Implement FP GPU depthwise convolution 1x1 kernel for in-place computation
* Implement in-place graph node mutator for 1x1 depthwise convolution
* Add in-place to validation fixture except for
DepthwiseConvolutionLayerNativeValidationFixture as it would be a
duplicate test otherwise (DepthwiseConvolutionLayerNative test tests
the underlying kernel)
Resolves: COMPMID-4432
Change-Id: Id7f10f5ebdce7d49f550c0b62dbaaab7f5b59d29
Signed-off-by: SiCongLi <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5874
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/src/graph/mutators/InPlaceOperationMutator.cpp b/src/graph/mutators/InPlaceOperationMutator.cpp
index 616ec5c..86236e8 100644
--- a/src/graph/mutators/InPlaceOperationMutator.cpp
+++ b/src/graph/mutators/InPlaceOperationMutator.cpp
@@ -23,9 +23,15 @@
*/
#include "arm_compute/graph/mutators/InPlaceOperationMutator.h"
+#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/graph/Graph.h"
#include "arm_compute/graph/Logger.h"
+#include "arm_compute/graph/nodes/DepthwiseConvolutionLayerNode.h"
+#include "arm_compute/graph/nodes/FusedDepthwiseConvolutionBatchNormalizationNode.h"
+#include "support/Cast.h"
+
+using namespace arm_compute::utils::cast;
namespace arm_compute
{
@@ -82,6 +88,69 @@
node->set_output_tensor(new_output->id(), 0);
}
+// Try to mutate the node to perform the depthwise in-place calculation
+void try_in_place_depthwiseconv(std::unique_ptr<INode> &node)
+{
+ // Get input edge
+ Edge *input_edge = node->input_edge(0);
+ Edge *weight_edge = node->input_edge(1);
+ ARM_COMPUTE_ERROR_ON(input_edge == nullptr || weight_edge == nullptr);
+
+ auto input_tensor = input_edge->tensor();
+ auto weight_tensor = weight_edge->tensor();
+ ARM_COMPUTE_ERROR_ON(input_tensor == nullptr || weight_tensor == nullptr);
+
+ const auto input_shape = input_tensor->desc().shape;
+ const auto qinfo_input = input_tensor->desc().quant_info;
+
+ const auto weight_shape = weight_tensor->desc().shape;
+ const auto weight_layout = weight_tensor->desc().layout;
+
+ // Extract PadStrideInfo and depth multiplier
+ PadStrideInfo conv_info{};
+ unsigned int depth_multiplier{};
+ if(node->type() == NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer)
+ {
+ conv_info = polymorphic_downcast<FusedDepthwiseConvolutionBatchNormalizationNode *>(node.get())->convolution_info();
+ depth_multiplier = polymorphic_downcast<FusedDepthwiseConvolutionBatchNormalizationNode *>(node.get())->depth_multiplier();
+ }
+ else if(node->type() == NodeType::DepthwiseConvolutionLayer)
+ {
+ conv_info = polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node.get())->convolution_info();
+ depth_multiplier = polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node.get())->depth_multiplier();
+ }
+
+ // Get current output tensor
+ auto current_output_tensor = node->output(0);
+ ARM_COMPUTE_ERROR_ON(current_output_tensor == nullptr);
+ const auto out_shape = current_output_tensor->desc().shape;
+ const auto qinfo_out = current_output_tensor->desc().quant_info;
+
+ bool input_can_in_place = !arm_compute::detail::have_different_dimensions(out_shape, input_shape, 0) && (qinfo_input == qinfo_out) && (input_tensor->accessor() == nullptr);
+
+ // Specify conditions with which input can be in-placed
+ input_can_in_place &= weight_layout == input_tensor->desc().layout && weight_layout == DataLayout::NHWC;
+
+ const int weights_width_idx = get_data_layout_dimension_index(weight_layout, DataLayoutDimension::WIDTH);
+ const int weights_height_idx = get_data_layout_dimension_index(weight_layout, DataLayoutDimension::HEIGHT);
+ const bool is_1x1 = weight_shape[weights_width_idx] == 1U && weight_shape[weights_height_idx] == 1U;
+ input_can_in_place &= is_1x1;
+
+ input_can_in_place &= depth_multiplier == 1;
+ input_can_in_place &= conv_info.stride() == std::make_pair(1U, 1U);
+ input_can_in_place &= !conv_info.has_padding();
+ // NOTE: Dilation should also be (1, 1). However currently dilation is not supported in the depthwise conv node
+
+ if(input_can_in_place)
+ {
+ set_new_output_and_inherit_accessor(node, current_output_tensor, input_tensor);
+ }
+ else
+ {
+ ARM_COMPUTE_LOG_GRAPH_VERBOSE("Prevented in-place operation as there is an accessor bound to the input tensor or the quantization info are different.\n");
+ }
+}
+
// Try to mutate the node to perform the elementwise in-place calculation
void try_in_place_elementwise(std::unique_ptr<INode> &node)
{
@@ -148,6 +217,8 @@
NodeType::BatchNormalizationLayer,
NodeType::EltwiseLayer,
NodeType::UnaryEltwiseLayer,
+ NodeType::DepthwiseConvolutionLayer,
+ NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer,
NodeType::PrintLayer
};
@@ -166,6 +237,10 @@
{
try_in_place_elementwise(node);
}
+ else if(node->type() == NodeType::FusedDepthwiseConvolutionBatchNormalizationLayer || node->type() == NodeType::DepthwiseConvolutionLayer)
+ {
+ try_in_place_depthwiseconv(node);
+ }
else
{
// Get current and new output tensors