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feat(*): Add self-play RL training pipeline with PPO trainer, in-game GDScript policy inference, and bot opponent support in Match mode
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<docs>
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<members name="ONNXInference">
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<ONNXInference>
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<summary>
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The main <c>ONNXInference</c> Class that handles the inference process.
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</summary>
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</ONNXInference>
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<Initialize>
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<summary>
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Starts the inference process.
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</summary>
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<param name="Path">Path to the ONNX model, expects a path inside resources.</param>
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<param name="BatchSize">How many observations will the model recieve.</param>
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</Initialize>
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<Run>
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<summary>
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Runs the given input through the model and returns the output.
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</summary>
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<param name="obs">Dictionary containing all observations.</param>
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<param name="state_ins">How many different agents are creating these observations.</param>
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<returns>A Dictionary of arrays, containing instructions based on the observations.</returns>
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</Run>
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<Load>
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<summary>
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Loads the given model into the inference process, using the best Execution provider available.
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</summary>
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<param name="Path">Path to the ONNX model, expects a path inside resources.</param>
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<returns>InferenceSession ready to run.</returns>
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</Load>
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</members>
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</docs>
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<docs>
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<members name="SessionConfigurator">
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<SessionConfigurator>
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<summary>
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The main <c>SessionConfigurator</c> Class that handles the execution options and providers for the inference process.
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</summary>
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</SessionConfigurator>
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<GetSessionOptions>
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<summary>
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Creates a SessionOptions with all available execution providers.
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</summary>
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<returns>SessionOptions with all available execution providers.</returns>
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</GetSessionOptions>
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<SystemCheck>
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<summary>
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Appends any execution provider available in the current system.
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</summary>
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<remarks>
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This function is mainly verbose for tracking implementation progress of different compute APIs.
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</remarks>
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</SystemCheck>
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<ComputeCheck>
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<summary>
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Checks for available GPUs.
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</summary>
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<returns>An integer identifier for each compute platform.</returns>
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</ComputeCheck>
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</members>
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</docs>
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