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452 行
16 KiB
452 行
16 KiB
using System.Collections.Generic;
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using System.Linq;
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using Unity.Barracuda;
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using FailedCheck = Unity.MLAgents.Inference.BarracudaModelParamLoader.FailedCheck;
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using UnityEngine;
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namespace Unity.MLAgents.Inference
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{
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/// <summary>
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/// Barracuda Model extension methods.
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/// </summary>
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internal static class BarracudaModelExtensions
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{
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/// <summary>
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/// Get array of the input tensor names of the model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>Array of the input tensor names of the model</returns>
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public static string[] GetInputNames(this Model model)
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{
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var names = new List<string>();
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if (model == null)
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return names.ToArray();
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foreach (var input in model.inputs)
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{
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names.Add(input.name);
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}
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foreach (var mem in model.memories)
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{
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names.Add(mem.input);
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}
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names.Sort();
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return names.ToArray();
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}
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/// <summary>
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/// Get the version of the model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>The api version of the model</returns>
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public static int GetVersion(this Model model)
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{
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// return (int)model.GetTensorByName(TensorNames.VersionNumber)[0];
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return 3;
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}
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/// <summary>
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/// Generates the Tensor inputs that are expected to be present in the Model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>TensorProxy IEnumerable with the expected Tensor inputs.</returns>
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public static IReadOnlyList<TensorProxy> GetInputTensors(this Model model)
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{
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var tensors = new List<TensorProxy>();
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if (model == null)
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return tensors;
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foreach (var input in model.inputs)
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{
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tensors.Add(new TensorProxy
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{
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name = input.name,
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valueType = TensorProxy.TensorType.FloatingPoint,
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data = null,
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shape = input.shape.Select(i => (long)i).ToArray()
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});
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}
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foreach (var mem in model.memories)
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{
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tensors.Add(new TensorProxy
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{
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name = mem.input,
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valueType = TensorProxy.TensorType.FloatingPoint,
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data = null,
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shape = TensorUtils.TensorShapeFromBarracuda(mem.shape)
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});
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}
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tensors.Sort((el1, el2) => el1.name.CompareTo(el2.name));
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return tensors;
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}
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public static IReadOnlyList<TensorProxy> GetTrainingInputTensors(this Model model)
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{
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var tensors = new List<TensorProxy>();
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if (model == null)
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return tensors;
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foreach (var input in model.inputs)
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{
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tensors.Add(new TensorProxy
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{
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name = input.name,
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valueType = TensorProxy.TensorType.FloatingPoint,
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data = null,
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shape = input.shape.Select(i => (long)i).ToArray()
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});
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}
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tensors.Sort((el1, el2) => el1.name.CompareTo(el2.name));
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return tensors;
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}
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/// <summary>
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/// Get number of visual observation inputs to the model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>Number of visual observation inputs to the model</returns>
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public static int GetNumVisualInputs(this Model model)
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{
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var count = 0;
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if (model == null)
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return count;
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foreach (var input in model.inputs)
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{
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if (input.name.StartsWith(TensorNames.VisualObservationPlaceholderPrefix))
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{
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count++;
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}
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}
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return count;
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}
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/// <summary>
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/// Get array of the output tensor names of the model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>Array of the output tensor names of the model</returns>
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public static string[] GetOutputNames(this Model model)
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{
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var names = new List<string>();
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if (model == null)
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{
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return names.ToArray();
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}
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if (model.HasContinuousOutputs())
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{
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names.Add(model.ContinuousOutputName());
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}
