AlexKoff88 commited on
Commit
ad14b11
·
1 Parent(s): e12048f

Added torch model

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Files changed (1) hide show
  1. app.py +13 -8
app.py CHANGED
@@ -1,13 +1,15 @@
1
  import gradio as gr
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  from optimum.intel.openvino import OVStableDiffusionPipeline
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  from diffusers.training_utils import set_seed
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- from diffusers import LMSDiscreteScheduler
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  import time
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- scheduler = LMSDiscreteScheduler(beta_start=0.00085, beta_end=0.012,
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- beta_schedule="scaled_linear", num_train_timesteps=1000)
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- pipe_fp32 = OVStableDiffusionPipeline.from_pretrained("OpenVINO/stable-diffusion-pokemons-fp32", compile=False, scheduler=scheduler)
 
 
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  pipe_fp32.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1)
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  pipe_fp32.compile()
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@@ -22,9 +24,10 @@ pipe_tome_int8.compile()
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  prompt = "cartoon bird"
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  pipes = {
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- "FP32": pipe_fp32,
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- "8-bit quantized": pipe_int8,
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- "Merged and quantized": pipe_tome_int8
 
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  }
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  def generate(image, option):
@@ -38,10 +41,12 @@ examples = ["cartoon bird",
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  "a drawing of a green pokemon with red eyes",
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  "plant pokemon in jungle"]
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  gr.Interface(
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  fn=generate,
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  inputs=[gr.inputs.Textbox(placeholder="cartoon bird", label="Prompt", lines=1),
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- gr.inputs.Dropdown(choices=[option for option in pipes.keys()], default="Merged and quantized", label="Model version"),
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  ],
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  outputs=[gr.outputs.Image(type="pil", label="Generated Image"), gr.outputs.Textbox(label="Inference time")],
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  title="OpenVINO-optimized Stable Diffusion",
 
1
  import gradio as gr
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  from optimum.intel.openvino import OVStableDiffusionPipeline
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  from diffusers.training_utils import set_seed
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+ from diffusers import LMSDiscreteScheduler, StableDiffusionPipeline
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  import time
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+ # scheduler = DDPMScheduler(beta_start=0.00085, beta_end=0.012,
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+ # beta_schedule="scaled_linear", num_train_timesteps=1000)
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+ pipe_torch_fp32 = StableDiffusionPipeline("svjack/Stable-Diffusion-Pokemon-en")
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+
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+ pipe_fp32 = OVStableDiffusionPipeline.from_pretrained("OpenVINO/stable-diffusion-pokemons-fp32", compile=False) scheduler=scheduler)
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  pipe_fp32.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1)
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  pipe_fp32.compile()
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  prompt = "cartoon bird"
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  pipes = {
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+ "Torch fp32"
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+ "OpenVINO fp32": pipe_fp32,
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+ "OpenVINO 8-bit quantized": pipe_int8,
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+ "OpenVINO merged and quantized": pipe_tome_int8
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  }
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  def generate(image, option):
 
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  "a drawing of a green pokemon with red eyes",
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  "plant pokemon in jungle"]
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+ choices = [option for option in pipes.keys()]
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+
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  gr.Interface(
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  fn=generate,
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  inputs=[gr.inputs.Textbox(placeholder="cartoon bird", label="Prompt", lines=1),
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+ gr.inputs.Dropdown(choices=choices], default=choices[-1], label="Model version"),
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  ],
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  outputs=[gr.outputs.Image(type="pil", label="Generated Image"), gr.outputs.Textbox(label="Inference time")],
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  title="OpenVINO-optimized Stable Diffusion",