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add a bit of a comment about what's being done with tensor noise

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AUTOMATIC 2022-09-16 10:04:07 +03:00
parent 83bce1a604
commit b8cf2ea8ea
1 changed files with 4 additions and 0 deletions
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modules/processing.py
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@ -122,6 +122,10 @@ def slerp(val, low, high):
def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, p=None): def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, p=None):
xs = [] xs = []
# 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
# 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: 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))] sampler_noises = [[] for _ in range(p.sampler.number_of_needed_noises(p))]
else: else: