Spaces:
Running
on
Zero
Running
on
Zero
increase speed (test)
Browse files
app.py
CHANGED
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@@ -7,10 +7,8 @@ import numpy as np
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import torch
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from PIL import Image
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from diffusers import DiffusionPipeline, StableDiffusionXLPipeline, EDMEulerScheduler, StableDiffusionXLInstructPix2PixPipeline, AutoencoderKL
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from custom_pipeline import CosStableDiffusionXLInstructPix2PixPipeline
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from huggingface_hub import hf_hub_download
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from huggingface_hub import InferenceClient
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from diffusers import StableDiffusion3Pipeline, SD3Transformer2DModel, FlowMatchEulerDiscreteScheduler
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device = "cuda" if torch.cuda.is_available() else "cpu"
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dtype = torch.float16
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@@ -51,9 +49,7 @@ def set_timesteps_patched(self, num_inference_steps: int, device = None):
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# Image Editor
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edit_file = hf_hub_download(repo_id="stabilityai/cosxl", filename="cosxl_edit.safetensors")
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EDMEulerScheduler.set_timesteps = set_timesteps_patched
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pipe_edit = StableDiffusionXLInstructPix2PixPipeline.from_single_file(
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edit_file, num_in_channels=8, is_cosxl_edit=True, vae=vae, torch_dtype=torch.float16,
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)
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pipe_edit.scheduler = EDMEulerScheduler(sigma_min=0.002, sigma_max=120.0, sigma_data=1.0, prediction_type="v_prediction")
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pipe_edit.to("cuda")
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@@ -103,8 +99,8 @@ def king(type ,
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prompt = instruction,
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guidance_scale = guidance_scale,
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num_inference_steps = steps,
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width = width,
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height = height,
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generator = generator,
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output_type="latent",
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).images
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@@ -113,6 +109,8 @@ def king(type ,
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prompt=instruction,
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guidance_scale=guidance_scale,
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num_inference_steps=steps,
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image=image,
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generator=generator,
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).images[0]
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import torch
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from PIL import Image
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from diffusers import DiffusionPipeline, StableDiffusionXLPipeline, EDMEulerScheduler, StableDiffusionXLInstructPix2PixPipeline, AutoencoderKL
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from huggingface_hub import hf_hub_download
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from huggingface_hub import InferenceClient
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device = "cuda" if torch.cuda.is_available() else "cpu"
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dtype = torch.float16
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# Image Editor
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edit_file = hf_hub_download(repo_id="stabilityai/cosxl", filename="cosxl_edit.safetensors")
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EDMEulerScheduler.set_timesteps = set_timesteps_patched
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pipe_edit = StableDiffusionXLInstructPix2PixPipeline.from_single_file( edit_file, num_in_channels=8, is_cosxl_edit=True, vae=vae, torch_dtype=torch.float16 )
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pipe_edit.scheduler = EDMEulerScheduler(sigma_min=0.002, sigma_max=120.0, sigma_data=1.0, prediction_type="v_prediction")
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pipe_edit.to("cuda")
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prompt = instruction,
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guidance_scale = guidance_scale,
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num_inference_steps = steps,
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width = (width/2),
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height = (height/2),
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generator = generator,
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output_type="latent",
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).images
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prompt=instruction,
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guidance_scale=guidance_scale,
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num_inference_steps=steps,
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width = width,
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height = height,
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image=image,
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generator=generator,
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).images[0]
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