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diff --git a/examples/dynamic_fusion/cl_ref_conv2d_elementwise_add.cpp b/examples/dynamic_fusion/cl_ref_conv2d_elementwise_add.cpp
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--- a/examples/dynamic_fusion/cl_ref_conv2d_elementwise_add.cpp
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@@ -1,238 +0,0 @@
-/*
- * Copyright (c) 2022 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef ARM_COMPUTE_CL /* Needed by Utils.cpp to handle OpenCL exceptions properly */
-#error "This example needs to be built with -DARM_COMPUTE_CL"
-#endif /* ARM_COMPUTE_CL */
-
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTuner.h"
-#include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h"
-#include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h"
-
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "utils/TypePrinter.h"
-#include "utils/Utils.h"
-
-#include <cstdlib>
-
-using namespace arm_compute;
-using namespace utils;
-
-#define TICK(clock_name) \
- auto clock_name##_tick = std::chrono::high_resolution_clock::now();
-#define TOCK(clock_name, measurement_map) \
- auto clock_name##_tock = std::chrono::high_resolution_clock::now(); \
- measurement_map["\"" #clock_name "\""] = duration_cast<microseconds>(clock_name##_tock - clock_name##_tick);
-#define TOCK_AVG(clock_name, measurement_map, num_iterations) \
- auto clock_name##_tock = std::chrono::high_resolution_clock::now(); \
- measurement_map["\"" #clock_name "\""] = duration_cast<microseconds>((clock_name##_tock - clock_name##_tick) / (num_iterations));
-
-using std::chrono::duration_cast;
-using std::chrono::microseconds;
-/** A reference for comparing against the fusion of a direct convolution with an elementwise addition:
- * examples/dynamic_fusion/cl_fused_conv2d_elementwise_add.cpp
- */
-class ClRefConv2dEltwiseAddExample : public Example
-{
-public:
- bool do_setup(int argc, char **argv) override
- {
- size_t ih;
- size_t iw;
- size_t ifm;
- size_t wh;
- size_t ww;
- size_t ofm;
- size_t tuner_choice;
- unsigned int pad_x;
- unsigned int pad_y;
- if(argc < 10)
- {
- // Print help
- std::cout << "Usage: ./cl_ref_conv2d_elementwise_add ih iw ifm wh ww ofm tuner_choice(0=Disable, 1=Rapid, 2=Normal, 3=Exhaustive) pad_x pad_y\n";
- std::cout << "Too few or no input_matrices provided. Using shape config = SRGAN_0, tuner_choice=2\n\n";
- ih = 512;
- iw = 512;
- ifm = 64;
- wh = 1;
- ww = 1;
- ofm = 3;
- tuner_choice = 2;
- pad_x = 0;
- pad_y = 0;
- }
- else
- {
- ih = strtol(argv[1], nullptr, 10);
- iw = strtol(argv[2], nullptr, 10);
- ifm = strtol(argv[3], nullptr, 10);
- wh = strtol(argv[4], nullptr, 10);
- ww = strtol(argv[5], nullptr, 10);
- ofm = strtol(argv[6], nullptr, 10);
- tuner_choice = strtol(argv[7], nullptr, 10);
- pad_x = strtol(argv[8], nullptr, 10);
- pad_y = strtol(argv[9], nullptr, 10);
- }
-
- CLTuner *tuner_to_use;
- switch(tuner_choice)
- {
- case 0:
- {
- tuner_to_use = nullptr;
- break;
- }
- case 1:
- {
- tuner.set_tuner_mode(CLTunerMode::RAPID);
- tuner_to_use = &tuner;
- break;
- }
- case 3:
- {
- tuner.set_tuner_mode(CLTunerMode::EXHAUSTIVE);
- tuner_to_use = &tuner;
- break;
- }
- case 2:
- default:
- {
- tuner.set_tuner_mode(CLTunerMode::NORMAL);
- tuner_to_use = &tuner;
- break;
- }
- }
-
- CLScheduler::get().default_init(tuner_to_use);
-
- TICK(startup_time);
- TICK(configure);
-
- /* Computation:
- * out = add_desc(addend, conv2d1x1(direct_conv)(input, weights, bias))
- */
