diff options
-rw-r--r-- | examples/graph_vgg16.cpp | 24 | ||||
-rw-r--r-- | examples/graph_vgg19.cpp | 10 |
2 files changed, 12 insertions, 22 deletions
diff --git a/examples/graph_vgg16.cpp b/examples/graph_vgg16.cpp index 82be97c316..9e8e69411f 100644 --- a/examples/graph_vgg16.cpp +++ b/examples/graph_vgg16.cpp @@ -32,20 +32,6 @@ using namespace arm_compute::utils; using namespace arm_compute::graph::frontend; using namespace arm_compute::graph_utils; -namespace -{ -/** This function checks if we can use GEMM-based convolution trying to allocate a memory of size "size_in_bytes" - * - * @param[in] size_in_bytes Memory size in bytes needed for VGG-16 - * - * @return The convolution layer hint - */ -ConvolutionMethod convolution_hint_vgg16(size_t size_in_bytes) -{ - return ((get_mem_free_from_meminfo() * 1024) >= size_in_bytes) ? ConvolutionMethod::GEMM : ConvolutionMethod::DIRECT; -} -} // namespace - /** Example demonstrating how to implement VGG16's network using the Compute Library's graph API * * @param[in] argc Number of arguments @@ -65,14 +51,12 @@ 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); + 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; - // Check if we can use GEMM-based convolutions evaluating if the platform has at least 1.8 GB of available memory - const size_t memory_required = 1932735283L; - const bool is_opencl = target_hint == Target::CL; ConvolutionMethod first_convolution3x3_hint = is_opencl ? ConvolutionMethod::DIRECT : ConvolutionMethod::GEMM; - ConvolutionMethod convolution3x3_hint = is_opencl ? ConvolutionMethod::WINOGRAD : convolution_hint_vgg16(memory_required); + ConvolutionMethod convolution3x3_hint = ConvolutionMethod::DEFAULT; // Parse arguments if(argc < 2) diff --git a/examples/graph_vgg19.cpp b/examples/graph_vgg19.cpp index 28e1a0fe04..fed2c806ee 100644 --- a/examples/graph_vgg19.cpp +++ b/examples/graph_vgg19.cpp @@ -51,8 +51,12 @@ 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); + 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; // Parse arguments if(argc < 2) @@ -87,6 +91,7 @@ public: } graph << target_hint + << first_convolution3x3_hint << InputLayer(TensorDescriptor(TensorShape(224U, 224U, 3U, 1U), DataType::F32), get_input_accessor(image, std::move(preprocessor))) // Layer 1 @@ -96,6 +101,7 @@ public: get_weights_accessor(data_path, "/cnn_data/vgg19_model/conv1_1_b.npy"), PadStrideInfo(1, 1, 1, 1)) << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)) + << convolution3x3_hint << ConvolutionLayer( 3U, 3U, 64U, get_weights_accessor(data_path, "/cnn_data/vgg19_model/conv1_2_w.npy"), |