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| author | AUTOMATIC1111 <16777216c@gmail.com> | 2022-10-30 09:29:29 +0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2022-10-30 09:29:29 +0300 |
| commit | 3dc9a43f7eb779c41cd0c61e35aedc4c5635c338 (patch) | |
| tree | 5bd572b645c9ff70cde5cc33b429225618181f29 /modules/textual_inversion | |
| parent | 5612d03016d2f675fc64eb04ed1e649bbba813a5 (diff) | |
| parent | ef4c94e1cfe66299227aa95a28c2380d21cb1600 (diff) | |
Merge pull request #3898 from R-N/lr-comma
Allow trailing comma in learning rate
Diffstat (limited to 'modules/textual_inversion')
| -rw-r--r-- | modules/textual_inversion/learn_schedule.py | 35 |
1 files changed, 21 insertions, 14 deletions
diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py index 3a736065..dd0c0ad1 100644 --- a/modules/textual_inversion/learn_schedule.py +++ b/modules/textual_inversion/learn_schedule.py @@ -4,30 +4,37 @@ import tqdm class LearnScheduleIterator:
def __init__(self, learn_rate, max_steps, cur_step=0):
"""
- specify learn_rate as "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, 1e-5:10000 until 10000
+ specify learn_rate as "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, and 1e-5 until 10000
"""
pairs = learn_rate.split(',')
self.rates = []
self.it = 0
self.maxit = 0
- for i, pair in enumerate(pairs):
- tmp = pair.split(':')
- if len(tmp) == 2:
- step = int(tmp[1])
- if step > cur_step:
- self.rates.append((float(tmp[0]), min(step, max_steps)))
- self.maxit += 1
- if step > max_steps:
+ try:
+ for i, pair in enumerate(pairs):
+ if not pair.strip():
+ continue
+ tmp = pair.split(':')
+ if len(tmp) == 2:
+ step = int(tmp[1])
+ if step > cur_step:
+ self.rates.append((float(tmp[0]), min(step, max_steps)))
+ self.maxit += 1
+ if step > max_steps:
+ return
+ elif step == -1:
+ self.rates.append((float(tmp[0]), max_steps))
+ self.maxit += 1
return
- elif step == -1:
+ else:
self.rates.append((float(tmp[0]), max_steps))
self.maxit += 1
return
- else:
- self.rates.append((float(tmp[0]), max_steps))
- self.maxit += 1
- return
+ assert self.rates
+ except (ValueError, AssertionError):
+ raise Exception('Invalid learning rate schedule. It should be a number or, for example, like "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, and 1e-5 until 10000.')
+
def __iter__(self):
return self
|