using System; using System.Collections.Generic; using System.Linq; using Unity.Barracuda; using Unity.MLAgents.Actuators; using Unity.MLAgents.Sensors; using Unity.MLAgents.Policies; namespace Unity.MLAgents.Inference { /// /// Prepares the Tensors for the Learning Brain and exposes a list of failed checks if Model /// and BrainParameters are incompatible. /// internal class BarracudaModelParamLoader { internal enum ModelApiVersion { MLAgents1_0 = 2, MLAgents2_0 = 3, MinSupportedVersion = MLAgents1_0, MaxSupportedVersion = MLAgents2_0 } internal class FailedCheck { public enum CheckTypeEnum { Info = 0, Warning = 1, Error = 2 } public CheckTypeEnum CheckType; public string Message; public static FailedCheck Info(string message) { return new FailedCheck { CheckType = CheckTypeEnum.Info, Message = message }; } public static FailedCheck Warning(string message) { return new FailedCheck { CheckType = CheckTypeEnum.Warning, Message = message }; } public static FailedCheck Error(string message) { return new FailedCheck { CheckType = CheckTypeEnum.Error, Message = message }; } } /// /// Factory for the ModelParamLoader : Creates a ModelParamLoader and runs the checks /// on it. /// /// /// The Barracuda engine model for loading static parameters /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// Attached sensor components /// Attached actuator components /// Sum of the sizes of all ObservableAttributes. /// BehaviorType or the Agent to check. /// A IEnumerable of the checks that failed public static IEnumerable CheckModel( Model model, BrainParameters brainParameters, ISensor[] sensors, ActuatorComponent[] actuatorComponents, int observableAttributeTotalSize = 0, BehaviorType behaviorType = BehaviorType.Default ) { List failedModelChecks = new List(); if (model == null) { var errorMsg = "There is no model for this Brain; cannot run inference. "; if (behaviorType == BehaviorType.InferenceOnly) { errorMsg += "Either assign a model, or change to a different Behavior Type."; } else { errorMsg += "(But can still train)"; } failedModelChecks.Add(FailedCheck.Info(errorMsg)); return failedModelChecks; } var hasExpectedTensors = model.CheckExpectedTensors(failedModelChecks); if (!hasExpectedTensors) { return failedModelChecks; } var modelApiVersion = model.GetVersion(); if (modelApiVersion < (int)ModelApiVersion.MinSupportedVersion || modelApiVersion > (int)ModelApiVersion.MaxSupportedVersion) { failedModelChecks.Add( FailedCheck.Warning($"Version of the trainer the model was trained with ({modelApiVersion}) " + $"is not compatible with the current range of supported versions: " + $"({(int)ModelApiVersion.MinSupportedVersion} to {(int)ModelApiVersion.MaxSupportedVersion}).") ); return failedModelChecks; } var memorySize = (int)model.GetTensorByName(TensorNames.MemorySize)[0]; if (memorySize == -1) { failedModelChecks.Add(FailedCheck.Warning($"Missing node in the model provided : {TensorNames.MemorySize}" )); return failedModelChecks; } if (modelApiVersion == (int)ModelApiVersion.MLAgents1_0) { failedModelChecks.AddRange( CheckInputTensorPresenceLegacy(model, brainParameters, memorySize, sensors) ); failedModelChecks.AddRange( CheckInputTensorShapeLegacy(model, brainParameters, sensors, observableAttributeTotalSize) ); } else if (modelApiVersion == (int)ModelApiVersion.MLAgents2_0) { failedModelChecks.AddRange( CheckInputTensorPresence(model, brainParameters, memorySize, sensors) ); failedModelChecks.AddRange( CheckInputTensorShape(model, brainParameters, sensors, observableAttributeTotalSize) ); } failedModelChecks.AddRange( CheckOutputTensorShape(model, brainParameters, actuatorComponents) ); failedModelChecks.AddRange( CheckOutputTensorPresence(model, memorySize) ); return failedModelChecks; } /// /// Generates failed checks that correspond to inputs expected by the model that are not /// present in the BrainParameters. Tests the models created with the API of version 1.X /// /// /// The Barracuda