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Apply reverse_cutoff with param_pow, to make it not too strong.

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This commit is contained in:
Daniel Povey 2022-06-26 11:07:08 +08:00
parent 0aa5a334d6
commit 0b811546f3
1 changed files with 3 additions and 3 deletions
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6
egs/librispeech/ASR/pruned_transducer_stateless7/optim.py
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@ -98,7 +98,7 @@ class NeutralGradient(Optimizer):
param_eps=1.0e-06,
param_rel_eps=1.0e-04,
param_rel_max=1.0,
param_reverse_cutoff=16.0,
param_reverse_cutoff=4.0,
param_max_rms=2.0,
param_min_rms=1.0e-05,
max_fullcov_size=1023,
@ -863,8 +863,8 @@ class NeutralGradient(Optimizer):
# 2nd factor below becomes a 1/param_diag type of function when
# param_diag >> param_reverse_cutoff.
ans = (ans ** param_pow) * (param_reverse_cutoff / (param_diag + param_reverse_cutoff))
return ans
ans = ans * (param_reverse_cutoff / (param_diag + param_reverse_cutoff))
return ans ** param_pow
def _estimate_proj(self,