public UnorderedMapVariableValuePtr GetVariableValueMapAsCNTKUnorderedMap(Minibatch batch)
{
var arguments = GetVariableValueMap(batch);
var map = new UnorderedMapVariableValuePtr();
foreach (var entry in arguments)
{
map.Add(entry.Key, entry.Value);
}
return(map);
}
public static void Evaluate(this Function func, Dictionary<Variable, Value> arguments, Dictionary<Variable, Value> outputs, DeviceDescriptor computeDevice)
{
// Evaluate the rootFunction.
var argMap = new UnorderedMapVariableValuePtr();
foreach (var p in arguments)
{
argMap.Add(p.Key, p.Value);
}
var outMap = new UnorderedMapVariableValuePtr();
foreach (var p in outputs)
{
outMap.Add(p.Key, p.Value);
}
func.Evaluate(argMap, outMap, computeDevice);
foreach (var p in outMap)
{
outputs[p.Key] = p.Value;
}
}
public static void EvaluateV2ModelUsingNDView()
{
// Load the model
var myFunc = Function.LoadModel("z.model");
// Ouput funciton info.
OutputFunctionInfo(myFunc);
// prepare input for evaluation
uint numOfSamples = 1;
// The z.model has only one input
var inputVar = myFunc.Arguments.Single();
// Todo: get size directly from inputVar.
uint numOfInputData = inputVar.Shape.TotalSize * numOfSamples;
float[] inputData = new float[numOfInputData];
for (uint i = 0; i < numOfInputData; ++i)
{
inputData[i] = (float)(i % 255);
}
// Todo: create value directly from data.
var dynamicAxisShape = new SizeTVector()
{
1, numOfSamples
};
var inputShape = inputVar.Shape.AppendShape(new NDShape(dynamicAxisShape));
var inputNDArrayView = new NDArrayView(inputShape, inputData, numOfInputData, DeviceDescriptor.CPUDevice);
var inputValue = new Value(inputNDArrayView);
// Create input map
// Todo: create a Dictionary wrapper?
var inputMap = new UnorderedMapVariableValuePtr();
inputMap.Add(inputVar, inputValue);
// The z.model has only one output.
var outputVar = myFunc.Output;
var outputShape = outputVar.Shape.AppendShape(new NDShape(dynamicAxisShape));
// Create output buffer
// Todo: use the system created buffer?
uint numOfOutputData = outputVar.Shape.TotalSize * numOfSamples;
float[] outputData = new float[numOfOutputData];
for (uint i = 0; i < numOfOutputData; ++i)
{
outputData[i] = (float)0.0;
}
var outputNDArrayView = new NDArrayView(outputShape, outputData, numOfOutputData, DeviceDescriptor.CPUDevice);
var outputValue = new Value(outputNDArrayView);
// Create ouput map
var outputMap = new UnorderedMapVariableValuePtr();
outputMap.Add(outputVar, outputValue);
// Evalaute
// Todo: test on GPUDevice()?
myFunc.Evaluate(inputMap, outputMap, DeviceDescriptor.CPUDevice);
// Output results
Console.WriteLine("Evaluation results:");
for (uint i = 0; i < numOfOutputData; ++i)
{
Console.WriteLine(outputData[i]);
}
}
public static void EvaluateUsingCreateValue()
{
// Load the model
var myFunc = Function.LoadModel("01_OneHidden");
// Ouput funciton info.
OutputFunctionInfo(myFunc);
// prepare input for evaluation
uint numOfSamples = 1;
const string inputNodeName = "features";
var inputVar = myFunc.Arguments.Where(variable => string.Equals(variable.Name, inputNodeName)).Single();
// Todo: get size directly from inputVar.
uint numOfInputData = inputVar.Shape.TotalSize;
var inputData = new List <float>();
for (uint i = 0; i < numOfInputData; ++i)
{
inputData.Add(i % 255);
}
var inputVector = new FloatVector(inputData);
var data = new FloatVectorVector()
{
inputVector
};
// Create value directly from data.