engine model for loading static parameters /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// /// The memory size that the model is expecting. /// /// Array of attached sensor components /// /// A IEnumerable of the checks that failed /// static IEnumerable CheckInputTensorPresenceLegacy( Model model, BrainParameters brainParameters, int memory, ISensor[] sensors ) { var failedModelChecks = new List(); var tensorsNames = model.GetInputNames(); // If there is no Vector Observation Input but the Brain Parameters expect one. if ((brainParameters.VectorObservationSize != 0) && (!tensorsNames.Contains(TensorNames.VectorObservationPlaceholder))) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain a Vector Observation Placeholder Input. " + "You must set the Vector Observation Space Size to 0.") ); } // If there are not enough Visual Observation Input compared to what the // sensors expect. var visObsIndex = 0; for (var sensorIndex = 0; sensorIndex < sensors.Length; sensorIndex++) { var sensor = sensors[sensorIndex]; if (sensor.GetObservationSpec().Shape.Length == 3) { if (!tensorsNames.Contains( TensorNames.GetVisualObservationName(visObsIndex))) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain a Visual Observation Placeholder Input " + $"for sensor component {visObsIndex} ({sensor.GetType().Name}).") ); } visObsIndex++; } if (sensor.GetObservationSpec().Shape.Length == 2) { if (!tensorsNames.Contains( TensorNames.GetObservationName(sensorIndex))) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain an Observation Placeholder Input " + $"for sensor component {sensorIndex} ({sensor.GetType().Name}).") ); } } } var expectedVisualObs = model.GetNumVisualInputs(); // Check if there's not enough visual sensors (too many would be handled above) if (expectedVisualObs > visObsIndex) { failedModelChecks.Add( FailedCheck.Warning($"The model expects {expectedVisualObs} visual inputs," + $" but only found {visObsIndex} visual sensors.") ); } // If the model has a non-negative memory size but requires a recurrent input if (memory > 0) { if (!tensorsNames.Any(x => x.EndsWith("_h")) || !tensorsNames.Any(x => x.EndsWith("_c"))) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain a Recurrent Input Node but has memory_size.") ); } } // If the model uses discrete control but does not have an input for action masks if (model.HasDiscreteOutputs()) { if (!tensorsNames.Contains(TensorNames.ActionMaskPlaceholder)) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain an Action Mask but is using Discrete Control.") ); } } return failedModelChecks; } /// /// Generates failed checks that correspond to inputs expected by the model that are not /// present in the BrainParameters. /// /// /// The Barracuda engine model for loading static parameters /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// /// The memory size that the model is expecting. /// /// Array of attached sensor components /// /// A IEnumerable of the checks that failed /// static IEnumerable CheckInputTensorPresence( Model model, BrainParameters brainParameters, int memory, ISensor[] sensors ) { var failedModelChecks = new List(); var tensorsNames = model.GetInputNames(); for (var sensorIndex = 0; sensorIndex < sensors.Length; sensorIndex++) { if (!tensorsNames.Contains( TensorNames.GetObservationName(sensorIndex))) { var sensor = sensors[sensorIndex]; failedModelChecks.Add( FailedCheck.Warning("The model does not contain an Observation Placeholder Input " + $"for sensor component {sensorIndex} ({sensor.GetType().Name}).") ); } } // If the model has a non-negative memory size but requires a recurrent input if (memory > 0) { if (!tensorsNames.Any(x => x.EndsWith("_h")) || !tensorsNames.Any(x => x.EndsWith("_c"))) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain a Recurrent Input Node but has memory_size.") ); } } // If the model uses discrete control but does not have an input for action masks if (model.HasDiscreteOutputs()) { if (!tensorsNames.Contains(TensorNames.ActionMaskPlaceholder)) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain an Action Mask but is using Discrete Control.") ); } } return failedModelChecks; } /// /// Generates failed checks that correspond to outputs expected by the model that are not /// present in the BrainParameters. /// /// /// The Barracuda engine model for loading static parameters /// /// The memory size that the model is expecting/ /// /// A IEnumerable of the checks that failed /// static IEnumerable CheckOutputTensorPresence(Model model, int memory) { var failedModelChecks = new List(); // If there is no Recurrent Output but the model is Recurrent. if (memory > 0) { var memOutputs = model.memories.Select(x => x.output).ToList(); if (!memOutputs.Any(x => x.EndsWith("_h")) || !memOutputs.Any(x => x.EndsWith("_c"))) { failedModelChecks.Add( FailedCheck.Warning("The model does not contain a Recurrent Output Node but has memory_size.") ); } } return failedModelChecks; } /// /// Checks that the shape of the visual observation input placeholder is the same as the corresponding sensor. /// /// The tensor that is expected by the model /// The sensor that produces the visual observation. /// /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. /// static FailedCheck CheckVisualObsShape( TensorProxy tensorProxy, ISensor sensor) { var shape = sensor.GetObservationSpec().Shape; var heightBp = shape[0]; var widthBp = shape[1]; var pixelBp = shape[2]; var heightT = tensorProxy.Height; var widthT = tensorProxy.Width; var pixelT = tensorProxy.Channels; if ((widthBp != widthT) || (heightBp != heightT) || (pixelBp != pixelT)) { return FailedCheck.Warning($"The visual Observation of the model does not match. " + $"Received TensorProxy of shape [?x{widthBp}x{heightBp}x{pixelBp}] but " + $"was expecting [?x{widthT}x{heightT}x{pixelT}] for the {sensor.GetName()} Sensor." ); } return null; } /// /// Checks that the shape of the rank 2 observation input placeholder is the same as the corresponding sensor. /// /// The tensor that is expected by the model /// The sensor that produces the visual observation. /// /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. /// static FailedCheck CheckRankTwoObsShape( TensorProxy tensorProxy, ISensor sensor) { var shape = sensor.GetObservationSpec().Shape; var dim1Bp = shape[0]; var dim2Bp = shape[1]; var dim1T = tensorProxy.Channels; var dim2T = tensorProxy.Width; var dim3T = tensorProxy.Height; if ((dim1Bp != dim1T) || (dim2Bp != dim2T)) { var proxyDimStr = $"[?x{dim1T}x{dim2T}]"; if (dim3T > 1) { proxyDimStr = $"[?x{dim3T}x{dim2T}x{dim1T}]"; } return FailedCheck.Warning($"An Observation of the model does not match. " + $"Received TensorProxy of shape [?x{dim1Bp}x{dim2Bp}] but " + $"was expecting {proxyDimStr} for the {sensor.GetName()} Sensor." ); } return null; } /// /// Checks that the shape of the rank 2 observation input placeholder is the same as the corresponding sensor. /// /// The tensor that is expected by the model /// The sensor that produces the visual observation. /// /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. /// static FailedCheck CheckRankOneObsShape( TensorProxy tensorProxy, ISensor sensor) { var shape = sensor.GetObservationSpec().Shape; var dim1Bp = shape[0]; var dim1T = tensorProxy.Channels; var dim2T = tensorProxy.Width; var dim3T = tensorProxy.Height; if ((dim1Bp != dim1T)) { var proxyDimStr = $"[?x{dim1T}]"; if (dim2T > 1) { proxyDimStr = $"[?x{dim1T}x{dim2T}]"; } if (dim3T > 1) { proxyDimStr = $"[?x{dim3T}x{dim2T}x{dim1T}]"; } return FailedCheck.Warning($"An Observation of the model does not match. " + $"Received TensorProxy of shape [?x{dim1Bp}] but " + $"was expecting {proxyDimStr} for the {sensor.GetName()} Sensor." ); } return null; } /// /// Generates failed checks that correspond to inputs shapes incompatibilities between /// the model and the BrainParameters. Tests the models created with