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Diffstat (limited to 'tests/validation/CL/UNIT/dynamic_fusion/Integration_OperatorFuseMovenetSubGraph1.cpp')
| -rw-r--r-- | tests/validation/CL/UNIT/dynamic_fusion/Integration_OperatorFuseMovenetSubGraph1.cpp | 402 |
1 files changed, 0 insertions, 402 deletions
diff --git a/tests/validation/CL/UNIT/dynamic_fusion/Integration_OperatorFuseMovenetSubGraph1.cpp b/tests/validation/CL/UNIT/dynamic_fusion/Integration_OperatorFuseMovenetSubGraph1.cpp deleted file mode 100644 index 3a8b7c8ce8..0000000000 --- a/tests/validation/CL/UNIT/dynamic_fusion/Integration_OperatorFuseMovenetSubGraph1.cpp +++ /dev/null @@ -1,402 +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. - */ - -#ifdef ENABLE_EXPERIMENTAL_DYNAMIC_FUSION -#include "arm_compute/core/TensorInfo.h" - -#include "arm_compute/core/CL/CLKernelLibrary.h" -#include "arm_compute/core/experimental/ClWorkload.h" -#include "arm_compute/runtime/CL/CLScheduler.h" -#include "arm_compute/runtime/experimental/ClCompositeOperator.h" -#include "src/core/experimental/dynamic_fusion/WorkloadImpl/ClKernelDescriptors.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(Operator_Fuse_Movenet_SubGraph_1_F32, framework::DatasetMode::ALL) -{ - // Please refer to: https://confluence.arm.com/pages/viewpage.action?pageId=886243697 - /* Computation: - * out = add_desc(addend, conv2d1x1(direct_conv)(input, weights, bias)) - */ - 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, 64); - // const auto t_dst_shape = TensorShape(64, 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_l1_addend_info = TensorInfo(t_dst_shape, 1, data_type, data_layout); - auto t_acc_info = TensorInfo(); // Intermediate tensor for cond3 - auto t_dst_info = TensorInfo(); - - Conv2dDescriptor conv2d_desc{}; - ElementwiseDescriptor add_desc{ ArithmeticOperation::ADD }; - - // 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 }; - SimpleTensor<float> ref_t_l1_addend{ 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()); - fill<float>(ref_t_l1_addend, 2, 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 ref_t_l1_addend_nchw = reference::permute(ref_t_l1_addend, 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_desc.stride.x(), conv2d_desc.stride.y(), conv2d_desc.pad.left, conv2d_desc.pad.right, conv2d_desc.pad.top, conv2d_desc.pad.bottom, DimensionRoundingType{}); - auto ref_t_dst_nchw = reference::arithmetic_operation( - ArithmeticOperation::ADD, - ref_t_l1_addend_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_desc.dilation), - data_type, - ConvertPolicy{}); - const auto ref_t_dst = reference::permute(ref_t_dst_nchw, PermutationVector(2U, 0U, 1U)); - - CLScheduler::get().default_reinit(); - const auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); - OperatorGraph op_graph; - - const auto op_t_input = add_tensor(op_graph, t_input_info); - const auto op_t_weight = add_tensor(op_graph, t_weight_info); - const auto op_t_l1_addend = add_tensor(op_graph, t_l1_addend_info); - const auto op_t_acc = add_tensor(op_graph, t_acc_info); // temp accumulator; TensorInfo to be inferred - const auto op_t_dst = add_tensor(op_graph, t_dst_info); - - auto conv2d = add_op_conv2d(op_graph, conv2d_desc, op_t_input, op_t_weight, op_t_acc); - force_conv2d_method(op_graph, conv2d, ConvolutionMethod::DIRECT); - add_op_elementwise_op(op_graph, add_desc, op_t_acc, op_t_l1_addend, op_t_dst); - - const ClWorkloadContext workload_ctx{ GpuInfo{ CLScheduler::get().target() } }; - ClWorkload workload; - build(workload, op_graph, workload_ctx); - - ClCompositeOperator op; - op.configure(cl_compile_ctx, workload); - - // Construct tensors - CLTensor t_input{}; - CLTensor t_weight{}; - CLTensor t_l1_addend{}; - CLTensor t_dst{}; - - // Init tensors - t_input.allocator()->init(t_input_info); - t_weight.allocator()->init(t_weight_info); - t_l1_addend.allocator()->init(t_dst_info); - t_dst.allocator()->init(t_dst_info); - - // Allocate and fill tensors - t_input.allocator()->allocate(); - t_weight.allocator()->allocate(); - t_l1_addend.allocator()->allocate(); - t_dst.allocator()->allocate(); - fill<float>(CLAccessor(t_input), 0, library.get()); - fill<float>(CLAccessor(t_weight), 1, library.get()); - fill<float>(CLAccessor(t_l1_addend), 2, library.get()); - // "Pack" tensors - OpTensorBinding bp_tensors({ { op_t_input, &t_input }, - { op_t_weight, &t_weight }, - { op_t_l1_addend, &t_l1_addend }, - { op_t_dst, &t_dst } - }); - - // Populate prepare and run pack-maps (including allocating aux tensors) - ClAuxTensorData aux_tensor_data{}; - TensorPackMap prepare_pack_map{}; - TensorPackMap run_pack_map{}; - bind_tensors(aux_tensor_data, prepare_pack_map, run_pack_map, workload, bp_tensors); - - op.prepare(prepare_pack_map); - op.run(run_pack_map); - 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(Unsupported) -TEST_CASE(DataType_QASYMM8, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::QASYMM8; - const auto data_layout = DataLayout::NHWC; - const auto t_input_shape = TensorShape(384, 12, 12); - const auto t_weight_shape = TensorShape(384, 1, 1, 64); - const auto t_dst_shape = TensorShape(64, 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_l1_addend_info = TensorInfo(t_dst_shape, 1, data_type, data_layout); - auto t_acc_info = TensorInfo(t_dst_shape, 1, data_type, data_layout); - auto t_dst_info = TensorInfo(t_dst_shape, 1, data_type, data_layout); - - Conv2dDescriptor conv2d_desc{}; - ElementwiseDescriptor add_desc{}; - - OperatorGraph op_graph; - - const auto op_t_input = add_tensor(op_graph, t_input_info); - const auto op_t_weight = add_tensor(op_graph, t_weight_info); - const auto op_t_l1_addend = add_tensor(op_graph, t_l1_addend_info); - const auto op_t_acc = add_tensor(op_graph, t_acc_info); // temp accumulator; TensorInfo to be inferred - const auto op_t_dst = add_tensor(op_graph, t_dst_info); - - auto conv2d = add_op_conv2d(op_graph, conv2d_desc, op_t_input, op_t_weight, op_t_acc); - add_op_elementwise_op(op_graph, add_desc, op_t_acc, op_t_l1_addend, op_t_dst); - force_conv2d_method(op_graph, conv2d, ConvolutionMethod::DIRECT); - - const ClWorkloadContext workload_ctx{ GpuInfo{ CLScheduler::get().target() } }; - ClWorkload workload; - const auto success = build(workload, op_graph, workload_ctx); - - ARM_COMPUTE_EXPECT(!bool(success), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bool(ClCompositeOperator::validate(workload)), framework::LogLevel::ERRORS); -} -TEST_CASE(DataLayout_NCHW, framework::DatasetMode::ALL) -{ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NCHW; - const auto t_input_shape = TensorShape(384, 12, 12); - const auto t_weight_shape = TensorShape(384, 1, 1, 64); - const auto t_dst_shape = TensorShape(64, 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(t_dst_shape, 1, data_type, data_layout); - - Conv2dDescriptor conv2d_desc{}; - - OperatorGraph op_graph; - - const auto op_t_input = add_tensor(op_graph, t_input_info); - const auto op_t_weight = add_tensor(op_graph, t_weight_info); - const auto op_t_dst = add_tensor(op_graph, t_dst_info); - - auto conv2d = add_op_conv2d(op_graph, conv2d_desc, op_t_input, op_t_weight, op_t_dst); - force_conv2d_method(op_graph, conv2d, ConvolutionMethod::DIRECT); - const ClWorkloadContext workload_ctx{ GpuInfo{ CLScheduler::get().target() } }; - ClWorkload workload; - const auto success = build(workload, op_graph, workload_ctx); - - ARM_COMPUTE_EXPECT(!bool(success), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bool(ClCompositeOperator::validate(workload)), framework::LogLevel::ERRORS); -} -TEST_SUITE_END() // Unsupported - -TEST_SUITE(Invalid) -TEST_CASE(Multiple_Complex_Ops_0, framework::DatasetMode::ALL) -{ - /* Computation: - * out = conv2d(conv2d(l0_input, l0_weight), l1_weight) - */ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - const auto t_l0_input_shape = TensorShape(1024, 56, 56); - const auto t_l0_weight_shape = TensorShape(512, 1024, 1, 1); - const auto t_l1_weight_shape = TensorShape(512, 256, 1, 1); - - auto t_l0_input_info = TensorInfo(t_l0_input_shape, 1, data_type, data_layout); - auto t_l0_weight_info = TensorInfo(t_l0_weight_shape, 1, data_type, data_layout); - auto t_l1_weight_info = TensorInfo(t_l1_weight_shape, 1, data_type, data_layout); - auto t_l0_dst_info = TensorInfo(); - auto t_dst_info = TensorInfo(); - - OperatorGraph op_graph; - const auto conv2d_desc = Conv2dDescriptor{}; - - const auto op_t_l0_input = add_tensor(op_graph, t_l0_input_info); - const auto op_t_l0_weight = add_tensor(op_graph, t_l0_weight_info); - const auto op_t_l1_weight = add_tensor(op_graph, t_l1_weight_info); - const auto op_t_l0_dst = add_tensor(op_graph, t_l0_dst_info); // temp accumulator; TensorInfo to be inferred - const auto op_t_dst = add_tensor(op_graph, t_dst_info); - - add_op_conv2d(op_graph, conv2d_desc, op_t_l0_input, op_t_l0_weight, op_t_l0_dst); - add_op_conv2d(op_graph, conv2d_desc, op_t_l0_dst, op_t_l1_weight, op_t_dst); - - const ClWorkloadContext workload_ctx{ GpuInfo{ CLScheduler::get().target() } }; - ClWorkload workload; - const auto success = build(workload, op_graph, workload_ctx); - - ARM_COMPUTE_EXPECT(!bool(success), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bool(ClCompositeOperator::validate(workload)), framework::LogLevel::ERRORS); -} -TEST_CASE(Enlarging_Execution_Space, framework::DatasetMode::ALL) -{ - /* Computation: - * out = add(l2_lhs, add(add(l0_lhs, l0_rhs), l1_rhs)) - */ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - const auto t_l0_lhs_shape = TensorShape(1, 256, 3); - const auto t_l0_rhs_shape = TensorShape(1, 256, 3); - const auto t_l1_rhs_shape = TensorShape(1, 1, 3); - const auto t_l2_lhs_shape = TensorShape(1024, 1, 3); - - auto t_l0_lhs_info = TensorInfo(t_l0_lhs_shape, 1, data_type, data_layout); - auto t_l0_rhs_info = TensorInfo(t_l0_rhs_shape, 1, data_type, data_layout); - auto t_l1_rhs_info = TensorInfo(t_l1_rhs_shape, 1, data_type, data_layout); - auto t_l2_lhs_info = TensorInfo(t_l2_lhs_shape, 1, data_type, data_layout); - auto t_l0_dst_info = TensorInfo(); - auto t_l1_dst_info = TensorInfo(); - auto t_dst_info = TensorInfo(); - - OperatorGraph op_graph; - const auto add_desc = ElementwiseDescriptor{}; - - const auto op_t_l0_lhs = add_tensor(op_graph, t_l0_lhs_info); - const auto op_t_l0_rhs = add_tensor(op_graph, t_l0_rhs_info); - const auto op_t_l1_rhs = add_tensor(op_graph, t_l1_rhs_info); - const auto op_t_l2_lhs = add_tensor(op_graph, t_l2_lhs_info); - const auto op_t_l0_dst = add_tensor(op_graph, t_l0_dst_info); // temp accumulator; TensorInfo to be inferred - const auto op_t_l1_dst = add_tensor(op_graph, t_l1_dst_info); // temp accumulator; TensorInfo to be inferred - const auto op_t_dst = add_tensor(op_graph, t_dst_info); - - add_op_elementwise_op(op_graph, add_desc, op_t_l0_lhs, op_t_l0_rhs, op_t_l0_dst); - add_op_elementwise_op(op_graph, add_desc, op_t_l0_dst, op_t_l1_rhs, op_t_l1_dst); - add_op_elementwise_op(op_graph, add_desc, op_t_l1_dst, op_t_l2_lhs, op_t_dst); - - const ClWorkloadContext workload_ctx{ GpuInfo{ CLScheduler::get().target() } }; - ClWorkload workload; - const auto success = build(workload, op_graph, workload_ctx); - - ARM_COMPUTE_EXPECT(!bool(success), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bool(ClCompositeOperator::validate(workload)), framework::LogLevel::ERRORS); -} -TEST_CASE(Root_Simple_And_Complex, framework::DatasetMode::ALL) -{ - /* Computation: - * out = add(conv(l0_0_input, l0_0_weight), add(l0_1_lhs, l0_1_rhs)) - */ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - - const auto t_l0_0_input_shape = TensorShape(128, 21, 21); - const auto t_l0_0_weight_shape = TensorShape(144, 128, 1, 1); - const auto t_l0_1_lhs_shape = TensorShape(144, 21, 21); - const auto t_l0_1_rhs_shape = TensorShape(1, 1, 21); - - auto t_l0_0_input_info = TensorInfo(t_l0_0_input_shape, 1, data_type, data_layout); - auto t_l0_0_weight_info = TensorInfo(t_l0_0_weight_shape, 1, data_type, data_layout); - auto t_l0_1_lhs_info = TensorInfo(t_l0_1_lhs_shape, 1, data_type, data_layout); - auto t_l0_1_rhs_info = TensorInfo(t_l0_1_rhs_shape, 1, data_type, data_layout); - auto t_l0_0_dst_info = TensorInfo(); - auto t_l0_1_dst_info = TensorInfo(); - auto t_dst_info = TensorInfo(); - - OperatorGraph op_graph; - const auto conv2d_desc = Conv2dDescriptor{}; - const auto add_desc = ElementwiseDescriptor{}; - - const auto op_t_l0_0_input = add_tensor(op_graph, t_l0_0_input_info); - const auto op_t_l0_0_weight = add_tensor(op_graph, t_l0_0_weight_info); - const auto op_t_l0_1_lhs = add_tensor(op_graph, t_l0_1_lhs_info); - const auto op_t_l0_1_rhs = add_tensor(op_graph, t_l0_1_rhs_info); - const auto op_t_l0_0_dst = add_tensor(op_graph, t_l0_0_dst_info); // temp accumulator; TensorInfo to be inferred - const auto op_t_l0_1_dst = add_tensor(op_graph, t_l0_1_dst_info); // temp accumulator; TensorInfo to be inferred - const auto op_t_dst = add_tensor(op_graph, t_dst_info); - - add_op_conv2d(op_graph, conv2d_desc, op_t_l0_0_input, op_t_l0_0_weight, op_t_l0_0_dst); - add_op_elementwise_op(op_graph, add_desc, op_t_l0_1_lhs, op_t_l0_1_rhs, op_t_l0_1_dst); - add_op_elementwise_op(op_graph, add_desc, op_t_l0_0_dst, op_t_l0_1_dst, op_t_dst); - - const ClWorkloadContext workload_ctx{ GpuInfo{ CLScheduler::get().target() } }; - ClWorkload workload; - const auto success = build(workload, op_graph, workload_ctx); - - ARM_COMPUTE_EXPECT(!bool(success), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bool(ClCompositeOperator::validate(workload)), framework::LogLevel::ERRORS); -} -TEST_CASE(Loop, framework::DatasetMode::ALL) -{ - /* Computation: - * tensor state0; - * state1 = add(l0_lhs, state0) - * state0 = add(l1_lhs, state1) - */ - const auto data_type = DataType::F32; - const auto data_layout = DataLayout::NHWC; - - const auto t_shape = TensorShape(13, 21); - - auto t_l0_lhs_info = TensorInfo(t_shape, 1, data_type, data_layout); - auto t_l1_lhs_info = TensorInfo(t_shape, 1, data_type, data_layout); - auto state0_info = TensorInfo(t_shape, 1, data_type, data_layout); - auto state1_info = TensorInfo(); - - OperatorGraph op_graph; - const auto conv2d_desc = Conv2dDescriptor{}; - const auto add_desc = ElementwiseDescriptor{}; - - const auto op_t_l0_lhs = add_tensor(op_graph, t_l0_lhs_info); - const auto op_t_l1_lhs = add_tensor(op_graph, t_l1_lhs_info); - const auto op_t_state0 = add_tensor(op_graph, state0_info); - const auto op_t_state1 = add_tensor(op_graph, state1_info); - - add_op_conv2d(op_graph, conv2d_desc, op_t_l0_lhs, op_t_state0, op_t_state1); - add_op_elementwise_op(op_graph, add_desc, op_t_l1_lhs, op_t_state1, op_t_state0); - - const ClWorkloadContext workload_ctx{ GpuInfo{ CLScheduler::get().target() } }; - ClWorkload workload; - const auto success = build(workload, op_graph, workload_ctx); - - ARM_COMPUTE_EXPECT(!bool(success), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bool(ClCompositeOperator::validate(workload)), framework::LogLevel::ERRORS); -} -TEST_SUITE_END() // Invalid - -TEST_SUITE_END() // DYNAMIC_FUSION -TEST_SUITE_END() // INTEGRATION -TEST_SUITE_END() // CL -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* ENABLE_EXPERIMENTAL_DYNAMIC_FUSION */
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