var inputValue = Value.CreateDenseFloat(inputVar.Shape, data, DeviceDescriptor.CPUDevice);
// Create input map
// Todo: create a Dictionary wrapper?
var inputMap = new UnorderedMapVariableValuePtr();
inputMap.Add(inputVar, inputValue);
// Prepare output
const string outputNodeName = "out.z_output";
var outputVar = myFunc.Outputs.Where(variable => string.Equals(variable.Name, outputNodeName)).Single();
// Create ouput map. Using null as Value to indicate using system allocated memory.
var outputMap = new UnorderedMapVariableValuePtr();
outputMap.Add(outputVar, null);
// Evalaute
// Todo: test on GPUDevice()?
myFunc.Evaluate(inputMap, outputMap, DeviceDescriptor.CPUDevice);
// Get output value after evaluation
var outputValue = outputMap[outputVar];
var outputNDArrayView = outputValue.Data();
var dynamicAxisShape = new SizeTVector()
{
1, numOfSamples
};
var outputShape = outputVar.Shape.AppendShape(new NDShape(dynamicAxisShape));
// Copy the data from the output buffer.
// Todo: directly access the data in output buffer if it is on CPU?
uint numOfOutputData = outputNDArrayView.Shape().TotalSize;
float[] outputData = new float[numOfOutputData];
var cpuOutputNDArrayView = new NDArrayView(outputShape, outputData, numOfOutputData, DeviceDescriptor.CPUDevice);
cpuOutputNDArrayView.CopyFrom(outputNDArrayView);
// Output results
Console.WriteLine("Evaluation results:");
for (uint i = 0; i < numOfOutputData; ++i)
{
Console.WriteLine(outputData[i]);
}
}
public static void EvaluateUsingSystemAllocatedMemory()
{
// Load the model
var myFunc = Function.LoadModel("z.model");
// Ouput funciton info.
OutputFunctionInfo(myFunc);
// prepare input for evaluation
uint numOfSamples = 1;
// Only one input for the model.
var inputVar = myFunc.Arguments.First();
// Todo: get size directly from inputVar.
uint numOfInputData = inputVar.Shape.TotalSize * numOfSamples;
float[] inputData = new float[numOfInputData];
for (uint i = 0; i < numOfInputData; ++i)
{
inputData[i] = (float)(i % 255);
}
// Todo: create value directly from data.
var dynamicAxisShape = new SizeTVector()
{
1, numOfSamples
};
var inputShape = inputVar.Shape.AppendShape(new NDShape(dynamicAxisShape));
var inputNDArrayView = new NDArrayView(inputShape, inputData, numOfInputData, DeviceDescriptor.CPUDevice);
var inputValue = new Value(inputNDArrayView);
// Create input map
// Todo: create a Dictionary wrapper?
var inputMap = new UnorderedMapVariableValuePtr();
inputMap.Add(inputVar, inputValue);
// Prepare output. The model has only one output.
var outputVar = myFunc.Output;
// Create ouput map. Using null as Value to indicate using system allocated memory.
var outputMap = new UnorderedMapVariableValuePtr();
outputMap.Add(outputVar, null);
// Evalaute
// Todo: test on GPUDevice()?
myFunc.Evaluate(inputMap, outputMap, DeviceDescriptor.CPUDevice);
// Get output value after evaluation
var outputValue = outputMap[outputVar];
var outputNDArrayView = outputValue.Data();
var outputShape = outputVar.Shape.AppendShape(new NDShape(dynamicAxisShape));
// Copy the data from the output buffer.
// Todo: directly access the data in output buffer if it is on CPU?
uint numOfOutputData = outputNDArrayView.Shape().TotalSize;
float[] outputData = new float[numOfOutputData];
var cpuOutputNDArrayView = new NDArrayView(outputShape, outputData, numOfOutputData, DeviceDescriptor.CPUDevice);
cpuOutputNDArrayView.CopyFrom(outputNDArrayView);
// Output results
Console.WriteLine("Evaluation results:");
for (uint i = 0; i < numOfOutputData; ++i)
{
Console.WriteLine(outputData[i]);
}
}