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path: root/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp
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Diffstat (limited to 'src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp')
-rw-r--r--src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp151
1 files changed, 93 insertions, 58 deletions
diff --git a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp
index dcb982fa56..873601bb11 100644
--- a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp
@@ -29,12 +29,12 @@
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
+
+#include "src/common/utils/Log.h"
#include "src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.h"
#include "src/runtime/heuristics/dwc_native/ClDWCNativeKernelConfig.h"
#include "src/runtime/heuristics/dwc_native/IClDWCNativeKernelConfig.h"
-#include "src/common/utils/Log.h"
-
namespace arm_compute
{
using namespace arm_compute::misc;
@@ -63,25 +63,33 @@ CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayer(std::shared_ptr<IMemory
CLDepthwiseConvolutionLayer::~CLDepthwiseConvolutionLayer() = default;
-void CLDepthwiseConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
+void CLDepthwiseConvolutionLayer::configure(ICLTensor *input,
+ const ICLTensor *weights,
+ const ICLTensor *biases,
+ ICLTensor *output,
+ const PadStrideInfo &conv_info,
+ unsigned int depth_multiplier,
+ ActivationLayerInfo act_info,
+ const Size2D &dilation)
{
- configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation);
+ configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier,
+ act_info, dilation);
}
-void CLDepthwiseConvolutionLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases,
- ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
+void CLDepthwiseConvolutionLayer::configure(const CLCompileContext &compile_context,
+ ICLTensor *input,
+ const ICLTensor *weights,
+ const ICLTensor *biases,
+ ICLTensor *output,
+ const PadStrideInfo &conv_info,
+ unsigned int depth_multiplier,
+ ActivationLayerInfo act_info,
+ const Size2D &dilation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights);
- ARM_COMPUTE_ERROR_THROW_ON(CLDepthwiseConvolutionLayer::validate(input->info(),
- weights->info(),
- biases != nullptr ? biases->info() : nullptr,
- output != nullptr ? output->info() : input->info(),
- conv_info,
- depth_multiplier,
- act_info,
- dilation));
+ ARM_COMPUTE_ERROR_THROW_ON(CLDepthwiseConvolutionLayer::validate(
+ input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr,
+ output != nullptr ? output->info() : input->info(), conv_info, depth_multiplier, act_info, dilation));
ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation);
_is_quantized = is_data_type_quantized(input->info()->data_type());
@@ -96,7 +104,7 @@ void CLDepthwiseConvolutionLayer::configure(const CLCompileContext &compile_cont
ICLTensor *input_to_use = input;
const ICLTensor *weights_to_use = weights;
ICLTensor *output_to_use = output;
- if(_needs_permute)
+ if (_needs_permute)
{
_memory_group.manage(&_permuted_input);
_memory_group.manage(&_permuted_output);
@@ -119,10 +127,12 @@ void CLDepthwiseConvolutionLayer::configure(const CLCompileContext &compile_cont
CLTensor *output_multipliers_to_use = nullptr;
CLTensor *output_shifts_to_use = nullptr;
- if(_is_quantized)
+ if (_is_quantized)
{
- const size_t idx_c = get_data_layout_dimension_index(weights->info()->data_layout(), DataLayoutDimension::CHANNEL);
- const size_t num_filters = (is_data_type_quantized_per_channel(weights->info()->data_type())) ? weights->info()->dimension(idx_c) : 1;
+ const size_t idx_c =
+ get_data_layout_dimension_index(weights->info()->data_layout(), DataLayoutDimension::CHANNEL);
+ const size_t num_filters =
+ (is_data_type_quantized_per_channel(weights->info()->data_type())) ? weights->info()->dimension(idx_c) : 1;
_output_multipliers.allocator()->init(TensorInfo(TensorShape(num_filters), 1, DataType::S32));
_output_shifts.allocator()->init(TensorInfo(TensorShape(num_filters), 1, DataType::S32));
@@ -132,16 +142,18 @@ void CLDepthwiseConvolutionLayer::configure(const CLCompileContext &compile_cont
}
// Get the depthwise convolution compute parameters
- auto t = ClDWCNativeKernelConfigurationFactory::create(gpu_target);
- const DWCComputeKernelInfo dwc_native_compute_info = t->configure(input_to_use->info(), weights_to_use->info(), conv_info, dilation, depth_multiplier);
