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| author | AUTOMATIC <16777216c@gmail.com> | 2022-09-18 09:09:34 +0300 |
|---|---|---|
| committer | AUTOMATIC <16777216c@gmail.com> | 2022-09-18 09:09:34 +0300 |
| commit | 7e77938230d4fefb6edccdba0b80b61d8416673e (patch) | |
| tree | c49e697e7d6cc97d8ddea8472116cc77c7a36a4a /modules | |
| parent | 9f9a2084c7679e6b022f91432ed004701cb09638 (diff) | |
| parent | c89b1a6f3dde245fe0130d7e957362248e3d979b (diff) | |
Merge remote-tracking branch 'origin/master'
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/processing.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/modules/processing.py b/modules/processing.py index a60dec24..147d64e3 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -124,7 +124,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see # if we have multiple seeds, this means we are working with batch size>1; this then
# enables the generation of additional tensors with noise that the sampler will use during its processing.
- # Using those pre-genrated tensors instead of siimple torch.randn allows a batch with seeds [100, 101] to
+ # Using those pre-generated tensors instead of simple torch.randn allows a batch with seeds [100, 101] to
# produce the same images as with two batches [100], [101].
if p is not None and p.sampler is not None and len(seeds) > 1 and opts.enable_batch_seeds:
sampler_noises = [[] for _ in range(p.sampler.number_of_needed_noises(p))]
|