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Modify feature_mask_dropout_prob

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Daniel Povey 2023-03-31 13:25:39 +08:00
parent e64ec396bd
commit d41b73000e
1 changed files with 5 additions and 6 deletions
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11
egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
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@ -297,21 +297,20 @@ class Zipformer2(EncoderInterface):
num_frames_max = (num_frames0 + max_downsampling_factor - 1) num_frames_max = (num_frames0 + max_downsampling_factor - 1)
# we divide the dropped-out feature dimensions into two equal groups; # we divide the dropped-out feature dimensions into two equal groups;
# the first group is dropped out with probability 0.05, the second # the first group is dropped out with probability 0.1, the second
# with probability approximately (0.2 + 0.05). # with probability approximately twice that.
feature_mask_dropout_prob1 = 0.05 feature_mask_dropout_prob = 0.1
feature_mask_dropout_prob2 = 0.2
# frame_mask_max1 shape: (num_frames_max, batch_size, 1) # frame_mask_max1 shape: (num_frames_max, batch_size, 1)
frame_mask_max1 = (torch.rand(num_frames_max, batch_size, 1, frame_mask_max1 = (torch.rand(num_frames_max, batch_size, 1,
device=x.device) > device=x.device) >
feature_mask_dropout_prob1).to(x.dtype) feature_mask_dropout_prob).to(x.dtype)
# frame_mask_max2 has additional frames masked, about twice the number. # frame_mask_max2 has additional frames masked, about twice the number.
frame_mask_max2 = torch.logical_and(frame_mask_max1, frame_mask_max2 = torch.logical_and(frame_mask_max1,
(torch.rand(num_frames_max, batch_size, 1, (torch.rand(num_frames_max, batch_size, 1,
device=x.device) > device=x.device) >
feature_mask_dropout_prob2).to(x.dtype)) feature_mask_dropout_prob).to(x.dtype))
# dim: (num_frames_max, batch_size, 3) # dim: (num_frames_max, batch_size, 3)