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737 行
32 KiB
737 行
32 KiB
using System;
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using System.Collections.Generic;
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using System.Linq;
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using Unity.Barracuda;
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using Unity.MLAgents.Actuators;
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using Unity.MLAgents.Sensors;
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using Unity.MLAgents.Policies;
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namespace Unity.MLAgents.Inference
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{
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/// <summary>
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/// Prepares the Tensors for the Learning Brain and exposes a list of failed checks if Model
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/// and BrainParameters are incompatible.
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/// </summary>
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internal class BarracudaModelParamLoader
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{
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enum ModelActionType
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{
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Unknown,
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Discrete,
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Continuous
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}
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const long k_ApiVersion = 2;
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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(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 int GetNumVisualInputs(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.shape.Length == 4)
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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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}
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return count;
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}
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/// <summary>
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/// Generates the Tensor outputs 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 outputs</returns>
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public static string[] GetOutputNames(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.ActionOutput);
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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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/// <summary>
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/// Factory for the ModelParamLoader : Creates a ModelParamLoader and runs the checks
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/// on it.
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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="brainParameters">
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/// The BrainParameters that are used verify the compatibility with the InferenceEngine
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/// </param>
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/// <param name="sensorComponents">Attached sensor components</param>
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/// <param name="actuatorComponents">Attached actuator components</param>
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/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes.</param>
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/// <param name="behaviorType">BehaviorType or the Agent to check.</param>
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/// <returns>The list the error messages of the checks that failed</returns>
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public static IEnumerable<string> CheckModel(Model model, BrainParameters brainParameters,
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SensorComponent[] sensorComponents, ActuatorComponent[] actuatorComponents,
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int observableAttributeTotalSize = 0,
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BehaviorType behaviorType = BehaviorType.Default)
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{
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List<string> failedModelChecks = new List<string>();
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if (model == null)
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{
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var errorMsg = "There is no model for this Brain; cannot run inference. ";
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if (behaviorType == BehaviorType.InferenceOnly)
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{
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errorMsg += "Either assign a model, or change to a different Behavior Type.";
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}
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else
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{
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errorMsg += "(But can still train)";
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}
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failedModelChecks.Add(errorMsg);
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return failedModelChecks;
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}
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foreach (var constantName in TensorNames.RequiredConstants)
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{
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var tensor = model.GetTensorByName(constantName);
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if (tensor == null)
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{
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failedModelChecks.Add($"Required constant \"{constantName}\" was not found in the model file.");
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return failedModelChecks;
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}
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}
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var modelApiVersion = (int)model.GetTensorByName(TensorNames.VersionNumber)[0];
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var memorySize = (int)model.GetTensorByName(TensorNames.MemorySize)[0];
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var isContinuousInt = (int)model.GetTensorByName(TensorNames.IsContinuousControl)[0];
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var isContinuous = GetActionType(isContinuousInt);
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var actionSize = (int)model.GetTensorByName(TensorNames.ActionOutputShape)[0];
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if (modelApiVersion == -1)
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{
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failedModelChecks.Add(
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"Model was not trained using the right version of ML-Agents. " +
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"Cannot use this model.");
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return failedModelChecks;
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}
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if (modelApiVersion != k_ApiVersion)
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{
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failedModelChecks.Add(
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$"Version of the trainer the model was trained with ({modelApiVersion}) " +
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$"is not compatible with the Brain's version ({k_ApiVersion}).");
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return failedModelChecks;
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}
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var modelDiscreteActionSize = isContinuous == ModelActionType.Discrete ? actionSize : 0;
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var modelContinuousActionSize = isContinuous == ModelActionType.Continuous ? actionSize : 0;
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failedModelChecks.AddRange(
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CheckIntScalarPresenceHelper(new Dictionary<string, int>()
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{
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{TensorNames.MemorySize, memorySize},
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{TensorNames.IsContinuousControl, isContinuousInt},
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{TensorNames.ActionOutputShape, actionSize}
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})
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);
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failedModelChecks.AddRange(
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CheckInputTensorPresence(model, brainParameters, memorySize, isContinuous, sensorComponents)
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);
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failedModelChecks.AddRange(
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CheckOutputTensorPresence(model, memorySize))
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;
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failedModelChecks.AddRange(
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CheckInputTensorShape(model, brainParameters, sensorComponents, observableAttributeTotalSize)
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);
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failedModelChecks.AddRange(
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CheckOutputTensorShape(model, brainParameters, actuatorComponents, isContinuous, modelContinuousActionSize, modelDiscreteActionSize)
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);
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return failedModelChecks;
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}
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/// <summary>
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/// Converts the integer value in the model corresponding to the type of control to a
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/// ModelActionType.