the API of version 1.X /// /// /// The Barracuda engine model for loading static parameters /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// Attached sensors /// Sum of the sizes of all ObservableAttributes. /// A IEnumerable of the checks that failed static IEnumerable CheckInputTensorShapeLegacy( Model model, BrainParameters brainParameters, ISensor[] sensors, int observableAttributeTotalSize) { var failedModelChecks = new List(); var tensorTester = new Dictionary>() { {TensorNames.VectorObservationPlaceholder, CheckVectorObsShapeLegacy}, {TensorNames.PreviousActionPlaceholder, CheckPreviousActionShape}, {TensorNames.RandomNormalEpsilonPlaceholder, ((bp, tensor, scs, i) => null)}, {TensorNames.ActionMaskPlaceholder, ((bp, tensor, scs, i) => null)}, {TensorNames.SequenceLengthPlaceholder, ((bp, tensor, scs, i) => null)}, {TensorNames.RecurrentInPlaceholder, ((bp, tensor, scs, i) => null)}, }; foreach (var mem in model.memories) { tensorTester[mem.input] = ((bp, tensor, scs, i) => null); } var visObsIndex = 0; for (var sensorIndex = 0; sensorIndex < sensors.Length; sensorIndex++) { var sens = sensors[sensorIndex]; if (sens.GetObservationSpec().Shape.Length == 3) { tensorTester[TensorNames.GetVisualObservationName(visObsIndex)] = (bp, tensor, scs, i) => CheckVisualObsShape(tensor, sens); visObsIndex++; } if (sens.GetObservationSpec().Shape.Length == 2) { tensorTester[TensorNames.GetObservationName(sensorIndex)] = (bp, tensor, scs, i) => CheckRankTwoObsShape(tensor, sens); } } // If the model expects an input but it is not in this list foreach (var tensor in model.GetInputTensors()) { if (!tensorTester.ContainsKey(tensor.name)) { if (!tensor.name.Contains("visual_observation")) { failedModelChecks.Add( FailedCheck.Warning("Model contains an unexpected input named : " + tensor.name) ); } } else { var tester = tensorTester[tensor.name]; var error = tester.Invoke(brainParameters, tensor, sensors, observableAttributeTotalSize); if (error != null) { failedModelChecks.Add(error); } } } return failedModelChecks; } /// /// Checks that the shape of the Vector Observation input placeholder is the same in the /// model and in the Brain Parameters. Tests the models created with the API of version 1.X /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// The tensor that is expected by the model /// Array of attached sensor components /// Sum of the sizes of all ObservableAttributes. /// /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. /// static FailedCheck CheckVectorObsShapeLegacy( BrainParameters brainParameters, TensorProxy tensorProxy, ISensor[] sensors, int observableAttributeTotalSize) { var vecObsSizeBp = brainParameters.VectorObservationSize; var numStackedVector = brainParameters.NumStackedVectorObservations; var totalVecObsSizeT = tensorProxy.shape[tensorProxy.shape.Length - 1]; var totalVectorSensorSize = 0; foreach (var sens in sensors) { if ((sens.GetObservationSpec().Shape.Length == 1)) { totalVectorSensorSize += sens.GetObservationSpec().Shape[0]; } } if (totalVectorSensorSize != totalVecObsSizeT) { var sensorSizes = ""; foreach (var sensorComp in sensors) { if (sensorComp.GetObservationSpec().Shape.Length == 1) { var vecSize = sensorComp.GetObservationSpec().Shape[0]; if (sensorSizes.Length == 0) { sensorSizes = $"[{vecSize}"; } else { sensorSizes += $", {vecSize}"; } } } sensorSizes += "]"; return FailedCheck.Warning( $"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" + $"Sensor sizes: {sensorSizes}." ); } return null; } /// /// Generates failed checks that correspond to inputs shapes incompatibilities between /// the model and the BrainParameters. /// /// /// The Barracuda engine model for loading static parameters /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// Attached sensors /// Sum of the sizes of all ObservableAttributes. /// A IEnumerable of the checks that failed static IEnumerable CheckInputTensorShape( Model model, BrainParameters