IVGCVSW-6940 ConstTensorsAsInput: DepthwiseConvolution2d - Complete ACL
* Added backend specific optimization & test for CpuAcc and GpuAcc: PermuteDepthwiseConv2dWeights
Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: I600476b2e9c557a39818a574c1091c9d650b21b1
diff --git a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
index f6a071a..9a4cad3 100644
--- a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
+++ b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp
@@ -33,8 +33,15 @@
const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
- // ArmNN's weight format is usually [ M, I, H, W ] but for depthwise its [ 1, H, W, I*M]
- // Permute to [ 1, I * M, H, W ] (if NCHW) as required by the compute library
+ // ArmNN format for weights for depthwise is [1, H, W, C] independently of the input/output layout
+ //
+ // ACL format for weights for depthwise is:
+ // - [1, H, W, C] for [N, H, W, C] input/output layout (matches with ArmNN)
+ // - [1, C, H, W] for [N, C, H, W] input/output layout
+ //
+ // Therefore ArmNN weights have to be permuted when input/output layout is [N, C, H, W] to pass them to ACL.
+ // The PermuteDepthwiseConv2dWeights backend optimization takes care of this, but it has not been performed yet,
+ // so we do the permute here for the TensorInfo weights.
unsigned int aclDepthMultiplier;
TensorInfo weightsPermuted;
std::tie(weightsPermuted, aclDepthMultiplier) = Convert1HWOTensorInfoToAcl(weights, input,descriptor.m_DataLayout);
@@ -43,12 +50,10 @@
const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weightsPermuted, descriptor.m_DataLayout);
arm_compute::TensorInfo aclBiasesInfo;
- arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
-
+ arm_compute::TensorInfo* optionalAclBiasesInfo = nullptr;
if (descriptor.m_BiasEnabled)
{
ARMNN_ASSERT(biases.has_value());
-
aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
optionalAclBiasesInfo = &aclBiasesInfo;
}
@@ -93,41 +98,36 @@
ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClDepthwiseConvolutionWorkload_Construct",
descriptor.m_Parameters,
detailsInfo,
- this->GetGuid());
+ GetGuid());
- // ArmNN's weight format is usually [ M, I, H, W ] but for depthwise its [ 1, H, W, I*M]
- // Permute to [ 1, I * M, H, W ] (if NCHW), as required by the compute library
- ConstTensor weightPermuted;
- unsigned int depthMultiplier;
- std::unique_ptr<unsigned char[]> permuteBuffer(new unsigned char[m_Data.m_Weight->GetTensorInfo().GetNumBytes()]);
- std::tie(weightPermuted, depthMultiplier) = Convert1HWOTensorToAcl(m_Data.m_Weight,
- info.m_InputTensorInfos[0],
- m_Data.m_Parameters.m_DataLayout,
- permuteBuffer.get());
+ m_Data.ValidateInputsOutputs("ClDepthwiseConv2dWorkload", descriptor.m_Parameters.GetNumInputs(), 1);
- // Convert the weights into the compute library format
- m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
- BuildArmComputeTensor(*m_KernelTensor, weightPermuted.GetInfo(), m_Data.m_Parameters.m_DataLayout);
+ arm_compute::ICLTensor& input = PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+ arm_compute::ICLTensor& output = PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+ arm_compute::ICLTensor& weights = PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Inputs[1])->GetTensor();
+ arm_compute::ITensorInfo* weightsInfo = weights.info();
+ arm_compute::ITensorInfo* inputInfo = input.info();
+ auto weightsShape = weightsInfo->tensor_shape();
+ auto inputShape = inputInfo->tensor_shape();
+ // The PermuteDepthwiseConv2dWeights backend optimization has been performed,
+ // converting weights to have the same data layout as input.
+ unsigned int depthMultiplier =
+ ComputeDepthwiseConv2dDepthMultiplier(m_Data.m_Parameters.m_DataLayout, weightsShape, inputShape);
+
+ arm_compute::ICLTensor* bias = nullptr;
if (m_Data.m_Parameters.m_BiasEnabled)
{
- m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
- BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout);
+ bias = &PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Inputs[2])->GetTensor();
}
const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(
m_Data.m_Parameters.m_DilationX,
m_Data.m_Parameters.m_DilationY);
-
- std::string name = std::string("ClDepthwiseConvolutionWorkload");
- m_Data.ValidateInputsOutputs(name, 1, 1);
-
- arm_compute::ICLTensor& input = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
- arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
-
arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
input.info()->set_data_layout(aclDataLayout);
+ weights.info()->set_data_layout(aclDataLayout);
output.info()->set_data_layout(aclDataLayout);
arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(m_Data.m_Parameters);
@@ -141,8 +141,8 @@
static_cast<arm_compute::CLDepthwiseConvolutionLayer*>(m_DepthwiseConvolutionLayer.get())->configure(
clCompileContext,
&input,
- m_KernelTensor.get(),
- m_BiasTensor.get(),
+ &weights,
+ bias,
&output,
padStrideInfo,
depthMultiplier,
@@ -150,28 +150,11 @@
aclDilationInfo);
}
ARMNN_ASSERT(m_DepthwiseConvolutionLayer);
-
- ScopedTensorHandle weightsPermutedHandle(weightPermuted);
- InitializeArmComputeClTensorData(*m_KernelTensor, &weightsPermutedHandle);
-
- if (m_BiasTensor)
- {
- InitializeArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias);
- }
-
- m_DepthwiseConvolutionLayer->prepare();
- FreeUnusedTensors();
-}
-
-void ClDepthwiseConvolutionWorkload::FreeUnusedTensors()
-{
- FreeTensorIfUnused(m_KernelTensor);
- FreeTensorIfUnused(m_BiasTensor);
}
void ClDepthwiseConvolutionWorkload::Execute() const
{
- ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClDepthwiseConvolutionWorkload_Execute", this->GetGuid());
+ ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClDepthwiseConvolutionWorkload_Execute", GetGuid());
ARMNN_ASSERT(m_DepthwiseConvolutionLayer);
RunClFunction(*m_DepthwiseConvolutionLayer, CHECK_LOCATION());