Spaces:
Running
on
Zero
Running
on
Zero
yucornetto
commited on
Commit
•
15a2a80
1
Parent(s):
995325f
Update app.py
Browse files
app.py
CHANGED
@@ -10,9 +10,7 @@ import argparse
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import demo_util
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import os
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import spaces
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model2ckpt = {
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"TiTok-L-32": ("tokenizer_titok_l32.bin", "generator_titok_l32.bin"),
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@@ -32,19 +30,24 @@ parser.add_argument("--seed", type=int, default=42)
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parser.add_argument("--temperature", type=float, default=1.0, help="temperature value to sample with")
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args = parser.parse_args()
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config = demo_util.get_config("configs/titok_l32.yaml")
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print(config)
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titok_tokenizer = demo_util.get_titok_tokenizer(config)
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print(titok_tokenizer)
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titok_generator = demo_util.get_titok_generator(config)
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print(titok_generator)
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@spaces.GPU
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def
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generator,
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guidance_scale, randomize_temperature, num_sample_steps,
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class_label, seed):
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@@ -70,7 +73,8 @@ def demo_infer(tokenizer,
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samples = [Image.fromarray(sample) for sample in generated_image]
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return samples
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with gr.Blocks() as demo:
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gr.Markdown("<h1 style='text-align: center'>An Image is Worth 32 Tokens for Reconstruction and Generation</h1>")
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@@ -92,7 +96,6 @@ with gr.Blocks() as demo:
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with gr.Column():
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output = gr.Gallery(label='Generated Images', height=700)
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button.click(demo_infer, inputs=[
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titok_tokenizer, titok_generator,
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guidance_scale, randomize_temperature, num_sample_steps,
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i1k_class, seed],
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outputs=[output])
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import demo_util
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import os
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import spaces
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from functools import partial
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model2ckpt = {
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"TiTok-L-32": ("tokenizer_titok_l32.bin", "generator_titok_l32.bin"),
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parser.add_argument("--temperature", type=float, default=1.0, help="temperature value to sample with")
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args = parser.parse_args()
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@spaces.GPU
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def load_model():
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device = "cuda" if torch.cuda.is_available() else "cpu"
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config = demo_util.get_config("configs/titok_l32.yaml")
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print(config)
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titok_tokenizer = demo_util.get_titok_tokenizer(config)
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print(titok_tokenizer)
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titok_generator = demo_util.get_titok_generator(config)
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print(titok_generator)
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titok_tokenizer = titok_tokenizer.to(device)
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titok_generator = titok_generator.to(device)
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return titok_tokenizer, titok_generator
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@spaces.GPU
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def demo_infer_(tokenizer,
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generator,
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guidance_scale, randomize_temperature, num_sample_steps,
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class_label, seed):
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samples = [Image.fromarray(sample) for sample in generated_image]
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return samples
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titok_tokenizer, titok_generator = load_model()
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demo_infer = partial(demo_infer_, tokenizer=titok_tokenizer, generator=titok_generator)
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with gr.Blocks() as demo:
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gr.Markdown("<h1 style='text-align: center'>An Image is Worth 32 Tokens for Reconstruction and Generation</h1>")
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with gr.Column():
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output = gr.Gallery(label='Generated Images', height=700)
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button.click(demo_infer, inputs=[
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guidance_scale, randomize_temperature, num_sample_steps,
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i1k_class, seed],
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outputs=[output])
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