- const auto data_type = DataType::F32;
- const auto data_layout = DataLayout::NHWC;
- const PadStrideInfo conv_info{ 1, 1, pad_x, pad_y };
- const auto t_input_shape = TensorShape(ifm, iw, ih);
- const auto t_weight_shape = TensorShape(ifm, ww, wh, ofm);
- const auto t_bias_shape = TensorShape(ofm);
- const auto t_l1_addend_shape = TensorShape(ofm, iw);
- const auto t_dst_shape = misc::shape_calculator::compute_deep_convolution_shape(t_input_shape, data_layout, t_weight_shape, conv_info);
- std::cout << "input_shape: " << t_input_shape << std::endl;
- std::cout << "weight_shape: " << t_weight_shape << std::endl;
- std::cout << "bias_shape: " << t_bias_shape << std::endl;
- std::cout << "addend_shape: " << t_l1_addend_shape << std::endl;
- std::cout << "dst_shape: " << t_dst_shape << std::endl;
- auto t_input_info = TensorInfo(t_input_shape, 1, data_type, data_layout);
- auto t_weight_info = TensorInfo(t_weight_shape, 1, data_type, data_layout);
- auto t_bias_info = TensorInfo(t_bias_shape, 1, data_type, data_layout);
- auto t_l0_dst_info = TensorInfo(t_dst_shape, 1, data_type, data_layout); // Intermediate tensor for cond3
- auto t_l1_addend_info = TensorInfo(t_l1_addend_shape, 1, data_type, data_layout);
- auto t_dst_info = TensorInfo(t_dst_shape, 1, data_type, data_layout);
-
- // Init tensors
- {
- t_input.allocator()->init(t_input_info);
- t_weight.allocator()->init(t_weight_info);
- t_bias.allocator()->init(t_bias_info);
- t_l1_addend.allocator()->init(t_dst_info);
- t_l0_dst.allocator()->init(t_l0_dst_info);
- t_dst.allocator()->init(t_dst_info);
- }
-
- op0.configure(&t_input, &t_weight, &t_bias, &t_l0_dst, conv_info);
- op1.configure(&t_l0_dst, &t_l1_addend, &t_dst, ConvertPolicy{});
- TOCK(configure, measurements);
-
- TICK(tensor_allocation);
- // Construct tensors
- // Allocate and fill tensors
- {
- t_input.allocator()->allocate();
- t_weight.allocator()->allocate();
- t_bias.allocator()->allocate();
- t_l1_addend.allocator()->allocate();
- t_l0_dst.allocator()->allocate();
- t_dst.allocator()->allocate();
- fill_random_tensor(t_input, -1.f, 1.f);
- fill_random_tensor(t_weight, -1.f, 1.f);
- fill_random_tensor(t_bias, -1.f, 1.f);
- fill_random_tensor(t_l1_addend, -1.f, 1.f);
- }
- TOCK(tensor_allocation, measurements);
- // Dummy run for CLTuner
- TICK(dummy_run);
- op0.run();
- CLScheduler::get().sync();
- TOCK(dummy_run, measurements);
- TOCK(startup_time, measurements);
- return true;
- }
- void do_run() override
- {
- // Run the ops
- op0.run();
- op1.run();
-
- // Make sure all the OpenCL jobs are done executing:
- CLScheduler::get().sync();
- }
-
- void do_teardown() override
- {
- for(auto m : measurements)
- {
- std::cout << m.first << ": " << m.second.count() << "us" << std::endl;
- }
- }
-
-private:
- CLTensor t_input{};
- CLTensor t_weight{};
- CLTensor t_bias{};
- CLTensor t_l1_addend{};
- CLTensor t_l0_dst{};
- CLTensor t_dst{};
- CLDirectConvolutionLayer op0{};
- CLArithmeticAddition op1{};
- CLTuner tuner{};
- std::map<std::string, std::chrono::microseconds> measurements{};
-};
-
-/** Main program for sgemm test
- *
- * @param[in] argc Number of arguments
- * @param[in] argv Arguments ( [optional] Matrix A, [optional] Matrix B, [optional] Matrix C, [optional] alpha, [optional] beta )
- */
-int main(int argc, char **argv)
-{
- return utils::run_example<ClRefConv2dEltwiseAddExample>(argc, argv);
-}
-
-#undef TICK
-#undef TOCK
-#undef TOCK_AVG \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-11 07:02:47 +0000