+ auto t = ClDWCNativeKernelConfigurationFactory::create(gpu_target);
+ const DWCComputeKernelInfo dwc_native_compute_info =
+ t->configure(input_to_use->info(), weights_to_use->info(), conv_info, dilation, depth_multiplier);
- const ConvolutionInfo conv_kernel_info{ conv_info, depth_multiplier, act_info, dilation };
+ const ConvolutionInfo conv_kernel_info{conv_info, depth_multiplier, act_info, dilation};
_dwc_native_kernel->set_target(gpu_target);
_dwc_native_kernel->configure(compile_context, input_to_use, weights_to_use, biases, output_to_use,
- dwc_native_compute_info, conv_kernel_info, output_multipliers_to_use, output_shifts_to_use);
+ dwc_native_compute_info, conv_kernel_info, output_multipliers_to_use,
+ output_shifts_to_use);
- if(_needs_permute)
+ if (_needs_permute)
{
_permuted_input.allocator()->allocate();
@@ -151,22 +163,27 @@ void CLDepthwiseConvolutionLayer::configure(const CLCompileContext &compile_cont
_permuted_output.allocator()->allocate();
}
- if(_is_quantized)
+ if (_is_quantized)
{
_output_multipliers.allocator()->allocate();
_output_shifts.allocator()->allocate();
}
}
-Status CLDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
+Status CLDepthwiseConvolutionLayer::validate(const ITensorInfo *input,
+ const ITensorInfo *weights,
+ const ITensorInfo *biases,
+ const ITensorInfo *output,
const PadStrideInfo &conv_info,
- unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
+ unsigned int depth_multiplier,
+ ActivationLayerInfo act_info,
+ const Size2D &dilation)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(!weights->are_values_constant(), "Dynamic weights are not supported");
const bool in_place = input == output || output == nullptr;
- if(in_place)
+ if (in_place)
{
output = input;
}
@@ -174,21 +191,23 @@ Status CLDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe
const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH);
const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT);
- ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) + (weights->dimension(idx_w) - 1) * (dilation.x() - 1) > input->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right());
- ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) + (weights->dimension(idx_h) - 1) * (dilation.y() - 1) > input->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom());
+ ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) + (weights->dimension(idx_w) - 1) * (dilation.x() - 1) >
+ input->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right());
+ ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) + (weights->dimension(idx_h) - 1) * (dilation.y() - 1) >
+ input->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom());
const GPUTarget gpu_target = CLScheduler::get().target();
- const ConvolutionInfo conv_kernel_info{ conv_info, depth_multiplier, act_info, dilation };
+ const ConvolutionInfo conv_kernel_info{conv_info, depth_multiplier, act_info, dilation};
const bool needs_permute = input->data_layout() == DataLayout::NCHW;
const bool is_quantized = is_data_type_quantized(input->data_type());
TensorInfo output_multipliers_shifts_info(TensorInfo(TensorShape(1U), 1, DataType::S32));
- if(is_quantized)
+ if (is_quantized)
{
- if(is_data_type_quantized_per_channel(weights->data_type()))
+ if (is_data_type_quantized_per_channel(weights->data_type()))
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QSYMM8_PER_CHANNEL);
@@ -201,40 +220,57 @@ Status CLDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe
}
}
- if(needs_permute)
+ if (needs_permute)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(in_place, "In-place is supported only with NHWC data layout");
TensorShape permuted_input_shape = input->tensor_shape();
TensorShape permuted_weights_shape = weights->tensor_shape();
- const ConvolutionInfo info{ conv_info, depth_multiplier, ActivationLayerInfo(), dilation };
- TensorShape permuted_output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, info);
+ const ConvolutionInfo info{conv_info, depth_multiplier, ActivationLayerInfo(), dilation};
+ TensorShape permuted_output_shape =
+ shape_calculator::compute_depthwise_convolution_shape(*input, *weights, info);
permute(permuted_input_shape, PermutationVector(2U, 0U, 1U));
permute(permuted_weights_shape, PermutationVector(2U, 0U, 1U));
permute(permuted_output_shape, PermutationVector(2U, 0U, 1U));
- const TensorInfo permuted_input = input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_input_shape).set_data_layout(DataLayout::NHWC);
