MLCE-77 Depthwise Convolution with depth multiplier > 1 doesn't work
* Unified ArmNN's weight format to [ M, I, H, W ] for the depthwise convolution
* Added conversion utilities to permute/reshape the weights as appropriate
when using CL and Neon backends
* Updated the reference implementation of the convolution
* Updated the relevant unit tests accordingly
!android-nn-driver:459
Change-Id: I07d0818efa9d1ca1e5dad82983aac1fe78eadb18
diff --git a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
index 9cadbf0..1745b82 100644
--- a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
+++ b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
@@ -12,6 +12,7 @@
#include <aclCommon/ArmComputeTensorUtils.hpp>
#include <cl/ClTensorHandle.hpp>
#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/WorkloadUtils.hpp>
#include <arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h>
@@ -21,14 +22,23 @@
using namespace armcomputetensorutils;
arm_compute::Status ClDepthwiseConvolutionWorkloadValidate(const TensorInfo& input,
- const TensorInfo& output,
- const DepthwiseConvolution2dDescriptor& descriptor,
- const TensorInfo& weights,
- const Optional<TensorInfo>& biases)
+ const TensorInfo& output,
+ const DepthwiseConvolution2dDescriptor& descriptor,
+ const TensorInfo& weights,
+ const Optional<TensorInfo>& biases)
{
- const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
+ const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
- const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
+
+ // ArmNN's weight format is [ M, I, H, W ]
+ const unsigned int aclDepthMultiplier = weights.GetShape()[0];
+
+ // Convert the weight format from ArmNN's [ M, I, H, W ] (does NOT depend on the data layout) to either
+ // [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library
+ TensorInfo weightsPermuted = ConvertWeightTensorInfoFromArmnnToAcl(weights, descriptor.m_DataLayout);
+
+ // Convert the weights into the compute library format
+ const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weightsPermuted, descriptor.m_DataLayout);
arm_compute::TensorInfo aclBiasesInfo;
arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
@@ -42,7 +52,6 @@
}
const arm_compute::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor);
- const unsigned int aclDepthMultiplier = weights.GetShape()[0];
return arm_compute::CLDepthwiseConvolutionLayer::validate(&aclInputInfo,
&aclWeightsInfo,
@@ -57,10 +66,18 @@
const WorkloadInfo& info)
: BaseWorkload<DepthwiseConvolution2dQueueDescriptor>(descriptor, info)
{
- auto& weightInfo = m_Data.m_Weight->GetTensorInfo();
+ // Allocate a buffer for the swizzling of the weight tensor
+ std::unique_ptr<unsigned char[]> permuteBuffer(new unsigned char[m_Data.m_Weight->GetTensorInfo().GetNumBytes()]);
+ // Convert the weight format from ArmNN's [ M, I, H, W ] (does NOT depend on the data layout) to either
+ // [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library
+ ConstTensor weightPermuted = ConvertWeightTensorFromArmnnToAcl(m_Data.m_Weight,
+ m_Data.m_Parameters.m_DataLayout,
+ permuteBuffer.get());
+
+ // Convert the weights into the compute library format
m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
- BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout);
+ BuildArmComputeTensor(*m_KernelTensor, weightPermuted.GetInfo(), m_Data.m_Parameters.m_DataLayout);
if (m_Data.m_Parameters.m_BiasEnabled)
{
@@ -86,13 +103,14 @@
input.info()->set_data_layout(aclDataLayout);
output.info()->set_data_layout(aclDataLayout);
+ // ArmNN's weight format is [ M, I, H, W ]
+ auto& weightInfo = m_Data.m_Weight->GetTensorInfo();
+
+ // Get the depth multiplier
const unsigned int depthMultiplier = weightInfo.GetShape()[0];
- const unsigned int widthIndex = (m_Data.m_Parameters.m_DataLayout == DataLayout::NCHW) ? 3 : 2;
- const unsigned int heightIndex = (m_Data.m_Parameters.m_DataLayout == DataLayout::NCHW) ? 2 : 1;
-
- //Check for optimisation opportunities.
- bool use3x3Optimisation = (weightInfo.GetShape()[widthIndex] == 3) && (weightInfo.GetShape()[heightIndex] == 3);
+ // Check for optimisation opportunities.
+ bool use3x3Optimisation = (weightInfo.GetShape()[2] == 3) && (weightInfo.GetShape()[3] == 3);
if (use3x3Optimisation)
{
m_DepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer3x3>();
@@ -118,7 +136,8 @@
BOOST_ASSERT(m_DepthwiseConvolutionLayer);
- InitializeArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight);
+ ScopedCpuTensorHandle weightsPermutedHandle(weightPermuted);
+ InitializeArmComputeClTensorData(*m_KernelTensor, &weightsPermutedHandle);
if (m_BiasTensor)
{