public override void Validate(MyValidator validator)
{
ScriptCheckMethod = null;
ScriptShouldStopMethod = null;
CSharpCodeProvider codeProvider = new CSharpCodeProvider();
CompilerParameters parameters = new CompilerParameters()
{
GenerateInMemory = false,
GenerateExecutable = false,
};
parameters.ReferencedAssemblies.Add("GoodAI.Platform.Core.dll");
parameters.ReferencedAssemblies.Add("System.Core.dll"); //for LINQ support
parameters.ReferencedAssemblies.Add("System.Runtime.dll"); //for LINQ support
// TODO: load the xunit dll in Brain Simulator UI from the module directory.
parameters.ReferencedAssemblies.Add("xunit.assert.dll");
parameters.ReferencedAssemblies.Add(Assembly.GetExecutingAssembly().Location);
//Assembly[] loadedAssemblies = AppDomain.CurrentDomain.GetAssemblies();
//IEnumerable<Assembly> openTKAssemblies = loadedAssemblies.Where(x => x.ManifestModule.Name == "xunit.assert.dll");
//if (openTKAssemblies.Count() > 0)
// parameters.ReferencedAssemblies.Add(openTKAssemblies.First().Location);
CompilerResults results = codeProvider.CompileAssemblyFromSource(parameters, Script);
if (results.Errors.HasErrors)
{
string message = "";
foreach (CompilerError error in results.Errors)
{
message += "Line " + error.Line + ": " + error.ErrorText + "\n";
}
validator.AddError(this, "Errors in compiled script:\n" + message);
return;
}
else if (results.CompiledAssembly == null)
{
validator.AddError(this, "Compiled assembly is null.");
return;
}
try
{
Type enclosingType = results.CompiledAssembly.GetType("Runtime.Script");
ScriptCheckMethod = enclosingType.GetMethod("Check");
validator.AssertError(ScriptCheckMethod != null, this, "Check() method not found in compiled script");
ScriptShouldStopMethod = enclosingType.GetMethod("ShouldStop"); // optional, don't check for null
}
catch (Exception e)
{
validator.AddError(this, "Script analysis failed: " + e.GetType().Name + ": " + e.Message);
}
}
private void ValidateRange(MyValidator validator, int value, int valueMin, int valueMax, string valueName)
{
if (value > valueMax)
{
validator.AddError(this, string.Format("{0} cannot be more than {1}.", valueName, valueMax));
}
if (value < valueMin)
{
validator.AddError(this, string.Format("{0} cannot be less than {1}.", valueName, valueMin));
}
}
public override void Validate(MyValidator validator)
{
if (StateInput == null)
{
validator.AddError(this, "StateInput is not connected");
}
else if (StateInput.Count != MyTicTacToeWorld.NO_POSITIONS)
{
validator.AddError(this, "Incorrect length of StateInput, expected 9, found " + StateInput.Count);
}
}
public override void Validate(MyValidator validator)
{
if (Sample == null)
{
validator.AddError(this, "Missing input 'Sample'!");
}
if (Target == null)
{
validator.AddError(this, "Missing input 'Target'!");
}
}
internal override void ValidateMandatory(MyValidator validator)
{
base.ValidateMandatory(validator);
if (LoadOnStart || validator.Simulation.LoadAllNodesData)
{
if (MyMemoryBlockSerializer.TempDataExists(this))
{
validator.AddInfo(this, "Node will load data from temporal storage.");
}
else if (DataFolder != null && DataFolder != String.Empty)
{
validator.AddInfo(this, "Node will load data from user defined folder: " + DataFolder);
}
else if (validator.Simulation.LoadAllNodesData)
{
validator.AddInfo(this, "Node will load data from user defined folder: "
+ validator.Simulation.GlobalDataFolder + "\\" + MyMemoryBlockSerializer.GetNodeFolder(this));
}
else
{
validator.AddError(this, "LoadOnStart is active and no temporal data is available. DataFolder must be defined");
}
}
validator.AssertInfo(!(SaveOnStop || validator.Simulation.SaveAllNodesData), this, "Node will save data to temporal storage before stop.");
foreach (PropertyInfo pInfo in GetInfo().OwnedMemoryBlocks)
{
