ class LearnedDownsamplingModule(nn.Module):
downsampling_factor: factor to downsample by, e.g. 2 or 4. There is no downsampling_factor: factor to downsample by, e.g. 2 or 4. There is no
fundamental reason why this has to be an integer, but we make it so fundamental reason why this has to be an integer, but we make it so
anyway. anyway.
intermediate_rate: the proportion of the downsampled values that have
"intermediate weights"- between kept and downsampled. The user is
supposed to use these in such a way that if the weight we return is
0.0, it's equivalent to not using this frame at all.
""" """
def __init__(self, def __init__(self,
embed_dim: int, embed_dim: int,
downsampling_factor: int, downsampling_factor: int):
intermediate_rate: Optional[FloatLike] = ScheduledFloat((0.0, 0.5),
(4000.0, 0.2),
default=0.5)):
super().__init__() super().__init__()
self.to_scores = nn.Linear(embed_dim, 1, bias=False) self.to_scores = nn.Linear(embed_dim, 1, bias=False)
@ -833,7 +827,6 @@ class LearnedDownsamplingModule(nn.Module):
self.copy_weights2 = nn.Identity() self.copy_weights2 = nn.Identity()
self.downsampling_factor = downsampling_factor self.downsampling_factor = downsampling_factor
self.intermediate_rate = copy.deepcopy(intermediate_rate)
def forward(self, def forward(self,