CNTK/Source/CNTKv2LibraryDll/Value.cpp

226 строки
9.9 KiB
C++

//
// Copyright (c) Microsoft. All rights reserved.
// Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
//
#include "stdafx.h"
#ifdef _WIN32
#define _SCL_SECURE_NO_WARNINGS
#endif
#include "CNTKLibrary.h"
#include "Utils.h"
#include "Value.h"
#include "Function.h"
namespace CNTK
{
Value::Value(const NDArrayViewPtr& data)
: Value(data, nullptr)
{
}
Value::Value(const NDArrayViewPtr& data, const NDMaskPtr& mask)
: m_data(data), m_mask(mask)
{
if (mask != nullptr)
{
auto dataShape = data->Shape();
auto maskShape = mask->Shape();
if (maskShape.Rank() > dataShape.Rank())
InvalidArgument("The rank (%d) of the mask of a Value object cannot exceed the rank (%d) of the data NDArrayView object", (int)maskShape.Rank(), (int)dataShape.Rank());
if (dataShape.SubShape(dataShape.Rank() - maskShape.Rank()) != maskShape)
InvalidArgument("Invalid Value object; the data and mask are incompatible. The trailing dimensions of the data with shape %S do not match the dimensions of the mask with shape %S", AsStringForErrorReporting(dataShape).c_str(), AsStringForErrorReporting(maskShape).c_str());
}
}
template <typename T>
static NDMaskPtr CreateMask(size_t numElementsPerSample, const std::vector<std::vector<T>>& sequences, const DeviceDescriptor& device)
{
size_t numSequences = sequences.size();
std::vector<size_t> sequenceLengths(numSequences);
size_t maxSequenceLength = 0;
bool needsMask = false;
for (size_t i = 0; i < numSequences; ++i)
{
sequenceLengths[i] = sequences[i].size() / numElementsPerSample;
if (maxSequenceLength < sequenceLengths[i])
maxSequenceLength = sequenceLengths[i];
if ((i > 0) && (sequenceLengths[i - 1] != sequenceLengths[i]))
needsMask = true;
}
// If needed, create a mask to account for variability in lengths of specified sequences
NDMaskPtr deviceValueMask;
if (needsMask)
{
NDShape valueMaskShape = { maxSequenceLength, numSequences };
deviceValueMask = MakeSharedObject<NDMask>(valueMaskShape, device);
for (size_t i = 0; i < numSequences; ++i)
{
deviceValueMask->MarkSequenceBegin({0, i});
deviceValueMask->InvalidateSection({ sequenceLengths[i], i }, { NDShape::InferredDimension, 1 });
}
}
return deviceValueMask;
}
template <typename ElementType>
/*static*/ ValuePtr Value::Create(size_t vocabularySize, const std::vector<std::vector<size_t>>& oneHotSequences, const DeviceDescriptor& device, bool readOnly/* = false*/)
{
NDMaskPtr deviceValueMask = CreateMask(1, oneHotSequences, device);
size_t maxSequenceLength = (deviceValueMask == nullptr) ? oneHotSequences[0].size() : deviceValueMask->Shape()[0];
size_t numSequences = oneHotSequences.size();
NDShape sampleShape = { vocabularySize };
NDShape valueDataShape = sampleShape.AppendShape({ maxSequenceLength, numSequences });
size_t numCSCCols = valueDataShape.SubShape(1).TotalSize() + 1;
std::vector<SparseIndexType> colStarts(numCSCCols);
std::vector<ElementType> nonZeroValues;
std::vector<SparseIndexType> rowIndices;
for (size_t i = 0; i < numSequences; ++i)
{
size_t currentSequenceLength = oneHotSequences[i].size();
size_t j = 0;
for (; j < currentSequenceLength; ++j)
{
colStarts[(i * maxSequenceLength) + j] = (SparseIndexType)nonZeroValues.size();
nonZeroValues.push_back(1);
rowIndices.push_back((SparseIndexType)(oneHotSequences[i][j]));
}
for (; j < maxSequenceLength; ++j)
colStarts[(i * maxSequenceLength) + j] = (SparseIndexType)(nonZeroValues.size());
}
colStarts[numSequences * maxSequenceLength] = (SparseIndexType)(nonZeroValues.size());
NDArrayViewPtr deviceValueData = MakeSharedObject<NDArrayView>(valueDataShape, colStarts.data(), rowIndices.data(), nonZeroValues.data(), nonZeroValues.size(), device, readOnly);
return MakeSharedObject<Value>(deviceValueData, deviceValueMask);
}
template <typename ElementType>
/*static*/ ValuePtr Value::Create(const NDShape& sampleShape, const std::vector<std::vector<ElementType>>& sequences, const DeviceDescriptor& device, bool readOnly/* = false*/)
{
size_t numElementsPerSample = sampleShape.TotalSize();
NDMaskPtr deviceValueMask = CreateMask(numElementsPerSample, sequences, device);
size_t maxSequenceLength = (deviceValueMask == nullptr) ? sequences[0].size() : deviceValueMask->Shape()[0];
size_t numSequences = sequences.size();