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/// </summary>
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/// <param name="isContinuousInt">
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/// The integer value in the model indicating the type of control
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/// </param>
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/// <returns>The equivalent ModelActionType</returns>
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static ModelActionType GetActionType(int isContinuousInt)
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{
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ModelActionType isContinuous;
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switch (isContinuousInt)
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{
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case 0:
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isContinuous = ModelActionType.Discrete;
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break;
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case 1:
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isContinuous = ModelActionType.Continuous;
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break;
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default:
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isContinuous = ModelActionType.Unknown;
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break;
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}
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return isContinuous;
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}
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/// <summary>
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/// Given a Dictionary of node names to int values, create checks if the values have the
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/// invalid value of -1.
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/// </summary>
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/// <param name="requiredScalarFields"> Mapping from node names to int values</param>
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/// <returns>The list the error messages of the checks that failed</returns>
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static IEnumerable<string> CheckIntScalarPresenceHelper(
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Dictionary<string, int> requiredScalarFields)
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{
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var failedModelChecks = new List<string>();
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foreach (var field in requiredScalarFields)
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{
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if (field.Value == -1)
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{
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failedModelChecks.Add($"Missing node in the model provided : {field.Key}");
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}
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}
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return failedModelChecks;
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}
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/// <summary>
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/// Generates failed checks that correspond to inputs expected by the model that are not
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/// present in the BrainParameters.
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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="brainParameters">
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/// The BrainParameters that are used verify the compatibility with the InferenceEngine
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/// </param>
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/// <param name="memory">
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/// The memory size that the model is expecting.
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/// </param>
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/// <param name="isContinuous">
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/// Whether the model is expecting continuous or discrete control.
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/// </param>
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/// <param name="sensorComponents">Array of attached sensor components</param>
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/// <param name="observableAttributeTotalSize">Total size of ObservableAttributes</param>
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/// <returns>
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/// A IEnumerable of string corresponding to the failed input presence checks.
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/// </returns>
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static IEnumerable<string> CheckInputTensorPresence(
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Model model,
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BrainParameters brainParameters,
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int memory,
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ModelActionType isContinuous,
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SensorComponent[] sensorComponents
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)
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{
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var failedModelChecks = new List<string>();
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var tensorsNames = GetInputTensors(model).Select(x => x.name).ToList();
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// If there is no Vector Observation Input but the Brain Parameters expect one.
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if ((brainParameters.VectorObservationSize != 0) &&
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(!tensorsNames.Contains(TensorNames.VectorObservationPlaceholder)))
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{
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failedModelChecks.Add(
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"The model does not contain a Vector Observation Placeholder Input. " +
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"You must set the Vector Observation Space Size to 0.");
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}
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// If there are not enough Visual Observation Input compared to what the
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// sensors expect.
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var visObsIndex = 0;
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for (var sensorIndex = 0; sensorIndex < sensorComponents.Length; sensorIndex++)
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{
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var sensor = sensorComponents[sensorIndex];
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if (!sensor.IsVisual())
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{
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continue;
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}
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if (!tensorsNames.Contains(
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TensorNames.VisualObservationPlaceholderPrefix + visObsIndex))
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{
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failedModelChecks.Add(
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"The model does not contain a Visual Observation Placeholder Input " +
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$"for sensor component {visObsIndex} ({sensor.GetType().Name}).");
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}
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visObsIndex++;
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}
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var expectedVisualObs = GetNumVisualInputs(model);
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// Check if there's not enough visual sensors (too many would be handled above)
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if (expectedVisualObs > visObsIndex)
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{
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failedModelChecks.Add(
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$"The model expects {expectedVisualObs} visual inputs," +
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$" but only found {visObsIndex} visual sensors."
