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Update app.py
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app.py
CHANGED
@@ -1,8 +1,3 @@
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You can easily add that blurb by inserting a `gr.Markdown()` component within the same `gr.Column()` as your `sample_input_slider` and `run_button`. This effectively places it within Gradio's "flexbox" layout, ensuring it's always visible below the slider and button.
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Here's your `app.py` code with the blurb added in the correct place. I've also updated the `run_inference` function to explicitly target `torch.device("cpu")` and removed the `@spaces.GPU()` decorator, which aligns with your successful run on ZeroCPU.
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```python
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import gradio as gr
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import torch
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from neuralop.models import FNO
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@@ -61,7 +56,11 @@ def load_dataset():
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data = torch.load(local_dataset_path, map_location='cpu')
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if isinstance(data, dict) and 'x' in data:
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FULL_DATASET_X = data['x']
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elif isinstance(
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FULL_DATASET_X = data
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else:
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raise ValueError("Unknown dataset format or 'x' key missing.")
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@@ -170,6 +169,4 @@ with gr.Blocks() as demo:
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demo.load(load_initial_data_and_predict, inputs=None, outputs=[input_image_plot, output_image_plot])
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if __name__ == "__main__":
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demo.launch()
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```
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import gradio as gr
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import torch
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from neuralop.models import FNO
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data = torch.load(local_dataset_path, map_location='cpu')
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if isinstance(data, dict) and 'x' in data:
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FULL_DATASET_X = data['x']
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elif isinstance(dYou can easily add that blurb by inserting a `gr.Markdown()` component within the same `gr.Column()` as your `sample_input_slider` and `run_button`. This effectively places it within Gradio's "flexbox" layout, ensuring it's always visible below the slider and button.
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Here's your `app.py` code with the blurb added in the correct place. I've also updated the `run_inference` function to explicitly target `torch.device("cpu")` and removed the `@spaces.GPU()` decorator, which aligns with your successful run on ZeroCPU.
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```pythonata, torch.Tensor):
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FULL_DATASET_X = data
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else:
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raise ValueError("Unknown dataset format or 'x' key missing.")
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demo.load(load_initial_data_and_predict, inputs=None, outputs=[input_image_plot, output_image_plot])
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if __name__ == "__main__":
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demo.launch()
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