NDShape valueDataShape = sampleShape.AppendShape({ maxSequenceLength, numSequences });
NDArrayViewPtr valueData = MakeSharedObject<NDArrayView>(AsDataType<ElementType>(), valueDataShape, DeviceDescriptor::CPUDevice());
ElementType* dataBuffer = valueData->WritableDataBuffer<ElementType>();
for (size_t i = 0; i < numSequences; ++i)
std::copy(sequences[i].data(), sequences[i].data() + sequences[i].size(), dataBuffer + (maxSequenceLength * i * numElementsPerSample));
NDArrayViewPtr deviceValueData;
if (device == DeviceDescriptor::CPUDevice())
{
if (readOnly)
deviceValueData = valueData->Alias(true);
else
deviceValueData = valueData;
}
else
{
deviceValueData = MakeSharedObject<NDArrayView>(AsDataType<ElementType>(), valueDataShape, device);
deviceValueData->CopyFrom(*valueData);
if (readOnly)
deviceValueData = deviceValueData->Alias(true);
}
return MakeSharedObject<Value>(deviceValueData, deviceValueMask);
}
/*virtual*/ Value::~Value()
{
}
/*virtual*/ NDArrayViewPtr Value::Data() const
{
// TODO: Check if this is a derived type and throw an exception in that case
return m_data;
}
/*virtual*/ NDMaskPtr Value::Mask() const
{
// TODO: Check if this is a derived type and throw an exception in that case
return m_mask;
}
/*virtual*/ ValuePtr Value::DeepClone(bool readOnly/* = false*/) const
{
// TODO: Check if this is a derived type and throw an exception in that case
return MakeSharedObject<Value>(Data()->DeepClone(readOnly), (Mask() != nullptr) ? Mask()->DeepClone() : nullptr);
}
/*virtual*/ ValuePtr Value::Alias(bool readOnly/* = false*/) const
{
// TODO: Check if this is a derived type and throw an exception in that case
return MakeSharedObject<Value>(Data()->Alias(readOnly), (Mask() != nullptr) ? Mask()->Alias() : nullptr);
}
/*virtual*/ void Value::CopyFrom(const Value& source)
{
// TODO: Check if this is a derived type and throw an exception in that case
Data()->CopyFrom(*source.Data());
if ((Mask() == nullptr) && (source.Mask() != nullptr))
InvalidArgument("Value::CopyFrom: Invalid source object; Cannot copy a Value with a mask into 'this' Value that does not have a mask.");
if (source.Mask() != nullptr)
Mask()->CopyFrom(*source.Mask());
else
{
if (Mask() != nullptr)
{
// Clear the mask
Mask()->Clear();
}
}
}
void PackedValue::Unpack() const
{
if (m_packedDataLayout && (m_packedDataLayout->GetNumTimeSteps() != 1) && (m_packedDataLayout->GetNumSequences() != 1) && Internal::IsAutomaticUnpackingOfPackedValuesDisabled())
LogicError("PackedValue::Unpack: Automatic unpacking of PackedValue objects is disabled");
if (m_isPacked)
{
ValuePtr valueObject;
auto dataType = m_packedData->GetDataType();
switch (dataType)
{
case DataType::Float:
valueObject = CompositeFunction::GetValueObjectFromCNTKImplMatrixAndMBLayout(m_sampleShape, *(m_packedData->GetMatrix<float>()), m_packedDataLayout, m_isReadOnly);
break;
case DataType::Double:
valueObject = CompositeFunction::GetValueObjectFromCNTKImplMatrixAndMBLayout(m_sampleShape, *(m_packedData->GetMatrix<double>()), m_packedDataLayout, m_isReadOnly);
break;
default:
LogicError("Unsupported DataType %s", DataTypeName(dataType));
}
m_data = valueObject->Data();
m_mask = valueObject->Mask();
m_packedData = nullptr;
m_packedDataLayout = nullptr;
m_isPacked = false;
if (m_unpackedShape != m_data->Shape())
LogicError("The computed unpacked shape of the PackedValue object does not match the actual Data NDArrayView's shape after unpacking");
}
}
// Explicit template instantiations
template /*static*/ CNTK_API ValuePtr Value::Create<float>(const NDShape& sampleShape, const std::vector<std::vector<float>>& sequences, const DeviceDescriptor& device, bool readOnly/* = false*/);
template /*static*/ CNTK_API ValuePtr Value::Create<double>(const NDShape& sampleShape, const std::vector<std::vector<double>>& sequences, const DeviceDescriptor& device, bool readOnly/* = false*/);
template /*static*/ CNTK_API ValuePtr Value::Create<float>(size_t vocabSize, const std::vector<std::vector<size_t>>& oneHotSequences, const DeviceDescriptor& device, bool readOnly/* = false*/);
template /*static*/ CNTK_API ValuePtr Value::Create<double>(size_t vocabSize, const std::vector<std::vector<size_t>>& oneHotSequences, const DeviceDescriptor& device, bool readOnly/* = false*/);
}