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);
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}
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// If the model has a non-negative memory size but requires a recurrent input
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if (memory > 0)
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{
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if (!tensorsNames.Any(x => x.EndsWith("_h")) ||
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!tensorsNames.Any(x => x.EndsWith("_c")))
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{
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failedModelChecks.Add(
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"The model does not contain a Recurrent Input Node but has memory_size.");
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}
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}
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// If the model uses discrete control but does not have an input for action masks
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if (isContinuous == ModelActionType.Discrete)
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{
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if (!tensorsNames.Contains(TensorNames.ActionMaskPlaceholder))
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{
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failedModelChecks.Add(
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"The model does not contain an Action Mask but is using Discrete Control.");
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}
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}
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return failedModelChecks;
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}
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/// <summary>
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/// Generates failed checks that correspond to outputs expected by the model that are not
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/// present in the BrainParameters.
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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="memory">The memory size that the model is expecting/</param>
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/// <returns>
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/// A IEnumerable of string corresponding to the failed output presence checks.
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/// </returns>
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static IEnumerable<string> CheckOutputTensorPresence(Model model, int memory)
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{
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var failedModelChecks = new List<string>();
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// If there is no Action Output.
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if (!model.outputs.Contains(TensorNames.ActionOutput))
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{
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failedModelChecks.Add("The model does not contain an Action Output Node.");
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}
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// If there is no Recurrent Output but the model is Recurrent.
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if (memory > 0)
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{
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var memOutputs = model.memories.Select(x => x.output).ToList();
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if (!memOutputs.Any(x => x.EndsWith("_h")) ||
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!memOutputs.Any(x => x.EndsWith("_c")))
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{
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failedModelChecks.Add(
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"The model does not contain a Recurrent Output Node but has memory_size.");
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}
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}
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return failedModelChecks;
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}
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/// <summary>
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/// Checks that the shape of the visual observation input placeholder is the same as the corresponding sensor.
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/// </summary>
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/// <param name="tensorProxy">The tensor that is expected by the model</param>
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/// <param name="sensorComponent">The sensor that produces the visual observation.</param>
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/// <returns>
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/// If the Check failed, returns a string containing information about why the
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/// check failed. If the check passed, returns null.
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/// </returns>
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static string CheckVisualObsShape(
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TensorProxy tensorProxy, SensorComponent sensorComponent)
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{
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var shape = sensorComponent.GetObservationShape();
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var heightBp = shape[0];
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var widthBp = shape[1];
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var pixelBp = shape[2];
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var heightT = tensorProxy.shape[1];
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var widthT = tensorProxy.shape[2];
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var pixelT = tensorProxy.shape[3];
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if ((widthBp != widthT) || (heightBp != heightT) || (pixelBp != pixelT))
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{
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return $"The visual Observation of the model does not match. " +
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$"Received TensorProxy of shape [?x{widthBp}x{heightBp}x{pixelBp}] but " +
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$"was expecting [?x{widthT}x{heightT}x{pixelT}].";
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}
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return null;
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}
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/// <summary>
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/// Generates failed checks that correspond to inputs shapes incompatibilities between
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/// the model and the BrainParameters.