MyAbstractMemoryBlock mb = (pInfo.GetValue(this) as MyAbstractMemoryBlock);
validator.AssertError(mb.Count >= 0, this, "Size of " + mb.Name + " memory block cannot be negative.");
}
List <PropertyInfo> inputBlocks = GetInfo().InputBlocks;
for (int i = 0; i < inputBlocks.Count; i++)
{
PropertyInfo pInfo = inputBlocks[i];
if (GetAbstractInput(i) != pInfo.GetValue(this))
{
validator.AddError(this, "Incompatible memory block for \"" + pInfo.Name + "\" (" + GetAbstractInput(i).GetType().GenericTypeArguments[0].Name + " != " + pInfo.PropertyType.GenericTypeArguments[0].Name + ")");
}
}
}
public override void Validate(MyValidator validator)
{
ValidateRange(validator, ClearedLinesPerLevel, 1, 1000000000, "ClearedLinesPerLevel");
ValidateRange(validator, AlmostFullLinesAtStart, 0, 15, "AlmostFullLinesAtStart");
if (ActionInput != null)
{
// make sure ActionInput has the required modality
if (ActionInputModality == InputModality.Number && ActionInput.Count != 1)
{
validator.AddError(this, "InputModality is Number. A single number is expected on ActionInput.");
}
else if (ActionInputModality == InputModality.Vector && ActionInput.Count != 6)
{
validator.AddError(this, "InputModality is Vector. A vector of length 6 is expected on ActionInput.");
}
}
}
public override void Validate(MyValidator validator)
{
base.Validate(validator);
if (!AreParametersValid())
{
validator.AddError(this, "Current parameter values or their combination are not valid.");
}
}
public override void Validate(MyValidator validator)
{
base.Validate(validator);
if (MotivationInput.Count != 1)
{
validator.AddError(this, "MotivationInput requires size of 1");
}
}
public override void Validate(MyValidator validator)
{
base.Validate(validator);
if ((InitMNIST.TrainingExamplesPerDigit < 1) || (InitMNIST.TrainingExamplesPerDigit > 7000) ||
(InitMNIST.TestExamplesPerDigit < 1) || (InitMNIST.TestExamplesPerDigit > 7000))
{
validator.AddError(this, "The value of ExamplesPerDigit properties of the Init task have to be in the interval <1, 7000>");
}
}
public override void Validate(MyValidator validator)
{
for (int i = 0; i < InputBranches; i++)
{
MyMemoryBlock <float> ai = GetInput(i);
if (ai == null)
{
validator.AddError(this, string.Format("Missing input {0}.", i));
}
}
}
public override void Validate(MyValidator validator)
{
validator.AssertError(MemorySize > 0, this, "Memory can't be empty.");
if (Values == null || Indices == null)
{
validator.AddError(this, "Missing input is suspicious.");
return;
}
validator.AssertError(Values.Count == Indices.Count, this, "The input vector sizes must be the same.");
validator.AssertError(Values.Count % SymbolSize == 0, this, "The input vector size must be a multiple of SymbolSize.");
}
public override void Validate(MyValidator validator)
{
base.Validate(validator);
if (ParentNetwork == null)
{
validator.AddError(this, "LSTM layer needs to be in a neural network group");
}
if (LearningTasks == LearningTasksType.BPTT)
{
if (!inputToTemporalTask.Enabled)
{
validator.AddError(this, "BPTT requires Transform Input Task to be enabled");
}
}
else if (LearningTasks == LearningTasksType.RTRL)
{
if (inputToTemporalTask.Enabled)
{
validator.AddError(this, "RTRL requires Transform Input Task to be disabled");
}
}
}
public override void Validate(MyValidator validator)
{
switch (Operation)
{
case MyJoinOperation.StackInputs:
return;
case MyJoinOperation.DistanceSquared:
case MyJoinOperation.CosineDistance:
case MyJoinOperation.DotProduct:
validator.AssertError(InputBranches == 2, this, "Two operands are needed for distance measures");
break;
case MyJoinOperation.MatMultiplication:
bool is_correct = Input0ColHint == (Input1Count / Input1ColHint);
// if (Input1ColHint==1) /// BrainSim. bug for Nx1 vector, column hint is one, although it should be N...
