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Browse files- README.md +1 -2
- scripts/scripts_utils/plotly_interface.py +8 -8
README.md
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@@ -2,9 +2,8 @@
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title: "RAP: Risk-Aware Prediction"
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emoji: π
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colorFrom: red
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colorTo:
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sdk: gradio
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sdk_version: 3.7
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app_file: app.py
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pinned: false
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language:
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title: "RAP: Risk-Aware Prediction"
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emoji: π
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colorFrom: red
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colorTo: gray
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sdk: gradio
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app_file: app.py
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pinned: false
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language:
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scripts/scripts_utils/plotly_interface.py
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@@ -348,17 +348,17 @@ def main(load_from=None, cfg_path=None):
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# Define the device to use
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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predictor, dataset = load_from_huggingface(device=device)
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if load_from is not None:
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cfg = Config.fromfile(cfg_path)
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predictor = get_predictor(cfg, WaymoDataloaders.unnormalize_trajectory)
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predictor = load_weights(predictor, torch.load(load_from, map_location="cpu"))
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ui_update_fn = partial(update_figure, predictor, dataset)
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# Do the same thing as above but using the gradio blocks API
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with gr.Blocks() as interface:
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gr.Markdown(
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"""
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# Risk-Aware Prediction
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# Define the device to use
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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# Do the same thing as above but using the gradio blocks API
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with gr.Blocks() as interface:
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predictor, dataset = load_from_huggingface(device=device)
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if load_from is not None:
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cfg = Config.fromfile(cfg_path)
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predictor = get_predictor(cfg, WaymoDataloaders.unnormalize_trajectory)
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predictor = load_weights(predictor, torch.load(load_from, map_location="cpu"))
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ui_update_fn = partial(update_figure, predictor, dataset)
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gr.Markdown(
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"""
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# Risk-Aware Prediction
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