- const TensorInfo permuted_weights = weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_weights_shape).set_data_layout(DataLayout::NHWC);
- const TensorInfo permuted_output = output->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_output_shape).set_data_layout(DataLayout::NHWC);
+ const TensorInfo permuted_input = input->clone()
+ ->set_is_resizable(true)
+ .reset_padding()
+ .set_tensor_shape(permuted_input_shape)
+ .set_data_layout(DataLayout::NHWC);
+ const TensorInfo permuted_weights = weights->clone()
+ ->set_is_resizable(true)
+ .reset_padding()
+ .set_tensor_shape(permuted_weights_shape)
+ .set_data_layout(DataLayout::NHWC);
+ const TensorInfo permuted_output = output->clone()
+ ->set_is_resizable(true)
+ .reset_padding()
+ .set_tensor_shape(permuted_output_shape)
+ .set_data_layout(DataLayout::NHWC);
ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(input, &permuted_input, PermutationVector(2U, 0U, 1U)));
ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(weights, &permuted_weights, PermutationVector(2U, 0U, 1U)));
// Get the depthwise convolution compute parameters
- auto t = ClDWCNativeKernelConfigurationFactory::create(gpu_target);
- const DWCComputeKernelInfo dwc_native_compute_info = t->configure(&permuted_input, &permuted_weights, conv_info, dilation, depth_multiplier);
+ auto t = ClDWCNativeKernelConfigurationFactory::create(gpu_target);
+ const DWCComputeKernelInfo dwc_native_compute_info =
+ t->configure(&permuted_input, &permuted_weights, conv_info, dilation, depth_multiplier);
- ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(&permuted_input, &permuted_weights, biases, &permuted_output,
- dwc_native_compute_info, conv_kernel_info, &output_multipliers_shifts_info, &output_multipliers_shifts_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(
+ &permuted_input, &permuted_weights, biases, &permuted_output, dwc_native_compute_info, conv_kernel_info,
+ &output_multipliers_shifts_info, &output_multipliers_shifts_info));
ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(&permuted_output, output, PermutationVector(1U, 2U, 0U)));
}
else
{
// Get the depthwise convolution compute parameters
- auto t = ClDWCNativeKernelConfigurationFactory::create(gpu_target);
- const DWCComputeKernelInfo dwc_native_compute_info = t->configure(input, weights, conv_info, dilation, depth_multiplier);
- ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(input, weights, biases, output, dwc_native_compute_info, conv_kernel_info, &output_multipliers_shifts_info,
- &output_multipliers_shifts_info));
+ auto t = ClDWCNativeKernelConfigurationFactory::create(gpu_target);
+ const DWCComputeKernelInfo dwc_native_compute_info =
+ t->configure(input, weights, conv_info, dilation, depth_multiplier);
+ ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(
+ input, weights, biases, output, dwc_native_compute_info, conv_kernel_info, &output_multipliers_shifts_info,
+ &output_multipliers_shifts_info));
}
return Status{};
}
@@ -245,12 +281,12 @@ void CLDepthwiseConvolutionLayer::run()
MemoryGroupResourceScope scope_mg(_memory_group);
- if(_needs_permute)
+ if (_needs_permute)
{
_permute_input_to_nhwc.run();
}
CLScheduler::get().enqueue(*_dwc_native_kernel);
- if(_needs_permute)
+ if (_needs_permute)
{
_permute_output_to_nchw.run();
}
@@ -258,22 +294,21 @@ void CLDepthwiseConvolutionLayer::run()
void CLDepthwiseConvolutionLayer::prepare()
{
- if(!_is_prepared)
+ if (!_is_prepared)
{
- if(_is_quantized)
+ if (_is_quantized)
{
_output_multipliers.map();
_output_shifts.map();
- quantization::compute_quantized_multipliers_and_shifts(_input->info(),
- _original_weights->info(),
- _output != nullptr ? _output->info() : _input->info(),
- reinterpret_cast<int32_t *>(_output_multipliers.ptr_to_element(Coordinates(0))),
- reinterpret_cast<int32_t *>(_output_shifts.ptr_to_element(Coordinates(0))));
+ quantization::compute_quantized_multipliers_and_shifts(
+ _input->info(), _original_weights->info(), _output != nullptr ? _output->info() : _input->info(),
+ reinterpret_cast<int32_t *>(_output_multipliers.ptr_to_element(Coordinates(0))),
+ reinterpret_cast<int32_t *>(_output_shifts.ptr_to_element(Coordinates(0))));
_output_multipliers.unmap();
_output_shifts.unmap();
}
- if(_needs_permute)
+ if (_needs_permute)
{
ARM_COMPUTE_ERROR_ON(!_original_weights->is_used());
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-30 10:03:04 +0000