// is_correct = Input0ColHint == Input1Count;
validator.AssertError(is_correct, this, "# of columns in Mat1 needs to correspond to # of rows in Mat2!");
break;
case MyJoinOperation.AddToIdcs:
case MyJoinOperation.AddToIdcs_Normalize:
validator.AssertError(InputBranches >= 3, this, "Must provide the Target vector, Source vector and the idcs as the first three inputs");
validator.AssertError(GetInputSize(1) == GetInputSize(2), this, "Dimensions of the Source vector and idcs must be the same");
validator.AssertError(GetInputSize(0) >= GetInputSize(1), this, "Target vector must be bigger than Source vector");
return;
case MyJoinOperation.GatherFromIdcs:
validator.AssertError(InputBranches >= 2, this, "Must provide the Target vector and the idcs as the first two inputs");
validator.AssertError(GetInputSize(0) >= GetInputSize(1), this, "Target vector must be bigger than the idcs");
return;
default:
validator.AssertError(InputBranches >= 2, this, "Operation needs at least two operands");
break;
}
for (int i = 0; i < InputBranches; i++)
{
MyMemoryBlock <float> ai = GetInput(i);
if (ai == null)
{
validator.AddError(this, string.Format("Missing input {0}.", i));
}
else if (InputBranches > 2) // Two inputs are allowed to be of variable size
{
validator.AssertError(ai.Count == OutputSize, this, "Operand size differs from output size");
}
}
}
protected bool WorldSourcesExist(string[] paths, MyValidator validator)
{
bool exist = true;
foreach (string path in paths)
{
if (!File.Exists(path))
{
validator.AddError(this, string.Format("Missing dataset file \"{0}\". Check log (INFO level) for further information.", Path.GetFileName(path)));
exist = false;
}
}
return(exist);
}
public override void Validate(MyValidator validator)
{
base.ValidateMandatory(validator);
base.Validate(validator);
Children.ForEach(node =>
{
try
{
node.ValidateMandatory(validator);
node.Validate(validator);
}
catch (Exception e)
{
MyLog.ERROR.WriteLine("Exception occured while validating " + node.Name + ": " + e.Message);
validator.AddError(node, "Exception occured while validating: " + e.Message);
}
});
}
private string AppendGeneratedCode(string script, MyValidator validator)
{
string completeScript = script;
int location = script.IndexOf(GENERATED_CODE_LABEL);
if (location >= 0)
{
completeScript = script.Substring(0, location)
+ GenerateVariablesCode()
+ script.Substring(location);
}
else
{
validator.AddError(this, "Script generator: label \"" + GENERATED_CODE_LABEL + "\" not found. No generated code available.");
}
return(completeScript);
}
private void ValidateHiddenVectorUser(MyValidator validator)
{
if (m_engineParams.HiddenVectorUserParsed != null)
{
// must have a correct format and must be empty or contain HiddenVectorLength numerical entries;
// the number of unique entries must be less or equal to the number of colours and it must match the CanRepeatColors property
if (m_engineParams.HiddenVectorUserParsed.Length != HiddenVectorLength)
{
validator.AddError(this, "Number of elements specified in HiddenVectorUser must match HiddenVectorLength.");
}
if (!CanRepeatColors)
{
HashSet <int> userPicked = new HashSet <int>(m_engineParams.HiddenVectorUserParsed);
if (userPicked.Count != m_engineParams.HiddenVectorUserParsed.Length)
{
validator.AddError(this, "CanRepeatColors is false, but HiddenVectorUser contains repeating colors.");
}
}
// check color codes in user input
