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Diffstat (limited to 'tests/validation')
-rw-r--r-- | tests/validation/dynamic_fusion/gpu/Integration.cpp | 201 |
1 files changed, 201 insertions, 0 deletions
diff --git a/tests/validation/dynamic_fusion/gpu/Integration.cpp b/tests/validation/dynamic_fusion/gpu/Integration.cpp new file mode 100644 index 0000000000..87720a629d --- /dev/null +++ b/tests/validation/dynamic_fusion/gpu/Integration.cpp @@ -0,0 +1,201 @@ +/* + * 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. + */ + +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h" +#include "arm_compute/dynamic_fusion/sketch/OperatorAttributes.h" +#include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h" +#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuConv2d.h" +#include "arm_compute/runtime/CL/CLScheduler.h" + +#include "src/gpu/cl/operators/ClAdd.h" +#include "src/gpu/cl/operators/ClConv2d.h" + +#include "tests/CL/CLAccessor.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/validation/CL/UNIT/dynamic_fusion/Utils.h" +#include "tests/validation/Validation.h" +#include "tests/validation/reference/ConvolutionLayer.h" +#include "tests/validation/reference/ElementwiseOperations.h" +#include "tests/validation/reference/Permute.h" + +#ifdef ARM_COMPUTE_ASSERTS_ENABLED +#include "tests/SimpleTensorPrinter.h" +#endif /* ARM_COMPUTE_ASSERTS_ENABLED */ + +using namespace arm_compute::experimental::dynamic_fusion; +using namespace arm_compute::test::validation::utils; + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +TEST_SUITE(CL) +TEST_SUITE(INTEGRATION) +TEST_SUITE(DYNAMIC_FUSION) +TEST_CASE(Conv2d, framework::DatasetMode::ALL) +{ + /* Computation: + * out = conv2d1x1(direct_conv)(input, weights, bias) + */ + CLScheduler::get().default_reinit(); + + const auto data_type = DataType::F32; + const auto data_layout = DataLayout::NHWC; + const auto t_input_shape = TensorShape(384, 12, 12); + const auto t_weight_shape = TensorShape(384, 1, 1, 16); + const auto t_dst_shape = TensorShape(16, 12, 12); + + // Create a new workload sketch + auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); + auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx }; + GpuWorkloadSketch sketch{ &gpu_ctx }; + + // Fuse conv2d + Conv2dAttributes conv2d_attr{}; + auto input_info = sketch.create_tensor_info(t_input_shape, 1, data_type, data_layout); + auto weight_info = sketch.create_tensor_info(TensorInfo(t_weight_shape, 1, data_type, data_layout)); + auto dst_info = sketch.create_tensor_info(); + GpuConv2d::create_op(sketch, &input_info, &weight_info, nullptr, &dst_info, conv2d_attr); + + // Configure runtime + ClWorkloadRuntime runtime; + runtime.configure(sketch); + + // (Important) Allocate auxiliary tensor memory if there are any + // Instead of using ACL allocated memory, the user can choose to import memory into the tensors + for(auto &data : runtime.get_auxiliary_tensors()) + { + CLTensor *tensor = data.first; + AuxMemoryInfo aux_mem_req = data.second; + tensor->allocator()->init(*data.first->info(), aux_mem_req.alignment); + tensor->allocator()->allocate(); // Use ACL allocated memory + // auto buf = cl::Buffer(); + // tensor->allocator()->import_memory(buf); // Or, import external memory + } + + // Construct user tensors + CLTensor t_input{}; + CLTensor t_weight{}; + CLTensor t_dst{}; + + // Initialize user tensors + t_input.allocator()->init(input_info); + t_weight.allocator()->init(weight_info); + t_dst.allocator()->init(dst_info); + + // Allocate and fill user tensors + // Instead of using ACL allocator, the user can choose to import memory into the tensors + t_input.allocator()->allocate(); + t_weight.allocator()->allocate(); + t_dst.allocator()->allocate(); + fill<float>(CLAccessor(t_input), 