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Remove unused code LearnedScale.

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This commit is contained in:
Daniel Povey 2022-10-09 16:07:31 +08:00
parent cf450908c6
commit 00841f0f49
2 changed files with 0 additions and 25 deletions
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1
egs/librispeech/ASR/pruned_transducer_stateless7/conformer.py
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@ -29,7 +29,6 @@ from s import (
DoubleSwish,
ScaledConv1d,
ScaledLinear, # not as in other dirs.. just scales down initial parameter values.
LearnedScale,
)
from torch import Tensor, nn

24
egs/librispeech/ASR/pruned_transducer_stateless7/scaling.py
View File

@ -326,30 +326,6 @@ def ScaledConv1d(*args,
return ans
class LearnedScale(torch.nn.Module):
"""
Module that learns a scale dependent on some kind of mask that is typically going to be 0 or 1
in training. The scale will be 1.0 if the mask is 1.0, but may be a different (learned) value
if the mask value is not 1.0.
The idea is that if we have some kind of feature mask that would always be 1.0 in
test mode but might sometimes be 0.0 in training mode, we might want the multiply
the remaining features by a value dependent on this mask.
"""
def __init__(self):
super(LearnedScale, self).__init__()
self.alpha = nn.Parameter(torch.tensor(0.0))
def forward(self,
x: Tensor,
mask: Tensor):
"""
Mask should either be a number (probably 1.0) or a tensors that broadcasts with x.
"""
if self.training and mask is 1.0:
return x
return x * (1.0 + self.alpha * (1.0 - mask))
class ActivationBalancer(torch.nn.Module):
"""