aljaz/DALLE2-pytorch
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@jacobwjs reports dynamic thresholding works very well and 0.95 is a better value

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Phil Wang
2022-07-19 11:31:56 -07:00
parent 7f120a8b56
commit 291377bb9c
2 changed files with 2 additions and 2 deletions
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2
dalle2_pytorch/dalle2_pytorch.py
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@@ -2115,7 +2115,7 @@ class Decoder(nn.Module):
unconditional = False, # set to True for generating images without conditioning
auto_normalize_img = True, # whether to take care of normalizing the image from [0, 1] to [-1, 1] and back automatically - you can turn this off if you want to pass in the [-1, 1] ranged image yourself from the dataloader
use_dynamic_thres = False, # from the Imagen paper
dynamic_thres_percentile = 0.9,
dynamic_thres_percentile = 0.95,
p2_loss_weight_gamma = 0., # p2 loss weight, from https://arxiv.org/abs/2204.00227 - 0 is equivalent to weight of 1 across time - 1. is recommended
p2_loss_weight_k = 1,
ddim_sampling_eta = 1. # can be set to 0. for deterministic sampling afaict

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dalle2_pytorch/version.py
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@@ -1 +1 @@
__version__ = '0.26.0'
__version__ = '0.26.1'