void DoCommand(const ConfigParameters& configRoot)
{
ConfigArray command = configRoot("command", "train");
ConfigParameters config = configRoot(command[0]);
ConfigParameters readerConfig(config("reader"));
readerConfig.Insert("traceLevel", config("traceLevel", "0"));
ConfigArray minibatchSize = config("minibatchSize", "256");
intargvector mbSizeArr = minibatchSize;
size_t mbSize = 20000; // mbSizeArr[0];
size_t epochSize = config("epochSize", "0");
if (epochSize == 0)
{
epochSize = requestDataSize;
}
ConfigParameters configFeatures = readerConfig(L"features");
size_t dimFeatures = configFeatures("dim");
ConfigParameters configLabels = readerConfig(L"labels");
size_t dimLabels = configLabels("labelDim");
ConfigParameters configSgd = config("SGD");
std::wstring modelPath = configSgd("modelPath");
StreamMinibatchInputs inputMatrices;
StreamMinibatchInputs outputMatrices;
std::wstring inputName = L"features";
std::wstring outputName = L"CE.BFF.FF.P";
int deviceId = 0;
auto matrix = make_shared<Matrix<ElemType>>(dimFeatures, mbSize, deviceId);
MBLayoutPtr pMBLayout = make_shared<MBLayout>();
inputMatrices.AddInput(inputName, matrix, pMBLayout, TensorShape(dimFeatures));
outputMatrices.AddInput(outputName, make_shared<Matrix<ElemType>>(dimLabels, mbSize, deviceId), pMBLayout, TensorShape(dimLabels));
std::map<std::wstring, std::vector<ElemType>*> input;
std::map<std::wstring, std::vector<ElemType>*> output;
std::vector<ElemType>* arr = input[inputName] = new std::vector<ElemType>(dimFeatures * mbSize);
output[outputName] = new std::vector<ElemType>(dimLabels * mbSize);
Eval<ElemType> eval(config);
auto dataReader = make_shared<DataReader>(readerConfig);
eval.CreateNetwork(Microsoft::MSR::CNTK::ToLegacyString(Microsoft::MSR::CNTK::ToUTF8(modelPath)));
dataReader->StartMinibatchLoop(mbSize, 0, inputMatrices.GetStreamDescriptions(), epochSize);
eval.StartEvaluateMinibatchLoop(outputName);
while (dataReader->GetMinibatch(inputMatrices))
{
void* data = (void*) arr->data();
size_t dataSize = arr->size() * sizeof(ElemType);
void* mat = &(*matrix)(0, 0);
size_t matSize = matrix->GetNumElements() * sizeof(ElemType);
memcpy_s(data, dataSize, mat, matSize);
eval.Evaluate(input, output);
}
}
void TestReader(const ConfigParameters& configBase)
{
// int nonexistant = configBase("nonexistant"); // use to test global exception handler
ConfigParameters config(configBase("mnistTest"));
ConfigParameters readerConfig(config("reader"));
readerConfig.Insert("traceLevel", config("traceLevel", "0"));
size_t mbSize = config("minibatchSize");
size_t epochSize = config("epochSize", "0");
if (epochSize == 0)
{
epochSize = requestDataSize;
}
DataReader dataReader(readerConfig);
// get names of features and labels
std::vector<std::wstring> featureNames;
std::vector<std::wstring> labelNames;
GetFileConfigNames(readerConfig, featureNames, labelNames);
// setup minibatch matrices
int deviceId = 0;
auto featuresMatrix = make_shared<Matrix<ElemType>>(deviceId);
auto labelsMatrix = make_shared<Matrix<ElemType>>(deviceId);
MBLayoutPtr pMBLayout = make_shared<MBLayout>();
StreamMinibatchInputs matrices;
matrices.AddInput(featureNames[0], featuresMatrix, pMBLayout, TensorShape());
matrices.AddInput(labelNames[0], labelsMatrix , pMBLayout, TensorShape());
auto start = std::chrono::system_clock::now();
int epochs = config("maxEpochs");
epochs *= 2;
for (int epoch = 0; epoch < epochs; epoch++)
{
dataReader.StartMinibatchLoop(mbSize, epoch, epochSize);
int i = 0;
while (dataReader.GetMinibatch(matrices))
{
Matrix<ElemType>& features = matrices.GetInputMatrix<ElemType>(featureNames[0]);
Matrix<ElemType>& labels = matrices.GetInputMatrix<ElemType>(labelNames[0]);
if (labels.GetNumRows() == 0)
{
fprintf(stderr, "%4d: features dim: %lu x %lu - [%.8g, %.8g, ...]\n", i++, features.GetNumRows(), features.GetNumCols(), features(0, 0), features(0, 1));
}
else
{
fprintf(stderr, "%4d: features dim: %lu x %lu - [%.8g, %.8g, ...] label dim: %lu x %lu - [%d, %d, ...]\n", i++, features.GetNumRows(), features.GetNumCols(), features(0, 0), features(0, 1), labels.GetNumRows(), labels.GetNumCols(), (int) labels(0, 0), (int) labels(0, 1));
}
}
}
auto end = std::chrono::system_clock::now();
auto elapsed = end - start;
fprintf(stderr, "%f seconds elapsed", (float) (std::chrono::duration_cast<std::chrono::milliseconds>(elapsed).count()) / 1000);
}
