COMPMID-1109 - Enabling Winograd in the graph when possible

Change-Id: I524abd28188995ae9c7a43b189b1eb2d7546be93
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/130576
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

7 files changed, 23 insertions, 28 deletions

diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp
index d654f9ece9..291a586315 100644
--- a/examples/graph_alexnet.cpp
+++ b/examples/graph_alexnet.cpp
@@ -57,10 +57,9 @@ public:
         Target    target_hint = set_target_hint(target);
 
         // TODO (geopin01) : Get GPU target somehow and set gemm also for midgard ?
-        const bool        is_gemm_convolution5x5     = (target_hint == Target::NEON);
-        const bool        is_winograd_convolution3x3 = target_hint == Target::CL;
-        ConvolutionMethod convolution_5x5_hint       = is_gemm_convolution5x5 ? ConvolutionMethod::GEMM : ConvolutionMethod::DIRECT;
-        ConvolutionMethod convolution_3x3_hint       = is_winograd_convolution3x3 ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM;
+        const bool        is_neon              = (target_hint == Target::NEON);
+        ConvolutionMethod convolution_5x5_hint = is_neon ? ConvolutionMethod::GEMM : ConvolutionMethod::DIRECT;
+        ConvolutionMethod convolution_3x3_hint = is_neon ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT;
 
         // Parse arguments
         if(argc < 2)
diff --git a/examples/graph_googlenet.cpp b/examples/graph_googlenet.cpp
index 85384d48d3..25e9e7f0cf 100644
--- a/examples/graph_googlenet.cpp
+++ b/examples/graph_googlenet.cpp
@@ -54,7 +54,7 @@ public:
         // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
         const int         target           = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
         Target            target_hint      = set_target_hint(target);
-        ConvolutionMethod convolution_hint = (target_hint == Target::CL) ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM;
+        ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT;
 
         // Parse arguments
         if(argc < 2)
@@ -96,10 +96,10 @@ public:
                   get_weights_accessor(data_path, "/cnn_data/googlenet_model/conv1/conv1_7x7_s2_w.npy"),
                   get_weights_accessor(data_path, "/cnn_data/googlenet_model/conv1/conv1_7x7_s2_b.npy"),
                   PadStrideInfo(2, 2, 3, 3))
+              << convolution_hint
               << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
               << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
               << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f))
-              << convolution_hint
               << ConvolutionLayer(
                   1U, 1U, 64U,
                   get_weights_accessor(data_path, "/cnn_data/googlenet_model/conv2/conv2_3x3_reduce_w.npy"),
diff --git a/examples/graph_inception_v3.cpp b/examples/graph_inception_v3.cpp
index ed79ba65d8..01a4d0c49c 100644
--- a/examples/graph_inception_v3.cpp
+++ b/examples/graph_inception_v3.cpp
@@ -51,10 +51,9 @@ public:
         std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
 
         // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int target      = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target    target_hint = set_target_hint(target);
-
-        ConvolutionMethod convolution_hint = (target_hint == Target::CL) ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM;
+        const int         target           = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
+        Target            target_hint      = set_target_hint(target);
+        ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT;
 
         // Parse arguments
         if(argc < 2)
@@ -100,8 +99,8 @@ public:
                                          get_random_accessor(1.f, 1.f), get_weights_accessor(data_path,
                                                                                              "/cnn_data/inceptionv3_model/Conv2d_1a_3x3_BatchNorm_beta.npy"),
                                          0.001f)
-              << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
               << convolution_hint
+              << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
               << ConvolutionLayer(3U, 3U, 32U,
                                   get_weights_accessor(data_path, "/cnn_data/inceptionv3_model/Conv2d_2a_3x3_weights.npy"),
                                   std::unique_ptr<arm_compute::graph::ITensorAccessor>(nullptr), PadStrideInfo(1, 1, 0, 0))
diff --git a/examples/graph_inception_v4.cpp b/examples/graph_inception_v4.cpp
index d505133833..8f340354cd 100644
--- a/examples/graph_inception_v4.cpp
+++ b/examples/graph_inception_v4.cpp
@@ -54,10 +54,9 @@ public:
         std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
 
         // Set target. 0 (NEON), 1 (OpenCL). By default it is NEON
-        const int target      = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target    target_hint = set_target_hint(target);
-
-        ConvolutionMethod convolution_hint = (target_hint == Target::CL) ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM;
+        const int         target           = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
+        Target            target_hint      = set_target_hint(target);
+        ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT;
 
         // Parse arguments
         if(argc < 2)
diff --git a/examples/graph_resnet50.cpp b/examples/graph_resnet50.cpp
index 6fc652edbe..d0fa106bce 100644
--- a/examples/graph_resnet50.cpp
+++ b/examples/graph_resnet50.cpp
@@ -52,10 +52,9 @@ public:
                                                                                                                    false /* Do not convert to BGR */);
 
         // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int target      = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target    target_hint = set_target_hint(target);
-
-        ConvolutionMethod convolution_hint = (target_hint == Target::CL) ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM;
+        const int         target           = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
+        Target            target_hint      = set_target_hint(target);
+        ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT;
 
         // Parse arguments
         if(argc < 2)
diff --git a/examples/graph_squeezenet.cpp b/examples/graph_squeezenet.cpp
index e9bd8a9c5f..ff2487cd65 100644
--- a/examples/graph_squeezenet.cpp
+++ b/examples/graph_squeezenet.cpp
@@ -53,10 +53,9 @@ public:
         std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
 
         // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int target      = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target    target_hint = set_target_hint(target);
-
-        ConvolutionMethod convolution_hint = (target_hint == Target::CL) ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM;
+        const int         target           = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
+        Target            target_hint      = set_target_hint(target);
+        ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT;
 
         // Parse arguments
         if(argc < 2)
diff --git a/examples/graph_squeezenet_v1_1.cpp b/examples/graph_squeezenet_v1_1.cpp
index 1696b7df43..e1a1f661fb 100644
--- a/examples/graph_squeezenet_v1_1.cpp
+++ b/examples/graph_squeezenet_v1_1.cpp
@@ -56,10 +56,9 @@ public:
         std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb);
 
         // Set target. 0 (NEON), 1 (OpenCL), 2 (OpenCL with Tuner). By default it is NEON
-        const int target      = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
-        Target    target_hint = set_target_hint(target);
-
-        ConvolutionMethod convolution_hint = (target_hint == Target::CL) ? ConvolutionMethod::WINOGRAD : ConvolutionMethod::GEMM;
+        const int         target           = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0;
+        Target            target_hint      = set_target_hint(target);
+        ConvolutionMethod convolution_hint = target_hint == Target::NEON ? ConvolutionMethod::GEMM : ConvolutionMethod::DEFAULT;
 
         // Parse arguments
         if(argc < 2)
@@ -102,9 +101,10 @@ public:
                   get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/conv1_w.npy"),
                   get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/conv1_b.npy"),
                   PadStrideInfo(2, 2, 0, 0))
+              << convolution_hint
               << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
               << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0, DimensionRoundingType::CEIL)))
-              << convolution_hint
+              << ConvolutionMethod::DEFAULT
               << ConvolutionLayer(
                   1U, 1U, 16U,
                   get_weights_accessor(data_path, "/cnn_data/squeezenet_v1_1_model/fire2_squeeze1x1_w.npy"),