0, library.get()); + fill<float>(CLAccessor(t_weight), 1, library.get()); + + // Run runtime + runtime.run({ &t_input, &t_weight, &t_dst }); + + // Create reference + SimpleTensor<float> ref_t_input{ t_input_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC }; + SimpleTensor<float> ref_t_weight{ t_weight_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC }; + SimpleTensor<float> ref_t_bias_placeholder{ t_dst_shape, data_type, 1, QuantizationInfo(), DataLayout::NHWC }; + + // Fill reference + fill<float>(ref_t_input, 0, library.get()); + fill<float>(ref_t_weight, 1, library.get()); + + auto ref_t_input_nchw = reference::permute(ref_t_input, PermutationVector(1U, 2U, 0U)); + auto ref_t_weight_nchw = reference::permute(ref_t_weight, PermutationVector(1U, 2U, 0U)); + auto ref_t_bias_placeholder_nchw = reference::permute(ref_t_bias_placeholder, PermutationVector(1U, 2U, 0U)); + auto t_dst_shape_nchw = t_dst_shape; + permute(t_dst_shape_nchw, PermutationVector(1U, 2U, 0U)); + + PadStrideInfo legacy_pad_stride(conv2d_attr.stride().x(), conv2d_attr.stride().y(), conv2d_attr.pad().left, conv2d_attr.pad().right, conv2d_attr.pad().top, conv2d_attr.pad().bottom, + DimensionRoundingType{}); + auto ref_t_dst_nchw = reference::convolution_layer(ref_t_input_nchw, ref_t_weight_nchw, ref_t_bias_placeholder_nchw, t_dst_shape_nchw, legacy_pad_stride, conv2d_attr.dilation()); + const auto ref_t_dst = reference::permute(ref_t_dst_nchw, PermutationVector(2U, 0U, 1U)); + + RelativeTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for floating point data types */ + validate(CLAccessor(t_dst), ref_t_dst_nchw, tolerance_f32); +} +TEST_SUITE(Invalid_Fusion_Should_Fail) +TEST_CASE(Multiple_Complex_Ops_0, framework::DatasetMode::ALL) +{ + /* Computation: + * out = conv2d(conv2d(l0_input, l0_weight), l1_weight) + */ + CLScheduler::get().default_reinit(); + + const auto data_type = DataType::F32; + const auto data_layout = DataLayout::NHWC; + const auto t_input_shape = TensorShape(384, 12, 12); + const auto t_weight_shape = TensorShape(384, 1, 1, 16); + const auto t_dst_shape = TensorShape(16, 12, 12); + 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_dst_info = TensorInfo(); + + Conv2dAttributes conv2d_attr{}; + + // Create a new workload sketch + auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); + auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx }; + GpuWorkloadSketch sketch{ &gpu_ctx }; + + // Create tensor infos + auto input_info = sketch.create_tensor_info(t_input_shape, 1, data_type, data_layout); + auto weight_info = sketch.create_tensor_info(TensorInfo(t_weight_shape, 1, data_type, data_layout)); + auto dst_info = sketch.create_tensor_info(); + + // Fuse conv2d into the workload + { + // Validate operator + const auto success = GpuConv2d::validate_op(sketch, &input_info, &weight_info, nullptr, &dst_info, conv2d_attr); + ARM_COMPUTE_EXPECT(bool(success), framework::LogLevel::ERRORS); + + GpuConv2d::create_op(sketch, &input_info, &weight_info, nullptr, &dst_info, conv2d_attr); + } + + // Create tensor infos + auto weight_info_2 = sketch.create_tensor_info(t_weight_info); + auto dst_info_2 = sketch.create_tensor_info(); + + // Fuse conv2d into the workload + { + // Validate operator, should fail + const auto success = GpuConv2d::validate_op(sketch, &dst_info, &weight_info_2, nullptr, &dst_info_2, conv2d_attr); + ARM_COMPUTE_EXPECT(!bool(success), framework::LogLevel::ERRORS); + } +} +TEST_SUITE_END() // Invalid_Fusion_Should_Fail +TEST_SUITE_END() // DYNAMIC_FUSION +TEST_SUITE_END() // INTEGRATION +TEST_SUITE_END() // CL +} // namespace validation +} // namespace test +} // namespace arm_compute |