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Remove logging that was excessive

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This commit is contained in:
Daniel Povey 2022-06-10 14:25:23 +08:00
parent ff0309947a
commit c6cfb1e5fa
1 changed files with 8 additions and 0 deletions
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egs/librispeech/ASR/pruned_transducer_stateless2/scaling.py
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@ -820,11 +820,18 @@ class DecorrelateFunction(torch.autograd.Function):
x_grad_old_sqnorm = (x_grad ** 2).sum(dim=1)
x_sqnorm = (x.detach() ** 2).sum(dim=1)
x_desired_sqscale = x_grad_old_sqnorm ** 0.5 # desired scale of x in sum for cov
x_desired_sqscale /= (x_desired_sqscale.sum() + 1.0e-20) # sum-to-one scales
x_desired_sqscale_is_inf = (x_desired_sqscale - x_desired_sqscale != 0)
# if grads are inf, use equal scales for frames (can happen due to GradScaler, in half
# precision)
x_desired_sqscale.masked_fill_(x_desired_sqscale_is_inf, 1.0 / x_desired_sqscale.numel())
x_factor = (x_desired_sqscale / (x_sqnorm + ctx.eps)) ** 0.5
with torch.enable_grad():
scaled_x = x * x_factor.unsqueeze(-1)
cov = _update_cov_stats(old_cov, scaled_x, ctx.beta)
assert old_cov.dtype != torch.float16
old_cov[:] = cov # update the stats outside! This is not really
# how backprop is supposed to work, but this input
# is not differentiable..
@ -832,6 +839,7 @@ class DecorrelateFunction(torch.autograd.Function):
if random.random() < 0.01:
logging.info(f"Decorrelate: loss = {loss}")
loss.backward()
decorr_x_grad = x.grad