mirrors/icefall
1
0
Fork 0
mirror of https://github.com/k2-fsa/icefall.git synced 2025-09-19 05:54:20 +00:00
Code Issues Packages Projects Releases Wiki Activity

Reduce debug freq

Browse Source
This commit is contained in:
Daniel Povey 2022-07-13 06:51:23 +08:00
parent d48fe0b99c
commit 4785245e5c
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
egs/librispeech/ASR/pruned_transducer_stateless7/optim.py
View File

@ -592,7 +592,7 @@ param_rms_smooth1: Smoothing proportion for parameter matrix, if assumed rank of
# (where the stats permit). # (where the stats permit).
scale = (S.clamp(min=eps) / cur_param_var.clamp(min=eps)).sqrt() scale = (S.clamp(min=eps) / cur_param_var.clamp(min=eps)).sqrt()
if random.random() < 0.01: if random.random() < 0.001:
logging.info(f"shape={p.shape}, dim={dim}, scale={scale[0].flatten()[::10]}, cur_param_var={cur_param_var[0].flatten()[::10]}, S={S[0].flatten()[::10]}") logging.info(f"shape={p.shape}, dim={dim}, scale={scale[0].flatten()[::10]}, cur_param_var={cur_param_var[0].flatten()[::10]}, S={S[0].flatten()[::10]}")
# scale shape: (batch_size, 1, size, 1, 1) # scale shape: (batch_size, 1, size, 1, 1)
@ -619,7 +619,7 @@ param_rms_smooth1: Smoothing proportion for parameter matrix, if assumed rank of
# cur_scales for the other dims. # cur_scales for the other dims.
cur_scales = [None] * ndim cur_scales = [None] * ndim
debug = True #(random.random() < 0.001) debug = (random.random() < 0.001)
for i in range(4): # for 4 iterations (this is quite arbitrary) for i in range(4): # for 4 iterations (this is quite arbitrary)
for dim in range(1, ndim): for dim in range(1, ndim):
size = p.shape[dim] size = p.shape[dim]