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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="brainParameters">
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/// The BrainParameters that are used verify the compatibility with the InferenceEngine
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/// </param>
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/// <param name="sensorComponents">Attached sensors</param>
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/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes.</param>
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/// <returns>The list the error messages of the checks that failed</returns>
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static IEnumerable<string> CheckInputTensorShape(
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Model model, BrainParameters brainParameters, SensorComponent[] sensorComponents,
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int observableAttributeTotalSize)
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{
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var failedModelChecks = new List<string>();
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var tensorTester =
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new Dictionary<string, Func<BrainParameters, TensorProxy, SensorComponent[], int, string>>()
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{
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{TensorNames.VectorObservationPlaceholder, CheckVectorObsShape},
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{TensorNames.PreviousActionPlaceholder, CheckPreviousActionShape},
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{TensorNames.RandomNormalEpsilonPlaceholder, ((bp, tensor, scs, i) => null)},
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{TensorNames.ActionMaskPlaceholder, ((bp, tensor, scs, i) => null)},
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{TensorNames.SequenceLengthPlaceholder, ((bp, tensor, scs, i) => null)},
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{TensorNames.RecurrentInPlaceholder, ((bp, tensor, scs, i) => null)},
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};
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foreach (var mem in model.memories)
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{
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tensorTester[mem.input] = ((bp, tensor, scs, i) => null);
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}
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var visObsIndex = 0;
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for (var sensorIndex = 0; sensorIndex < sensorComponents.Length; sensorIndex++)
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{
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var sensorComponent = sensorComponents[sensorIndex];
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if (!sensorComponent.IsVisual())
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{
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continue;
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}
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tensorTester[TensorNames.VisualObservationPlaceholderPrefix + visObsIndex] =
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(bp, tensor, scs, i) => CheckVisualObsShape(tensor, sensorComponent);
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visObsIndex++;
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}
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// If the model expects an input but it is not in this list
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foreach (var tensor in GetInputTensors(model))
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{
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if (!tensorTester.ContainsKey(tensor.name))
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{
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if (!tensor.name.Contains("visual_observation"))
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{
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failedModelChecks.Add(
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"Model requires an unknown input named : " + tensor.name);
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}
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}
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else
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{
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var tester = tensorTester[tensor.name];
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var error = tester.Invoke(brainParameters, tensor, sensorComponents, observableAttributeTotalSize);
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if (error != null)
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{
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failedModelChecks.Add(error);
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}
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}
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}
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return failedModelChecks;
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}
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/// <summary>
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/// Checks that the shape of the Vector Observation input placeholder is the same in the
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/// model and in the Brain Parameters.
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/// </summary>
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/// <param name="brainParameters">
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/// The BrainParameters that are used verify the compatibility with the InferenceEngine
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/// </param>
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/// <param name="tensorProxy">The tensor that is expected by the model</param>
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/// <param name="sensorComponents">Array of attached sensor components</param>
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/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes.</param>
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/// <returns>
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/// If the Check failed, returns a string containing information about why the
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/// check failed. If the check passed, returns null.
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/// </returns>
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static string CheckVectorObsShape(
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BrainParameters brainParameters, TensorProxy tensorProxy, SensorComponent[] sensorComponents,
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int observableAttributeTotalSize)
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{
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var vecObsSizeBp = brainParameters.VectorObservationSize;
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var numStackedVector = brainParameters.NumStackedVectorObservations;
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var totalVecObsSizeT = tensorProxy.shape[tensorProxy.shape.Length - 1];
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var totalVectorSensorSize = 0;
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foreach (var sensorComp in sensorComponents)
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{
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if (sensorComp.IsVector())
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{
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totalVectorSensorSize += sensorComp.GetObservationShape()[0];
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}
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}
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totalVectorSensorSize += observableAttributeTotalSize;
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if (vecObsSizeBp * numStackedVector + totalVectorSensorSize != totalVecObsSizeT)
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{
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var sensorSizes = "";
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foreach (var sensorComp in sensorComponents)
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{
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if (sensorComp.IsVector())
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{
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var vecSize = sensorComp.GetObservationShape()[0];
|
|
if (sensorSizes.Length == 0)
|
|
{
|
|
sensorSizes = $"[{vecSize}";
|
|
}
|
|
else
|
|
{
|
|
sensorSizes += $", {vecSize}";
|
|
}
|
|
}
|
|
}
|
|
|
|
sensorSizes += "]";
|
|
return $"Vector Observation Size of the model does not match. Was expecting {totalVecObsSizeT} " +
|
|
$"but received: \n" +
|
|
$"Vector observations: {vecObsSizeBp} x {numStackedVector}\n" +
|
|
$"Total [Observable] attributes: {observableAttributeTotalSize}\n" +
|
|
$"SensorComponent sizes: {sensorSizes}.";
|
|
}
|
|
return null;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Checks that the shape of the Previous Vector Action input placeholder is the same in the
|
|
/// model and in the Brain Parameters.
