From e083771a1f28c34485f0d0054e2645070df98846 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Tue, 12 Jun 2018 11:30:50 +0100 Subject: COMPMID-1160 Turn Graph hints into heuristics Change-Id: Id24c2f07c59d863f8e1af6a1afbf6a542b2b9954 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/135142 Tested-by: Jenkins Reviewed-by: Pablo Tello Reviewed-by: Anthony Barbier --- examples/graph_alexnet.cpp | 12 +++--------- examples/graph_mobilenet.cpp | 4 +--- examples/graph_vgg16.cpp | 12 +++--------- examples/graph_vgg19.cpp | 6 ------ 4 files changed, 7 insertions(+), 27 deletions(-) (limited to 'examples') diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp index 9e6d91962e..5328662b6d 100644 --- a/examples/graph_alexnet.cpp +++ b/examples/graph_alexnet.cpp @@ -53,13 +53,9 @@ public: std::unique_ptr preprocessor = arm_compute::support::cpp14::make_unique(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); - - const bool is_neon = (target_hint == Target::NEON); - ConvolutionMethod convolution_5x5_hint = is_neon ? ConvolutionMethod::GEMM : ConvolutionMethod::DIRECT; - ConvolutionMethod convolution_3x3_hint = ConvolutionMethod::DEFAULT; - FastMathHint fast_math_hint = FastMathHint::DISABLED; + const int target = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0; + Target target_hint = set_target_hint(target); + FastMathHint fast_math_hint = FastMathHint::DISABLED; // Parse arguments if(argc < 2) @@ -117,7 +113,6 @@ public: << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)).set_name("norm1") << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool1") // Layer 2 - << convolution_5x5_hint << ConvolutionLayer( 5U, 5U, 256U, get_weights_accessor(data_path, "/cnn_data/alexnet_model/conv2_w.npy"), @@ -127,7 +122,6 @@ public: << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("relu2") << NormalizationLayer(NormalizationLayerInfo(NormType::CROSS_MAP, 5, 0.0001f, 0.75f)).set_name("norm2") << PoolingLayer(PoolingLayerInfo(PoolingType::MAX, 3, PadStrideInfo(2, 2, 0, 0))).set_name("pool2") - << convolution_3x3_hint // Layer 3 << ConvolutionLayer( 3U, 3U, 384U, diff --git a/examples/graph_mobilenet.cpp b/examples/graph_mobilenet.cpp index 50dc02482f..40243bb111 100644 --- a/examples/graph_mobilenet.cpp +++ b/examples/graph_mobilenet.cpp @@ -35,7 +35,7 @@ using namespace arm_compute::graph_utils; /** Example demonstrating how to implement MobileNet's network using the Compute Library's graph API * * @param[in] argc Number of arguments - * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] data layout, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) ) + * @param[in] argv Arguments ( [optional] Target (0 = NEON, 1 = OpenCL, 2 = OpenCL with Tuner), [optional] Model ID (0 = MobileNetV1_1.0_224, 1 = MobileNetV1_0.75_160), [optional] Path to the weights folder, [optional] image, [optional] labels, [optional] data layout, [optional] Fast math for convolution layer (0 = DISABLED, 1 = ENABLED) ) */ class GraphMobilenetExample : public Example { @@ -52,7 +52,6 @@ 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 = ConvolutionMethod::GEMM; DepthwiseConvolutionMethod depthwise_convolution_hint = DepthwiseConvolutionMethod::OPTIMIZED_3x3; FastMathHint fast_math_hint = FastMathHint::DISABLED; @@ -133,7 +132,6 @@ public: } graph << target_hint - << convolution_hint << depthwise_convolution_hint << fast_math_hint << InputLayer(input_descriptor, diff --git a/examples/graph_vgg16.cpp b/examples/graph_vgg16.cpp index 72e724025b..d70c56eadd 100644 --- a/examples/graph_vgg16.cpp +++ b/examples/graph_vgg16.cpp @@ -51,13 +51,9 @@ public: std::unique_ptr preprocessor = arm_compute::support::cpp14::make_unique(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); - const bool is_opencl = target_hint == Target::CL; - - ConvolutionMethod first_convolution3x3_hint = is_opencl ? ConvolutionMethod::DIRECT : ConvolutionMethod::GEMM; - ConvolutionMethod convolution3x3_hint = ConvolutionMethod::DEFAULT; - FastMathHint fast_math_hint = FastMathHint::DISABLED; + const int target = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0; + Target target_hint = set_target_hint(target); + FastMathHint fast_math_hint = FastMathHint::DISABLED; // Parse arguments if(argc < 2) @@ -102,7 +98,6 @@ public: graph << target_hint << fast_math_hint - << first_convolution3x3_hint << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32), get_input_accessor(image, std::move(preprocessor))) // Layer 1 @@ -113,7 +108,6 @@ public: PadStrideInfo(1, 1, 1, 1)) .set_name("conv1_1") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv1_1/Relu") - << convolution3x3_hint // Layer 2 << ConvolutionLayer( 3U, 3U, 64U, diff --git a/examples/graph_vgg19.cpp b/examples/graph_vgg19.cpp index b15c3f2def..8a0ec6fdbd 100644 --- a/examples/graph_vgg19.cpp +++ b/examples/graph_vgg19.cpp @@ -54,10 +54,6 @@ public: const int target = argc > 1 ? std::strtol(argv[1], nullptr, 10) : 0; Target target_hint = set_target_hint(target); FastMathHint fast_math_hint = FastMathHint::DISABLED; - const bool is_opencl = target_hint == Target::CL; - - ConvolutionMethod first_convolution3x3_hint = is_opencl ? ConvolutionMethod::DIRECT : ConvolutionMethod::GEMM; - ConvolutionMethod convolution3x3_hint = ConvolutionMethod::DEFAULT; // Parse arguments if(argc < 2) @@ -101,7 +97,6 @@ public: } graph << target_hint - << first_convolution3x3_hint << fast_math_hint << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32), get_input_accessor(image, std::move(preprocessor))) @@ -113,7 +108,6 @@ public: PadStrideInfo(1, 1, 1, 1)) .set_name("conv1_1") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv1_1/Relu") - << convolution3x3_hint << ConvolutionLayer( 3U, 3U, 64U, get_weights_accessor(data_path, "/cnn_data/vgg19_model/conv1_2_w.npy"), -- cgit v1.2.1