for (int i = 0; i < m_engineParams.HiddenVectorUserParsed.Length; i++)
{
if (m_engineParams.HiddenVectorUserParsed[i] >= NumberOfColors)
{
validator.AddError(this, string.Format("HiddenVectorUser must not contain color codes greater or equal to NumberOfColors ({0}).",
NumberOfColors));
break;
}
if (m_engineParams.HiddenVectorUserParsed[i] < 0)
{
validator.AddError(this, string.Format("HiddenVectorUser must not contain color codes less than 0."));
break;
}
}
}
if (GuessInput != null && HiddenVectorLength != GuessInput.Count)
{
validator.AddError(this, "Number of elements in the GuessInput memory block must match HiddenVectorLength.");
}
if (!CanRepeatColors && NumberOfColors < HiddenVectorLength)
{
validator.AddError(this, "Repeating of colors in the hidden vector is forbidden: NumberOfColors cannot be lower than HiddenVectorLength.");
}
}
public override void Validate(MyValidator validator)
{
validator.AssertError(ImageInput != null, this, "No input image available");
validator.AssertError(ImageInput.Dims.Rank >= 2, this, "Input image should have rank at least 2 (2 dimensions)");
if (!validator.ValidationSucessfull)
{
return;
}
if (Execute.Enabled)
{
if (XCrop == null && YCrop == null)
{
validator.AddError(this, "If the MaskByCoordinates is enabled, at least one of the XCrop and YCrop should be connected.");
}
}
else if (ProbabilisticMask.Enabled)
{
if (MaskProbabilityInput == null)
{
validator.AddError(this, "If the ProbabilisticMask is enabled, the MaskProbabilityInput has to be connected and have size 1");
}
if (RandomNumbersInput == null)
{
validator.AddError(this, "If the ProbabilisticMask is enabled, the RandomNumbersInput with the same count as the Image Input " +
"has to be connected. Uniform distribution from <0,1> is expected.");
}
}
if (MaskValuesInput != null && ImageInput != null && MaskValuesInput.Count != ImageInput.Count)
{
validator.AddError(this, "MaskValuesInput.Count != Image.Count");
}
if (RandomNumbersInput != null && ImageInput != null && RandomNumbersInput.Count != ImageInput.Count)
{
validator.AddError(this, "RandomNumbersInput.Count has to be equal to ImageInput.count");
}
if (MaskProbabilityInput != null && MaskProbabilityInput.Count != 1)
{
validator.AddError(this, "MaskProbabilityInput.Count has to be 1");
}
}
public void Compile(string script, MyValidator validator)
{
if (m_node.Language != this.Language)
{
throw new ArgumentException("Language is not supported (" + this.Language + " only): " + m_node.Language);
}
m_methods.Clear();
CSharpCodeProvider codeProvider = new CSharpCodeProvider();
CompilerParameters parameters = new CompilerParameters()
{
GenerateInMemory = false,
GenerateExecutable = false,
};
parameters.ReferencedAssemblies.Add("GoodAI.Platform.Core.dll");
parameters.ReferencedAssemblies.Add("System.Core.dll"); //for LINQ support
// add all loaded dll modules to be accessible also from the C# node script
foreach (FileInfo assemblyFile in MyConfiguration.ListModules())
{
parameters.ReferencedAssemblies.Add(assemblyFile.FullName);
}
parameters.ReferencedAssemblies.Add(Assembly.GetExecutingAssembly().Location);
Assembly[] loadedAssemblies = AppDomain.CurrentDomain.GetAssemblies();
IEnumerable <Assembly> openTKAssemblies = loadedAssemblies.Where(x => x.ManifestModule.Name == "OpenTK.dll").ToList();
if (openTKAssemblies.Any())
{
parameters.ReferencedAssemblies.Add(openTKAssemblies.First().Location);
