47 lines
788 B
Python
47 lines
788 B
Python
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import torch
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from pathlib import Path
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import celeste_ai.plotting as plotting
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from multiprocessing import Pool
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m = Path("model_data/current")
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# Make "predicted reward" plots
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def plot_pred(src_model):
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plotting.predicted_reward(
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src_model,
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m / f"plots/predicted/{src_model.stem}.png",
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device = torch.device("cpu")
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)
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# Make "actual reward" plots
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def plot_act(src_model):
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plotting.actual_reward(
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src_model,
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(60, 80),
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m / f"plots/actual/{src_model.stem}.png",
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device = torch.device("cpu")
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)
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if __name__ == "__main__":
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print("Making prediction plots...")
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with Pool(5) as p:
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p.map(
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plot_pred,
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list((m / "model_archive").iterdir())
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)
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print("Making actual plots...")
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with Pool(5) as p:
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p.map(
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plot_act,
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list((m / "model_archive").iterdir())
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)
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