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Update app.py
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app.py
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@@ -1,9 +1,39 @@
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import gradio as gr
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import spaces
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import torch
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from diffusers import Cosmos2TextToImagePipeline, EDMEulerScheduler
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import random
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model_2b_id = "nvidia/Cosmos-Predict2-2B-Text2Image"
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pipe_2b = Cosmos2TextToImagePipeline.from_pretrained(
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import subprocess
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subprocess.run(
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"pip install flash-attn --no-build-isolation", env={"FLASH_ATTENTION_SKIP_CUDA_BUILD": "TRUE"}, shell=True
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)
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import gradio as gr
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import spaces
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import torch
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from diffusers import Cosmos2TextToImagePipeline, EDMEulerScheduler
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from transformers import AutoModelForCausalLM, SiglipProcessor
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import random
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#Add flash_attention_2 to the safeguard model
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def patch_from_pretrained(cls):
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orig_method = cls.from_pretrained
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def new_from_pretrained(*args, **kwargs):
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kwargs.setdefault("attn_implementation", "flash_attention_2")
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kwargs.setdefault("torch_dtype", torch.bfloat16)
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return orig_method(*args, **kwargs)
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cls.from_pretrained = new_from_pretrained
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patch_from_pretrained(AutoModelForCausalLM)
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#Add a `use_fast` to the safeguard image processor
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def patch_processor_fast(cls):
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orig_method = cls.from_pretrained
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def new_from_pretrained(*args, **kwargs):
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kwargs.setdefault("use_fast", True)
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return orig_method(*args, **kwargs)
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cls.from_pretrained = new_from_pretrained
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patch_processor_fast(SiglipProcessor)
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model_2b_id = "nvidia/Cosmos-Predict2-2B-Text2Image"
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pipe_2b = Cosmos2TextToImagePipeline.from_pretrained(
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