commit 52ba29e936b8e711e8acdfe819e36f884d4f3fe1
author Jenkins <bsgcomp@arm.com> Wed Aug 29 15:32:11 2018 +0000
committer Michele Di Giorgio <michele.digiorgio@arm.com> Thu Aug 30 17:15:09 2018 +0100
tree 23a8e15208ad7fcf07a37ed9119979cde01dcdc8
parent e2542c9f35ca427286822cd0c9296f49914f78b0

arm_compute v18.08

src/runtime/NEON/functions/NEConvolutionLayer.cpp

diff --git a/src/runtime/NEON/functions/NEConvolutionLayer.cpp b/src/runtime/NEON/functions/NEConvolutionLayer.cpp
index 7053c7e..931e5db 100644
--- a/src/runtime/NEON/functions/NEConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEConvolutionLayer.cpp
@@ -26,6 +26,7 @@
 #include "arm_compute/core/PixelValue.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
 #include "support/ToolchainSupport.h"
 
 #include <cmath>
@@ -41,10 +42,11 @@
 }
 
 void NEConvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info,
-                                   const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math)
+                                   const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups)
 {
     // Perform validate step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
+    ARM_COMPUTE_UNUSED(num_groups);
     ARM_COMPUTE_ERROR_THROW_ON(NEConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation, act_info,
                                                             enable_fast_math));
 
@@ -78,8 +80,10 @@
 }
 
 Status NEConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
-                                    const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math)
+                                    const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups)
 {
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG((num_groups != 1), "Grouping (num_groups != 1) is not supported on NEON");
+
     switch(NEConvolutionLayer::get_convolution_method(input, weights, output, conv_info, weights_info, dilation, act_info))
     {
         case ConvolutionMethod::WINOGRAD:
@@ -108,6 +112,42 @@
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, weights);
     ARM_COMPUTE_UNUSED(weights_info);
 
+    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);
+    const size_t idx_c = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL);
+
+    /* Input spatial dims, kernel size, IFM/OFM, conv info*/
+    using ConvolutionConfiguration = std::tuple<Size2D, Size2D, Size2D, PadStrideInfo>;
+    using ConfigurationMethod      = std::pair<ConvolutionConfiguration, ConvolutionMethod>;
+
+    const std::vector<ConfigurationMethod> known_configs =
+    {
+        // Alexnet
+        ConfigurationMethod(ConvolutionConfiguration(Size2D(27U, 27U), Size2D(5U, 5U), Size2D(48U, 128U), PadStrideInfo(1U, 1U, 2U, 2U)), ConvolutionMethod::GEMM),
+        // VGG16 / VGG19
+        ConfigurationMethod(ConvolutionConfiguration(Size2D(224U, 224U), Size2D(3U, 3U), Size2D(3U, 64U), PadStrideInfo(1U, 1U, 1U, 1U)), ConvolutionMethod::GEMM),
+        // Mobilenet 224
+        ConfigurationMethod(ConvolutionConfiguration(Size2D(224U, 224U), Size2D(3U, 3U), Size2D(3U, 32U), PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR)), ConvolutionMethod::GEMM),
+        // Mobilenet 160
+        ConfigurationMethod(ConvolutionConfiguration(Size2D(160U, 160U), Size2D(3U, 3U), Size2D(3U, 24U), PadStrideInfo(2U, 2U, 0U, 1U, 0U, 1U, DimensionRoundingType::FLOOR)), ConvolutionMethod::GEMM)
+    };
+
+    const auto find_config = [&](ConfigurationMethod c)
+    {
+        const ConvolutionConfiguration config = c.first;
+        const PadStrideInfo            info   = std::get<3>(config);
+
+        return std::get<0>(config) == Size2D(input->dimension(idx_w), input->dimension(idx_h)) && std::get<1>(config) == Size2D(weights->dimension(idx_w), weights->dimension(idx_h))
+               && std::get<2>(config) == Size2D(weights->dimension(idx_c), weights->dimension(3)) && info.pad_top() == conv_info.pad_top() && info.pad_right() == conv_info.pad_right()
+               && info.pad_bottom() == conv_info.pad_bottom() && info.pad_left() == conv_info.pad_left() && info.stride() == conv_info.stride();
+    };
+
+    std::vector<ConfigurationMethod>::const_iterator found;
+    if((found = std::find_if(known_configs.begin(), known_configs.end(), find_config)) != known_configs.end())
+    {
+        return (*found).second;
+    }
+
     if(dilation != Size2D(1U, 1U) || Scheduler::get().cpu_info().get_cpu_model() == CPUModel::A53
        || input->dimension(get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL)) <= 16)
     {
@@ -119,6 +159,12 @@
 
 void NEConvolutionLayer::run()
 {
+    prepare();
     _function->run();
 }
+
+void NEConvolutionLayer::prepare()
+{
+    _function->prepare();
+}
 } // namespace arm_compute