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Update app.py
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app.py
CHANGED
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@@ -21,7 +21,7 @@ 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"
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MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1536"))
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USE_TORCH_COMPILE =
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ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
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PREVIEW_IMAGES = False #not working for now
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@@ -41,12 +41,7 @@ if torch.cuda.is_available():
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if USE_TORCH_COMPILE:
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prior_pipeline.prior = torch.compile(prior_pipeline.prior, mode="max-autotune", fullgraph=True)
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decoder_pipeline.decoder = torch.compile(decoder_pipeline.decoder, mode="max-autotune", fullgraph=True)
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torch._inductor.config.coordinate_descent_tuning = True
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torch._inductor.config.epilogue_fusion = False
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torch._inductor.config.coordinate_descent_check_all_directions = True
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prior_pipeline.prior.to(memory_format=torch.channels_last)
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decoder_pipeline.decoder.to(memory_format=torch.channels_last)
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if PREVIEW_IMAGES:
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pass
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# previewer = Previewer()
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@@ -198,7 +193,7 @@ with gr.Blocks() as demo:
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minimum=1,
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maximum=2,
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step=1,
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value=
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)
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with gr.Row():
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prior_guidance_scale = gr.Slider(
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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"
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MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "1536"))
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USE_TORCH_COMPILE = False
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ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
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PREVIEW_IMAGES = False #not working for now
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if USE_TORCH_COMPILE:
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prior_pipeline.prior = torch.compile(prior_pipeline.prior, mode="max-autotune", fullgraph=True)
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decoder_pipeline.decoder = torch.compile(decoder_pipeline.decoder, mode="max-autotune", fullgraph=True)
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if PREVIEW_IMAGES:
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pass
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# previewer = Previewer()
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minimum=1,
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maximum=2,
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step=1,
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value=1,
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)
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with gr.Row():
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prior_guidance_scale = gr.Slider(
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