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import torch | |
STYLESPACE_DIMENSIONS = [512 for _ in range(15)] + [256, 256, 256] + [128, 128, 128] + [64, 64, 64] + [32, 32] | |
TORGB_INDICES = list(range(1, len(STYLESPACE_DIMENSIONS), 3)) | |
STYLESPACE_INDICES_WITHOUT_TORGB = [i for i in range(len(STYLESPACE_DIMENSIONS)) if i not in TORGB_INDICES][:11] | |
def features_channels_to_s(s_without_torgb, s_std, device='cuda'): | |
s = [] | |
start_index_features = 0 | |
for c in range(len(STYLESPACE_DIMENSIONS)): | |
if c in STYLESPACE_INDICES_WITHOUT_TORGB: | |
end_index_features = start_index_features + STYLESPACE_DIMENSIONS[c] | |
s_i = s_without_torgb[start_index_features:end_index_features] * s_std[c] | |
start_index_features = end_index_features | |
else: | |
s_i = torch.zeros(STYLESPACE_DIMENSIONS[c]).to(device) | |
s_i = s_i.view(1, 1, -1, 1, 1) | |
s.append(s_i) | |
return s |