Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -167,14 +167,11 @@ def generate_60(
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num_images: int = 1,
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progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
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):
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torch.set_default_device('cuda')
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global models
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pipe = models[model_choice]
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seed = int(randomize_seed_fn(seed, randomize_seed))
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generator = torch.Generator(device='
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prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
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options = {
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"prompt": [prompt] * num_images,
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"negative_prompt": [negative_prompt] * num_images if use_negative_prompt else None,
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@@ -185,10 +182,8 @@ def generate_60(
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"generator": generator,
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"output_type": "pil",
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}
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if use_resolution_binning:
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options["use_resolution_binning"] = True
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images = []
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with torch.no_grad():
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for i in range(0, num_images, BATCH_SIZE):
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@@ -205,7 +200,6 @@ def generate_60(
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gc.collect()
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return image_paths, seed
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@spaces.GPU(duration=90)
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def generate_90(
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model_choice: str,
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@@ -226,10 +220,8 @@ def generate_90(
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global models
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pipe = models[model_choice]
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seed = int(randomize_seed_fn(seed, randomize_seed))
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generator = torch.Generator(device='
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prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
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options = {
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"prompt": [prompt] * num_images,
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"negative_prompt": [negative_prompt] * num_images if use_negative_prompt else None,
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@@ -240,10 +232,8 @@ def generate_90(
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"generator": generator,
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"output_type": "pil",
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}
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if use_resolution_binning:
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options["use_resolution_binning"] = True
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images = []
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with torch.no_grad():
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for i in range(0, num_images, BATCH_SIZE):
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@@ -274,23 +264,7 @@ def load_predefined_images1():
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]
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return predefined_images1
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# def load_predefined_images():
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# predefined_images = [
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# "assets2/11.png",
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# "assets2/22.png",
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# "assets2/33.png",
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# "assets2/44.png",
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# "assets2/55.png",
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# "assets2/66.png",
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# "assets2/77.png",
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# "assets2/88.png",
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# "assets2/99.png",
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# ]
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# return predefined_image
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with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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gr.Markdown(DESCRIPTIONXX)
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with gr.Row():
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prompt = gr.Text(
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num_images: int = 1,
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progress=gr.Progress(track_tqdm=True) # Add progress as a keyword argument
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):
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global models
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pipe = models[model_choice]
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seed = int(randomize_seed_fn(seed, randomize_seed))
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generator = torch.Generator(device='cpu').manual_seed(seed)
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prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
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options = {
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"prompt": [prompt] * num_images,
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"negative_prompt": [negative_prompt] * num_images if use_negative_prompt else None,
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"generator": generator,
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"output_type": "pil",
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}
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if use_resolution_binning:
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options["use_resolution_binning"] = True
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images = []
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with torch.no_grad():
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for i in range(0, num_images, BATCH_SIZE):
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gc.collect()
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return image_paths, seed
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@spaces.GPU(duration=90)
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def generate_90(
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model_choice: str,
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global models
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pipe = models[model_choice]
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seed = int(randomize_seed_fn(seed, randomize_seed))
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generator = torch.Generator(device='cpu').manual_seed(seed)
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prompt, negative_prompt = apply_style(style_selection, prompt, negative_prompt)
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options = {
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"prompt": [prompt] * num_images,
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"negative_prompt": [negative_prompt] * num_images if use_negative_prompt else None,
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"generator": generator,
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"output_type": "pil",
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}
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if use_resolution_binning:
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options["use_resolution_binning"] = True
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images = []
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with torch.no_grad():
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for i in range(0, num_images, BATCH_SIZE):
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]
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return predefined_images1
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with gr.Blocks(css=css) as demo:
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gr.Markdown(DESCRIPTIONXX)
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with gr.Row():
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prompt = gr.Text(
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