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if (model.HasDiscreteOutputs())
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{
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names.Add(model.DiscreteOutputName());
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}
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var memory = (int)model.GetTensorByName(TensorNames.MemorySize)[0];
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if (memory > 0)
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{
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foreach (var mem in model.memories)
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{
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names.Add(mem.output);
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}
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}
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names.Sort();
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return names.ToArray();
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}
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public static string[] GetTrainingOutputNames(this Model model)
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{
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var names = new List<string>();
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if (model == null)
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{
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return names.ToArray();
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}
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names.Add(TensorNames.TrainingStateOut);
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names.Add(TensorNames.OuputLoss);
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names.Add(TensorNames.TrainingOutput);
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names.Sort();
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return names.ToArray();
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}
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/// <summary>
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/// Check if the model has continuous action outputs.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>True if the model has continuous action outputs.</returns>
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public static bool HasContinuousOutputs(this Model model)
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{
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if (model == null)
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return false;
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if (!model.SupportsContinuousAndDiscrete())
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{
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return (int)model.GetTensorByName(TensorNames.IsContinuousControlDeprecated)[0] > 0;
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}
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else
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{
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return model.outputs.Contains(TensorNames.ContinuousActionOutput) &&
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(int)model.GetTensorByName(TensorNames.ContinuousActionOutputShape)[0] > 0;
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}
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}
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/// <summary>
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/// Continuous action output size of the model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>Size of continuous action output.</returns>
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public static int ContinuousOutputSize(this Model model)
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{
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if (model == null)
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return 0;
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if (!model.SupportsContinuousAndDiscrete())
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{
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return (int)model.GetTensorByName(TensorNames.IsContinuousControlDeprecated)[0] > 0 ?
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(int)model.GetTensorByName(TensorNames.ActionOutputShapeDeprecated)[0] : 0;
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}
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else
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{
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var continuousOutputShape = model.GetTensorByName(TensorNames.ContinuousActionOutputShape);
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return continuousOutputShape == null ? 0 : (int)continuousOutputShape[0];
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}
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}
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/// <summary>
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/// Continuous action output tensor name of the model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>Tensor name of continuous action output.</returns>
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public static string ContinuousOutputName(this Model model)
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{
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if (model == null)
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return null;
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if (!model.SupportsContinuousAndDiscrete())
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{
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return TensorNames.ActionOutputDeprecated;
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}
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else
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{
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return TensorNames.ContinuousActionOutput;
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}
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}
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/// <summary>
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/// Check if the model has discrete action outputs.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>True if the model has discrete action outputs.</returns>
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public static bool HasDiscreteOutputs(this Model model)
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{
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if (model == null)
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return false;
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if (!model.SupportsContinuousAndDiscrete())
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{
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return (int)model.GetTensorByName(TensorNames.IsContinuousControlDeprecated)[0] == 0;
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}
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else
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{
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return model.outputs.Contains(TensorNames.DiscreteActionOutput) &&
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(int)model.DiscreteOutputSize() > 0;
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}
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}
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/// <summary>
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/// Discrete action output size of the model. This is equal to the sum of the branch sizes.
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/// This method gets the tensor representing the list of branch size and returns the
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/// sum of all the elements in the Tensor.
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/// - In version 1.X this tensor contains a single number, the sum of all branch
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/// size values.
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/// - In version 2.X this tensor contains a 1D Tensor with each element corresponding
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/// to a branch size.
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/// Since this method does the sum of all elements in the tensor, the output
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/// will be the same on both 1.X and 2.X.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>Size of discrete action output.</returns>
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public static int DiscreteOutputSize(this Model model)
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{
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if (model == null)
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return 0;
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if (!model.SupportsContinuousAndDiscrete())
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{
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return (int)model.GetTensorByName(TensorNames.IsContinuousControlDeprecated)[0] > 0 ?
