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Mess with thresholds for printing

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This commit is contained in:
Daniel Povey 2022-04-26 10:39:35 +08:00
parent 3ba081e6d9
commit eba025a6b4
1 changed files with 2 additions and 2 deletions
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egs/librispeech/ASR/pruned2_knowledge/sampling.py
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@ -729,7 +729,7 @@ class SampleCombinedFunction(torch.autograd.Function):
@staticmethod @staticmethod
@custom_fwd @custom_fwd
def forward(ctx, p: Tensor, K: int, input_is_log: bool) -> Tuple[Tensor, Tensor]: def forward(ctx, p: Tensor, K: int, input_is_log: bool) -> Tuple[Tensor, Tensor]:
if random.random() < 0.0005: if random.random() < 0.001:
print("dtype[1] = ", p.dtype) print("dtype[1] = ", p.dtype)
with torch.no_grad(): with torch.no_grad():
weights, indexes = sample_combined_forward(p, K, input_is_log) weights, indexes = sample_combined_forward(p, K, input_is_log)
@ -892,7 +892,7 @@ class WeightedMatrixLookupFunction(torch.autograd.Function):
tensor of shape (*, D), containing weighted sums of rows of tensor of shape (*, D), containing weighted sums of rows of
`knowledge_base` `knowledge_base`
""" """
if random.random() < 0.0005: if random.random() < 0.001:
print("dtype[1] = ", weights.dtype) print("dtype[1] = ", weights.dtype)
ctx.save_for_backward(weights.detach(), indexes.detach(), ctx.save_for_backward(weights.detach(), indexes.detach(),
knowledge_base.detach()) knowledge_base.detach())