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Diffstat (limited to 'src/armnn/backends/ArmComputeTensorUtils.hpp')
-rw-r--r-- | src/armnn/backends/ArmComputeTensorUtils.hpp | 146 |
1 files changed, 146 insertions, 0 deletions
diff --git a/src/armnn/backends/ArmComputeTensorUtils.hpp b/src/armnn/backends/ArmComputeTensorUtils.hpp new file mode 100644 index 0000000000..9a13caf495 --- /dev/null +++ b/src/armnn/backends/ArmComputeTensorUtils.hpp @@ -0,0 +1,146 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// See LICENSE file in the project root for full license information. +// +#pragma once + +#include <armnn/Tensor.hpp> +#include <armnn/DescriptorsFwd.hpp> + +#include <arm_compute/core/ITensor.h> +#include <arm_compute/core/TensorInfo.h> + +#include <boost/cast.hpp> + +namespace armnn +{ +class ITensorHandle; + +namespace armcomputetensorutils +{ + +/// Utility function to map an armnn::DataType to corresponding arm_compute::DataType +arm_compute::DataType GetArmComputeDataType(armnn::DataType dataType); + +/// Utility function used to setup an arm_compute::TensorShape object from an armnn::TensorShape +arm_compute::TensorShape BuildArmComputeTensorShape(const armnn::TensorShape& tensorShape); + +/// Utility function used to setup an arm_compute::ITensorInfo object whose dimensions are based on the given +/// armnn::ITensorInfo +arm_compute::TensorInfo BuildArmComputeTensorInfo(const armnn::TensorInfo& tensorInfo); + +/// Utility function used to setup an arm_compute::PoolingLayerInfo object from an armnn::Pooling2dDescriptor +arm_compute::PoolingLayerInfo BuildArmComputePoolingLayerInfo(const Pooling2dDescriptor& descriptor); + +/// Utility function to setup an arm_compute::NormalizationLayerInfo object from an armnn::NormalizationDescriptor +arm_compute::NormalizationLayerInfo BuildArmComputeNormalizationLayerInfo(const NormalizationDescriptor& desc); + +/// Utility function used to setup an arm_compute::PermutationVector object from an armnn::PermutationVector +arm_compute::PermutationVector BuildArmComputePermutationVector(const armnn::PermutationVector& vector); + +/// Sets up the given ArmCompute tensor's dimensions based on the given ArmNN tensor. +template <typename Tensor> +void BuildArmComputeTensor(Tensor& tensor, const armnn::TensorInfo& tensorInfo) +{ + tensor.allocator()->init(BuildArmComputeTensorInfo(tensorInfo)); +} + +template <typename Tensor> +void InitialiseArmComputeTensorEmpty(Tensor& tensor) +{ + tensor.allocator()->allocate(); +} + +// Helper function to obtain byte offset into tensor data +inline size_t GetTensorOffset(const arm_compute::ITensorInfo& info, + uint32_t batchIndex, + uint32_t channelIndex, + uint32_t y, + uint32_t x) +{ + arm_compute::Coordinates coords; + coords.set(3, boost::numeric_cast<int>(batchIndex)); + coords.set(2, boost::numeric_cast<int>(channelIndex)); + coords.set(1, boost::numeric_cast<int>(y)); + coords.set(0, boost::numeric_cast<int>(x)); + return info.offset_element_in_bytes(coords); +} + +// Helper function to obtain element offset into data buffer representing tensor data (assuming no strides) +inline size_t GetLinearBufferOffset(const arm_compute::ITensorInfo& info, + uint32_t batchIndex, + uint32_t channelIndex, + uint32_t y, + uint32_t x) +{ + const arm_compute::TensorShape& shape = info.tensor_shape(); + uint32_t width = boost::numeric_cast<uint32_t>(shape[0]); + uint32_t height = boost::numeric_cast<uint32_t>(shape[1]); + uint32_t numChannels = boost::numeric_cast<uint32_t>(shape[2]); + return ((batchIndex * numChannels + channelIndex) * height + y) * width + x; +} + +template <typename T> +void CopyArmComputeITensorData(const arm_compute::ITensor& srcTensor, T* dstData) +{ + // if MaxNumOfTensorDimensions is increased, this loop will need fixing + static_assert(MaxNumOfTensorDimensions == 4, "Please update CopyArmComputeITensorData"); + { + const arm_compute::ITensorInfo& info = *srcTensor.info(); + const arm_compute::TensorShape& shape = info.tensor_shape(); + const uint8_t* const bufferPtr = srcTensor.buffer(); + uint32_t width = boost::numeric_cast<uint32_t>(shape[0]); + uint32_t height = boost::numeric_cast<uint32_t>(shape[1]); + uint32_t numChannels = boost::numeric_cast<uint32_t>(shape[2]); + uint32_t numBatches = boost::numeric_cast<uint32_t>(shape[3]); + + for (unsigned int batchIndex = 0; batchIndex < numBatches; ++batchIndex) + { + for (unsigned int channelIndex = 0; channelIndex < numChannels; ++channelIndex) + { + for (unsigned int y = 0; y < height; ++y) + { + // Copy one row from arm_compute tensor buffer to linear memory buffer + // A row is the largest contiguous region we can copy, as the tensor data may be using strides + memcpy(dstData + GetLinearBufferOffset(info, batchIndex, channelIndex, y, 0), + bufferPtr + GetTensorOffset(info, batchIndex, channelIndex, y, 0), + width * sizeof(T)); + } + } + } + } +} + +template <typename T> +void CopyArmComputeITensorData(const T* srcData, arm_compute::ITensor& dstTensor) +{ + // if MaxNumOfTensorDimensions is increased, this loop will need fixing + static_assert(MaxNumOfTensorDimensions == 4, "Please update CopyArmComputeITensorData"); + { + const arm_compute::ITensorInfo& info = *dstTensor.info(); + const arm_compute::TensorShape& shape = info.tensor_shape(); + uint8_t* const bufferPtr = dstTensor.buffer(); + uint32_t width = boost::numeric_cast<uint32_t>(shape[0]); + uint32_t height = boost::numeric_cast<uint32_t>(shape[1]); + uint32_t numChannels = boost::numeric_cast<uint32_t>(shape[2]); + uint32_t numBatches = boost::numeric_cast<uint32_t>(shape[3]); + + for (unsigned int batchIndex = 0; batchIndex < numBatches; ++batchIndex) + { + for (unsigned int channelIndex = 0; channelIndex < numChannels; ++channelIndex) + { + for (unsigned int y = 0; y < height; ++y) + { + // Copy one row from linear memory buffer to arm_compute tensor buffer + // A row is the largest contiguous region we can copy, as the tensor data may be using strides + memcpy(bufferPtr + GetTensorOffset(info, batchIndex, channelIndex, y, 0), + srcData + GetLinearBufferOffset(info, batchIndex, channelIndex, y, 0), + width * sizeof(T)); + } + } + } + } +} + +} // namespace armcomputetensorutils +} // namespace armnn |