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0 : (int)model.GetTensorByName(TensorNames.ActionOutputShapeDeprecated)[0];
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}
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else
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{
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var discreteOutputShape = model.GetTensorByName(TensorNames.DiscreteActionOutputShape);
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if (discreteOutputShape == null)
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{
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return 0;
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}
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else
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{
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int result = 0;
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for (int i = 0; i < discreteOutputShape.length; i++)
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{
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result += (int)discreteOutputShape[i];
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}
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return result;
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}
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}
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}
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/// <summary>
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/// Discrete action output tensor name of the model.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>Tensor name of discrete action output.</returns>
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public static string DiscreteOutputName(this Model model)
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{
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if (model == null)
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return null;
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if (!model.SupportsContinuousAndDiscrete())
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{
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return TensorNames.ActionOutputDeprecated;
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}
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else
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{
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return TensorNames.DiscreteActionOutput;
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}
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}
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/// <summary>
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/// Check if the model supports both continuous and discrete actions.
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/// If not, the model should be handled differently and use the deprecated fields.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <returns>True if the model supports both continuous and discrete actions.</returns>
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public static bool SupportsContinuousAndDiscrete(this Model model)
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{
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return model == null ||
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model.outputs.Contains(TensorNames.ContinuousActionOutput) ||
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model.outputs.Contains(TensorNames.DiscreteActionOutput);
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}
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/// <summary>
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/// Check if the model contains all the expected input/output tensors.
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/// </summary>
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/// <param name="model">
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/// The Barracuda engine model for loading static parameters.
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/// </param>
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/// <param name="failedModelChecks">Output list of failure messages</param>
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///
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/// <returns>True if the model contains all the expected tensors.</returns>
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public static bool CheckExpectedTensors(this Model model, List<FailedCheck> failedModelChecks)
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{
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// Check the presence of model version
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// var modelApiVersionTensor = model.GetTensorByName(TensorNames.VersionNumber);
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// if (modelApiVersionTensor == null)
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// {
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// failedModelChecks.Add(
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// FailedCheck.Warning($"Required constant \"{TensorNames.VersionNumber}\" was not found in the model file.")
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// );
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// return false;
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// }
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// Check the presence of memory size
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// var memorySizeTensor = model.GetTensorByName(TensorNames.MemorySize);
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// if (memorySizeTensor == null)
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// {
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// failedModelChecks.Add(
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// FailedCheck.Warning($"Required constant \"{TensorNames.MemorySize}\" was not found in the model file.")
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// );
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// return false;
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// }
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// Check the presence of action output tensor
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if (!model.outputs.Contains(TensorNames.ActionOutputDeprecated) &&
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!model.outputs.Contains(TensorNames.ContinuousActionOutput) &&
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!model.outputs.Contains(TensorNames.DiscreteActionOutput))
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{
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failedModelChecks.Add(
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FailedCheck.Warning("The model does not contain any Action Output Node.")
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);
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return false;
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}
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// Check the presence of action output shape tensor
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if (!model.SupportsContinuousAndDiscrete())
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{
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if (model.GetTensorByName(TensorNames.ActionOutputShapeDeprecated) == null)
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{
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failedModelChecks.Add(
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FailedCheck.Warning("The model does not contain any Action Output Shape Node.")
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);
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return false;
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}
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if (model.GetTensorByName(TensorNames.IsContinuousControlDeprecated) == null)
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{
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failedModelChecks.Add(
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FailedCheck.Warning($"Required constant \"{TensorNames.IsContinuousControlDeprecated}\" was " +
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"not found in the model file. " +
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"This is only required for model that uses a deprecated model format.")
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);
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return false;
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}
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}
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else
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{
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if (model.outputs.Contains(TensorNames.ContinuousActionOutput) &&
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model.GetTensorByName(TensorNames.ContinuousActionOutputShape) == null)
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{
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failedModelChecks.Add(
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FailedCheck.Warning("The model uses continuous action but does not contain Continuous Action Output Shape Node.")
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);
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return false;
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}
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if (model.outputs.Contains(TensorNames.DiscreteActionOutput) &&
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model.GetTensorByName(TensorNames.DiscreteActionOutputShape) == null)
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{
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failedModelChecks.Add(
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FailedCheck.Warning("The model uses discrete action but does not contain Discrete Action Output Shape Node.")
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);
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return false;
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}
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}
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return true;
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}
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}
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}
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