brainParameters, ISensor[] sensors, int observableAttributeTotalSize) { var failedModelChecks = new List(); var tensorTester = new Dictionary>() { {TensorNames.PreviousActionPlaceholder, CheckPreviousActionShape}, {TensorNames.RandomNormalEpsilonPlaceholder, ((bp, tensor, scs, i) => null)}, {TensorNames.ActionMaskPlaceholder, ((bp, tensor, scs, i) => null)}, {TensorNames.SequenceLengthPlaceholder, ((bp, tensor, scs, i) => null)}, {TensorNames.RecurrentInPlaceholder, ((bp, tensor, scs, i) => null)}, }; foreach (var mem in model.memories) { tensorTester[mem.input] = ((bp, tensor, scs, i) => null); } for (var sensorIndex = 0; sensorIndex < sensors.Length; sensorIndex++) { var sens = sensors[sensorIndex]; if (sens.GetObservationSpec().NumDimensions == 3) { tensorTester[TensorNames.GetObservationName(sensorIndex)] = (bp, tensor, scs, i) => CheckVisualObsShape(tensor, sens); } if (sens.GetObservationSpec().NumDimensions == 2) { tensorTester[TensorNames.GetObservationName(sensorIndex)] = (bp, tensor, scs, i) => CheckRankTwoObsShape(tensor, sens); } if (sens.GetObservationSpec().NumDimensions == 1) { tensorTester[TensorNames.GetObservationName(sensorIndex)] = (bp, tensor, scs, i) => CheckRankOneObsShape(tensor, sens); } } // If the model expects an input but it is not in this list foreach (var tensor in model.GetInputTensors()) { if (!tensorTester.ContainsKey(tensor.name)) { failedModelChecks.Add(FailedCheck.Warning("Model contains an unexpected input named : " + tensor.name )); } else { var tester = tensorTester[tensor.name]; var error = tester.Invoke(brainParameters, tensor, sensors, observableAttributeTotalSize); if (error != null) { failedModelChecks.Add(error); } } } return failedModelChecks; } /// /// Checks that the shape of the Previous Vector Action input placeholder is the same in the /// model and in the Brain Parameters. /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// The tensor that is expected by the model /// Array of attached sensor components (unused). /// Sum of the sizes of all ObservableAttributes (unused). /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. static FailedCheck CheckPreviousActionShape( BrainParameters brainParameters, TensorProxy tensorProxy, ISensor[] sensors, int observableAttributeTotalSize) { var numberActionsBp = brainParameters.ActionSpec.NumDiscreteActions; var numberActionsT = tensorProxy.shape[tensorProxy.shape.Length - 1]; if (numberActionsBp != numberActionsT) { return FailedCheck.Warning("Previous Action Size of the model does not match. " + $"Received {numberActionsBp} but was expecting {numberActionsT}." ); } return null; } /// /// Generates failed checks that correspond to output shapes incompatibilities between /// the model and the BrainParameters. /// /// /// The Barracuda engine model for loading static parameters /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// Array of attached actuator components. /// /// A IEnumerable of error messages corresponding to the incompatible shapes between model /// and BrainParameters. /// static IEnumerable CheckOutputTensorShape( Model model, BrainParameters brainParameters, ActuatorComponent[] actuatorComponents) { var failedModelChecks = new List(); // If the model expects an output but it is not in this list var modelContinuousActionSize = model.ContinuousOutputSize(); var continuousError = CheckContinuousActionOutputShape(brainParameters, actuatorComponents, modelContinuousActionSize); if (continuousError != null) { failedModelChecks.Add(continuousError); } FailedCheck discreteError = null; var modelApiVersion = model.GetVersion(); if (modelApiVersion == (int)ModelApiVersion.MLAgents1_0) { var modelSumDiscreteBranchSizes = model.DiscreteOutputSize(); discreteError = CheckDiscreteActionOutputShapeLegacy(brainParameters, actuatorComponents, modelSumDiscreteBranchSizes); } if (modelApiVersion == (int)ModelApiVersion.MLAgents2_0) { var modelDiscreteBranches = model.GetTensorByName(TensorNames.DiscreteActionOutputShape); discreteError = CheckDiscreteActionOutputShape(brainParameters, actuatorComponents, modelDiscreteBranches); } if (discreteError != null) { failedModelChecks.Add(discreteError); } return failedModelChecks; } /// /// Checks that the shape of the discrete action output is the same in the /// model and in the Brain Parameters. /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// Array of attached actuator components. /// The Tensor of branch sizes. /// /// /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. /// static FailedCheck CheckDiscreteActionOutputShape( BrainParameters brainParameters, ActuatorComponent[] actuatorComponents, Tensor modelDiscreteBranches) { var discreteActionBranches = brainParameters.ActionSpec.BranchSizes.ToList(); foreach (var actuatorComponent in actuatorComponents) { var actionSpec = actuatorComponent.ActionSpec; discreteActionBranches.AddRange(actionSpec.BranchSizes); } int modelDiscreteBranchesLength = modelDiscreteBranches?.length ?? 0; if (modelDiscreteBranchesLength != discreteActionBranches.Count) { return FailedCheck.Warning("Discrete Action Size of the model does not match. The BrainParameters expect " + $"{discreteActionBranches.Count} branches but the model contains {modelDiscreteBranchesLength}." ); } for (int i = 0; i < modelDiscreteBranchesLength; i++) { if (modelDiscreteBranches[i] != discreteActionBranches[i]) { return FailedCheck.Warning($"The number of Discrete Actions of branch {i} does not match. " + $"Was expecting {discreteActionBranches[i]} but the model contains {modelDiscreteBranches[i]} " ); } } return null; } /// /// Checks that the shape of the discrete action output is the same in the /// model and in the Brain Parameters. Tests the models created with the API of version 1.X /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// Array of attached actuator components. /// /// The size of the discrete action output that is expected by the model. /// /// /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. /// static FailedCheck CheckDiscreteActionOutputShapeLegacy( BrainParameters brainParameters, ActuatorComponent[] actuatorComponents, int modelSumDiscreteBranchSizes) { // TODO: check each branch size instead of sum of branch sizes var sumOfDiscreteBranchSizes = brainParameters.ActionSpec.SumOfDiscreteBranchSizes; foreach (var actuatorComponent in actuatorComponents) { var actionSpec = actuatorComponent.ActionSpec; sumOfDiscreteBranchSizes += actionSpec.SumOfDiscreteBranchSizes; } if (modelSumDiscreteBranchSizes != sumOfDiscreteBranchSizes) { return FailedCheck.Warning("Discrete Action Size of the model does not match. The BrainParameters expect " + $"{sumOfDiscreteBranchSizes} but the model contains {modelSumDiscreteBranchSizes}." ); } return null; } /// /// Checks that the shape of the continuous action output is the same in the /// model and in the Brain Parameters. /// /// /// The BrainParameters that are used verify the compatibility with the InferenceEngine /// /// Array of attached actuator components. /// /// The size of the continuous action output that is expected by the model. /// /// If the Check failed, returns a string containing information about why the /// check failed. If the check passed, returns null. static FailedCheck CheckContinuousActionOutputShape( BrainParameters brainParameters, ActuatorComponent[] actuatorComponents, int modelContinuousActionSize) { var numContinuousActions = brainParameters.ActionSpec.NumContinuousActions; foreach (var actuatorComponent in actuatorComponents) { var actionSpec = actuatorComponent.ActionSpec; numContinuousActions += actionSpec.NumContinuousActions; } if (modelContinuousActionSize != numContinuousActions) { return FailedCheck.Warning( "Continuous Action Size of the model does not match. The BrainParameters and ActuatorComponents expect " + $"{numContinuousActions} but the model contains {modelContinuousActionSize}." ); } return null; } } }