wangshuai6 commited on
Commit
7979f94
·
1 Parent(s): 9772775
Files changed (1) hide show
  1. app.py +3 -5
app.py CHANGED
@@ -82,7 +82,7 @@ class Pipeline:
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  @spaces.GPU
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  @torch.no_grad()
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  @torch.autocast(device_type="cuda", dtype=torch.bfloat16)
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- def __call__(self, y, num_images, seed, image_height, image_width, num_steps, guidance, timeshift, order):
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  diffusion_sampler = AdamLMSampler(
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  order=order,
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  scheduler=LinearScheduler(),
@@ -96,10 +96,10 @@ class Pipeline:
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  image_width = image_width // 32 * 32
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  self.denoiser.decoder_patch_scaling_h = image_height / 512
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  self.denoiser.decoder_patch_scaling_w = image_width / 512
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- xT = torch.randn((num_images, 3, image_height, image_width), device="cpu", dtype=torch.float32,
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  generator=generator).cuda()
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  with torch.no_grad():
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- condition, uncondition = conditioner([y,]*num_images)
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  # Sample images:
@@ -182,7 +182,6 @@ if __name__ == "__main__":
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  guidance = gr.Slider(minimum=0.1, maximum=10.0, step=0.1, label="CFG", value=4.0)
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  image_height = gr.Slider(minimum=128, maximum=1024, step=32, label="image height", value=512)
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  image_width = gr.Slider(minimum=128, maximum=1024, step=32, label="image width", value=512)
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- num_images = gr.Slider(minimum=1, maximum=4, step=1, label="num images", value=4)
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  label = gr.Textbox(label="positive prompt", value="a photo of a cat")
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  seed = gr.Slider(minimum=0, maximum=1000000, step=1, label="seed", value=0)
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  timeshift = gr.Slider(minimum=0.1, maximum=5.0, step=0.1, label="timeshift", value=3.0)
@@ -196,7 +195,6 @@ if __name__ == "__main__":
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  btn.click(fn=pipeline,
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  inputs=[
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  label,
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- num_images,
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  seed,
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  image_height,
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  image_width,
 
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  @spaces.GPU
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  @torch.no_grad()
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  @torch.autocast(device_type="cuda", dtype=torch.bfloat16)
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+ def __call__(self, y, seed, image_height, image_width, num_steps, guidance, timeshift, order):
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  diffusion_sampler = AdamLMSampler(
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  order=order,
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  scheduler=LinearScheduler(),
 
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  image_width = image_width // 32 * 32
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  self.denoiser.decoder_patch_scaling_h = image_height / 512
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  self.denoiser.decoder_patch_scaling_w = image_width / 512
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+ xT = torch.randn((1, 3, image_height, image_width), device="cpu", dtype=torch.float32,
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  generator=generator).cuda()
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  with torch.no_grad():
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+ condition, uncondition = conditioner([y,]*1)
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  # Sample images:
 
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  guidance = gr.Slider(minimum=0.1, maximum=10.0, step=0.1, label="CFG", value=4.0)
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  image_height = gr.Slider(minimum=128, maximum=1024, step=32, label="image height", value=512)
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  image_width = gr.Slider(minimum=128, maximum=1024, step=32, label="image width", value=512)
 
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  label = gr.Textbox(label="positive prompt", value="a photo of a cat")
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  seed = gr.Slider(minimum=0, maximum=1000000, step=1, label="seed", value=0)
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  timeshift = gr.Slider(minimum=0.1, maximum=5.0, step=0.1, label="timeshift", value=3.0)
 
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  btn.click(fn=pipeline,
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  inputs=[
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  label,
 
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  seed,
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  image_height,
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  image_width,