|
|
/// </summary>
|
|
/// <param name="brainParameters">
|
|
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
|
|
/// </param>
|
|
/// <param name="tensorProxy"> The tensor that is expected by the model</param>
|
|
/// <param name="sensorComponents">Array of attached sensor components (unused).</param>
|
|
/// <param name="observableAttributeTotalSize">Sum of the sizes of all ObservableAttributes (unused).</param>
|
|
/// <returns>If the Check failed, returns a string containing information about why the
|
|
/// check failed. If the check passed, returns null.</returns>
|
|
static string CheckPreviousActionShape(
|
|
BrainParameters brainParameters, TensorProxy tensorProxy,
|
|
SensorComponent[] sensorComponents, int observableAttributeTotalSize)
|
|
{
|
|
var numberActionsBp = brainParameters.VectorActionSize.Length;
|
|
var numberActionsT = tensorProxy.shape[tensorProxy.shape.Length - 1];
|
|
if (numberActionsBp != numberActionsT)
|
|
{
|
|
return "Previous Action Size of the model does not match. " +
|
|
$"Received {numberActionsBp} but was expecting {numberActionsT}.";
|
|
}
|
|
return null;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Generates failed checks that correspond to output shapes incompatibilities between
|
|
/// the model and the BrainParameters.
|
|
/// </summary>
|
|
/// <param name="model">
|
|
/// The Barracuda engine model for loading static parameters
|
|
/// </param>
|
|
/// <param name="brainParameters">
|
|
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
|
|
/// </param>
|
|
/// <param name="actuatorComponents">Array of attached actuator components.</param>
|
|
/// <param name="isContinuous">
|
|
/// Whether the model is expecting continuous or discrete control.
|
|
/// </param>
|
|
/// <param name="modelContinuousActionSize">
|
|
/// The size of the continuous action output that is expected by the model.
|
|
/// </param>
|
|
/// <param name="modelSumDiscreteBranchSizes">
|
|
/// The size of the discrete action output that is expected by the model.
|
|
/// </param>
|
|
/// <returns>
|
|
/// A IEnumerable of string corresponding to the incompatible shapes between model
|
|
/// and BrainParameters.
|
|
/// </returns>
|
|
static IEnumerable<string> CheckOutputTensorShape(
|
|
Model model,
|
|
BrainParameters brainParameters,
|
|
ActuatorComponent[] actuatorComponents,
|
|
ModelActionType isContinuous,
|
|
int modelContinuousActionSize, int modelSumDiscreteBranchSizes)
|
|
{
|
|
var failedModelChecks = new List<string>();
|
|
if (isContinuous == ModelActionType.Unknown)
|
|
{
|
|
failedModelChecks.Add("Cannot infer type of Control from the provided model.");
|
|
return failedModelChecks;
|
|
}
|
|
if (isContinuous == ModelActionType.Continuous &&
|
|
brainParameters.VectorActionSpaceType != SpaceType.Continuous)
|
|
{
|
|
failedModelChecks.Add(
|
|
"Model has been trained using Continuous Control but the Brain Parameters " +
|
|
"suggest Discrete Control.");
|
|
return failedModelChecks;
|
|
}
|
|
if (isContinuous == ModelActionType.Discrete &&
|
|
brainParameters.VectorActionSpaceType != SpaceType.Discrete)
|
|
{
|
|
failedModelChecks.Add(
|
|
"Model has been trained using Discrete Control but the Brain Parameters " +
|
|
"suggest Continuous Control.");
|
|
return failedModelChecks;
|
|
}
|
|
var tensorTester = new Dictionary<string, Func<BrainParameters, ActuatorComponent[], TensorShape?, int, int, string>>();
|
|
|
|
// This will need to change a bit for hybrid action spaces.
|
|
if (isContinuous == ModelActionType.Continuous)
|
|
{
|
|
tensorTester[TensorNames.ActionOutput] = CheckContinuousActionOutputShape;
|
|
}
|
|
else
|
|
{
|
|
tensorTester[TensorNames.ActionOutput] = CheckDiscreteActionOutputShape;
|
|
}
|
|
|
|
// If the model expects an output but it is not in this list
|
|
foreach (var name in model.outputs)
|
|
{
|
|
if (tensorTester.ContainsKey(name))
|
|
{
|
|
var tester = tensorTester[name];
|
|
var error = tester.Invoke(brainParameters, actuatorComponents, model.GetShapeByName(name), modelContinuousActionSize, modelSumDiscreteBranchSizes);
|
|
if (error != null)
|
|
{
|
|
failedModelChecks.Add(error);
|
|
}
|
|
}
|
|
}
|
|
return failedModelChecks;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Checks that the shape of the discrete action output is the same in the
|
|
/// model and in the Brain Parameters.
