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c7d725d
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Parent(s):
8947670
speed up demo
Browse files- README.md +1 -2
- app.py +7 -3
- requirements.txt +7 -4
README.md
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@@ -4,10 +4,9 @@ emoji: 👀
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colorFrom: pink
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colorTo: purple
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned: false
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license: agpl-3.0
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---
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Inference Code: https://github.com/PixArt-alpha/PixArt-alpha
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colorFrom: pink
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colorTo: purple
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sdk: gradio
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sdk_version: 4.1.1
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app_file: app.py
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pinned: false
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---
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Inference Code: https://github.com/PixArt-alpha/PixArt-alpha
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app.py
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@@ -22,7 +22,7 @@ if not torch.cuda.is_available():
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MAX_SEED = np.iinfo(np.int32).max
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CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "1") == "1"
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MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1024"))
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USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "
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ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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pipe = PixArtAlphaPipeline.from_pretrained(
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"PixArt-alpha/PixArt-XL-2-1024-MS",
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torch_dtype=torch.float16,
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use_safetensors=True,
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)
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@@ -105,6 +106,9 @@ if torch.cuda.is_available():
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pipe.to(device)
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print("Loaded on Device!")
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if USE_TORCH_COMPILE:
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pipe.transformer = torch.compile(
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pipe.transformer, mode="reduce-overhead", fullgraph=True
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@@ -254,7 +258,6 @@ with gr.Blocks(css="style.css") as demo:
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fn=lambda x: gr.update(visible=x),
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inputs=use_negative_prompt,
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outputs=negative_prompt,
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queue=False,
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api_name=False,
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)
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@@ -282,4 +285,5 @@ with gr.Blocks(css="style.css") as demo:
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)
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if __name__ == "__main__":
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demo.queue(max_size=20).launch()
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MAX_SEED = np.iinfo(np.int32).max
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CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "1") == "1"
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MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1024"))
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USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
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ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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pipe = PixArtAlphaPipeline.from_pretrained(
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"PixArt-alpha/PixArt-XL-2-1024-MS",
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torch_dtype=torch.float16,
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variant="fp16",
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use_safetensors=True,
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)
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pipe.to(device)
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print("Loaded on Device!")
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# speed-up T5
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pipe.text_encoder.to_bettertransformer()
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if USE_TORCH_COMPILE:
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pipe.transformer = torch.compile(
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pipe.transformer, mode="reduce-overhead", fullgraph=True
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fn=lambda x: gr.update(visible=x),
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inputs=use_negative_prompt,
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outputs=negative_prompt,
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api_name=False,
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)
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)
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if __name__ == "__main__":
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# demo.queue(max_size=20).launch()
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demo.launch(share=True)
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requirements.txt
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@@ -1,7 +1,10 @@
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-
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gradio==4.1.1
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Pillow==10.1.0
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torch==2.0.1
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transformers==4.35.0
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sentencepiece==0.1.99
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--index-url https://download.pytorch.org/whl/cu118
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torch==2.0.1
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diffusers==0.22.1
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accelerate
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transformers
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gradio==4.1.1
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Pillow==10.1.0
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sentencepiece==0.1.99
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