}
CompilerResults results = codeProvider.CompileAssemblyFromSource(parameters, script);
Assembly compiledAssembly = null;
if (results.Errors.HasErrors)
{
string message = "";
foreach (CompilerError error in results.Errors)
{
message += "\nLine " + error.Line + ": " + error.ErrorText;
}
validator.AddError(m_node, "Errors in compiled script:" + message);
}
else
{
compiledAssembly = results.CompiledAssembly;
}
if (compiledAssembly != null)
{
try
{
Type enclosingType = compiledAssembly.GetType("Runtime.Script");
Type methodEnum = typeof(TMethodEnum);
foreach (string methodName in methodEnum.GetEnumNames())
{
MethodInfo method = enclosingType.GetMethod(methodName);
if (method != null)
{
m_methods[methodName] = method;
}
else
{
validator.AddError(m_node, methodName + "() method not found in compiled script");
}
}
}
catch (Exception e)
{
validator.AddError(m_node, "Script analysis failed: " + e.GetType().Name + ": " + e.Message);
}
}
}
public override void Validate(MyValidator validator)
{
switch (Operation)
{
case MyJoinOperation.StackInputs:
return;
case MyJoinOperation.DistanceSquared:
case MyJoinOperation.CosineDistance:
case MyJoinOperation.DotProduct:
validator.AssertError(InputBranches == 2, this, "Two operands are needed for distance measures");
break;
case MyJoinOperation.MatMultiplication:
bool is_correct = Input0ColHint == (Input1Count / Input1ColHint);
// if (Input1ColHint==1) /// BrainSim. bug for Nx1 vector, column hint is one, although it should be N...
// is_correct = Input0ColHint == Input1Count;
validator.AssertError(is_correct, this, "# of columns in Mat1 needs to correspond to # of rows in Mat2!");
break;
case MyJoinOperation.AddToIdcs:
case MyJoinOperation.AddToIdcs_Normalize:
validator.AssertError(InputBranches >= 3, this, "Must provide the Target vector, Source vector and the idcs as the first three inputs");
validator.AssertError(GetInputSize(1) == GetInputSize(2), this, "Dimensions of the Source vector and idcs must be the same");
validator.AssertError(GetInputSize(0) >= GetInputSize(1), this, "Target vector must be bigger than Source vector");
return;
case MyJoinOperation.GatherFromIdcs:
validator.AssertError(InputBranches >= 2, this, "Must provide the Target vector and the idcs as the first two inputs");
validator.AssertError(GetInputSize(0) >= GetInputSize(1), this, "Target vector must be bigger than the idcs");
return;
default:
validator.AssertError(InputBranches >= 2, this, "Operation needs at least two operands");
break;
}
TensorDimensions firstInputDimensions = null;
bool firstInputDimensionsRankOne = false;
for (int i = 0; i < InputBranches; i++)
{
MyMemoryBlock <float> ai = GetInput(i);
if (ai == null)
{
validator.AddError(this, $"Missing input {i}.");
return;
}
if (InputBranches > 2) // Two inputs are allowed to be of variable size
{
validator.AssertError(ai.Count == OutputSize, this, $"Operand #{i} size differs from output size");
}
if (firstInputDimensions == null)
{
firstInputDimensions = ai.Dims;
firstInputDimensionsRankOne = IsRankOne(firstInputDimensions);
}
var bothDimensionsRankOne = firstInputDimensionsRankOne && IsRankOne(ai.Dims);
if (firstInputDimensions.Rank != ai.Dims.Rank && !bothDimensionsRankOne)
{
// TODO(Premek): replace warning with error when the check gets smart enough
validator.AddWarning(this, $"Incompatible input ranks (input #{i}).");
}
}
}