|
|
/// </summary>
|
|
/// <param name="brainParameters">
|
|
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
|
|
/// </param>
|
|
/// <param name="actuatorComponents">Array of attached actuator components.</param>
|
|
/// <param name="shape"> The tensor shape that is expected by the model</param>
|
|
/// <param name="modelContinuousActionSize">
|
|
/// The size of the continuous action output that is expected by the model.
|
|
/// </param>
|
|
/// <param name="modelSumDiscreteBranchSizes">
|
|
/// The size of the discrete action output that is expected by the model.
|
|
/// </param>
|
|
/// <returns>
|
|
/// If the Check failed, returns a string containing information about why the
|
|
/// check failed. If the check passed, returns null.
|
|
/// </returns>
|
|
static string CheckDiscreteActionOutputShape(
|
|
BrainParameters brainParameters, ActuatorComponent[] actuatorComponents, TensorShape? shape, int modelContinuousActionSize, int modelSumDiscreteBranchSizes)
|
|
{
|
|
var sumOfDiscreteBranchSizes = 0;
|
|
if (brainParameters.VectorActionSpaceType == SpaceType.Discrete)
|
|
{
|
|
sumOfDiscreteBranchSizes += brainParameters.VectorActionSize.Sum();
|
|
}
|
|
|
|
foreach (var actuatorComponent in actuatorComponents)
|
|
{
|
|
var actionSpec = actuatorComponent.ActionSpec;
|
|
sumOfDiscreteBranchSizes += actionSpec.SumOfDiscreteBranchSizes;
|
|
}
|
|
|
|
if (modelSumDiscreteBranchSizes != sumOfDiscreteBranchSizes)
|
|
{
|
|
return "Discrete Action Size of the model does not match. The BrainParameters expect " +
|
|
$"{sumOfDiscreteBranchSizes} but the model contains {modelSumDiscreteBranchSizes}.";
|
|
}
|
|
return null;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Checks that the shape of the continuous action output is the same in the
|
|
/// model and in the Brain Parameters.
|
|
/// </summary>
|
|
/// <param name="brainParameters">
|
|
/// The BrainParameters that are used verify the compatibility with the InferenceEngine
|
|
/// </param>
|
|
/// <param name="actuatorComponents">Array of attached actuator components.</param>
|
|
/// <param name="shape"> The tensor shape that is expected by the model</param>
|
|
/// <param name="modelContinuousActionSize">
|
|
/// The size of the continuous action output that is expected by the model.
|
|
/// </param>
|
|
/// <param name="modelSumDiscreteBranchSizes">
|
|
/// The size of the discrete action output that is expected by the model.
|
|
/// </param>
|
|
/// <returns>If the Check failed, returns a string containing information about why the
|
|
/// check failed. If the check passed, returns null.</returns>
|
|
static string CheckContinuousActionOutputShape(
|
|
BrainParameters brainParameters, ActuatorComponent[] actuatorComponents, TensorShape? shape, int modelContinuousActionSize, int modelSumDiscreteBranchSizes)
|
|
{
|
|
var numContinuousActions = 0;
|
|
if (brainParameters.VectorActionSpaceType == SpaceType.Continuous)
|
|
{
|
|
numContinuousActions += brainParameters.NumActions;
|
|
}
|
|
|
|
foreach (var actuatorComponent in actuatorComponents)
|
|
{
|
|
var actionSpec = actuatorComponent.ActionSpec;
|
|
numContinuousActions += actionSpec.NumContinuousActions;
|
|
}
|
|
|
|
if (modelContinuousActionSize != numContinuousActions)
|
|
{
|
|
return "Continuous Action Size of the model does not match. The BrainParameters and ActuatorComponents expect " +
|
|
$"{numContinuousActions} but the model contains {modelContinuousActionSize}.";
|
|
}
|
|
return null;
|
|
}
|
|
}
|
|
}
|