From 7930db48e12dd3a14c1971f41f5b83527efea281 Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Thu, 22 Nov 2018 17:36:28 +0000 Subject: COMPMID-1728 CL: Implement ArgMax/ArgMin Change-Id: I7eae2e55cc0b0b7bbebb7617299daaca6f75f40c Reviewed-on: https://review.mlplatform.org/292 Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- tests/validation/CL/ArgMinMax.cpp | 138 ++++++++++++++++++++++ tests/validation/fixtures/ArgMinMaxFixture.h | 111 +++++++++++++++++ tests/validation/reference/ReductionOperation.cpp | 103 +++++++++++++--- 3 files changed, 338 insertions(+), 14 deletions(-) create mode 100644 tests/validation/CL/ArgMinMax.cpp create mode 100644 tests/validation/fixtures/ArgMinMaxFixture.h (limited to 'tests') diff --git a/tests/validation/CL/ArgMinMax.cpp b/tests/validation/CL/ArgMinMax.cpp new file mode 100644 index 0000000000..0b873945d3 --- /dev/null +++ b/tests/validation/CL/ArgMinMax.cpp @@ -0,0 +1,138 @@ +/* + * Copyright (c) 2018 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/Types.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/CLTensorAllocator.h" +#include "arm_compute/runtime/CL/functions/CLArgMinMaxLayer.h" + +#include "tests/CL/CLAccessor.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/datasets/SplitDataset.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/ArgMinMaxFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +TEST_SUITE(CL) +TEST_SUITE(ArgMinMax) + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32), // Invalid axis + TensorInfo(TensorShape(27U, 3U, 16U, 2U), 1, DataType::F32), // Invalid output shape + TensorInfo(TensorShape(32U, 16U, 16U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 16U, 16U, 2U), 1, DataType::F32) // Invalid operation + }), + framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(27U, 3U, 1U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 3U, 1U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 16U, 1U, 2U), 1, DataType::U32), + TensorInfo(TensorShape(32U, 16U, 1U, 2U), 1, DataType::F32) + })), + framework::dataset::make("Axis", { 4, 0, 2, 0 })), + framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MAX, ReductionOperation::ARG_IDX_MAX, ReductionOperation::ARG_IDX_MAX, ReductionOperation::MEAN_SUM })), + framework::dataset::make("Expected", { false, false, true, false })), + input_info, output_info, axis, operation, expected) +{ + const Status status = CLArgMinMaxLayer::validate(&input_info.clone()->set_is_resizable(false), axis, &output_info.clone()->set_is_resizable(false), operation); + ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +DATA_TEST_CASE(Configuration, + framework::DatasetMode::ALL, + combine(datasets::SmallShapes(), framework::dataset::make("DataType", { DataType::F16, DataType::F32 })), + shape, data_type) +{ + // Create tensors + CLTensor ref_src = create_tensor(shape, data_type); + CLTensor dst; + + // Create and Configure function + CLArgMinMaxLayer arg_min_max_layer; + arg_min_max_layer.configure(&ref_src, 1, &dst, ReductionOperation::ARG_IDX_MAX); + + // Validate valid region + TensorShape output_shape = shape; + output_shape.set(1, 1); + const ValidRegion valid_region = shape_to_valid_region(output_shape); + validate(dst.info()->valid_region(), valid_region); +} + +template +using CLArgMinMaxValidationFixture = ArgMinMaxValidationFixture; + +TEST_SUITE(Float) +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, + CLArgMinMaxValidationFixture, + framework::DatasetMode::PRECOMMIT, + combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, + CLArgMinMaxValidationFixture, + framework::DatasetMode::NIGHTLY, + combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() // FP16 + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, + CLArgMinMaxValidationFixture, + framework::DatasetMode::PRECOMMIT, + combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, + CLArgMinMaxValidationFixture, + framework::DatasetMode::NIGHTLY, + combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX }))) +{ + // Validate output + validate(CLAccessor(_target), _reference); +} +TEST_SUITE_END() // FP32 +TEST_SUITE_END() // Float +TEST_SUITE_END() // ArgMinMax +TEST_SUITE_END() // CL +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/fixtures/ArgMinMaxFixture.h b/tests/validation/fixtures/ArgMinMaxFixture.h new file mode 100644 index 0000000000..5f5f85c104 --- /dev/null +++ b/tests/validation/fixtures/ArgMinMaxFixture.h @@ -0,0 +1,111 @@ +/* + * Copyright (c) 2018 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_TEST_ARG_MIN_MAX_FIXTURE +#define ARM_COMPUTE_TEST_ARG_MIN_MAX_FIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/Tensor.h" +#include "tests/AssetsLibrary.h" +#include "tests/Globals.h" +#include "tests/IAccessor.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Fixture.h" +#include "tests/validation/Helpers.h" +#include "tests/validation/reference/ReductionOperation.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template +class ArgMinMaxValidationFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape shape, DataType data_type, int axis, ReductionOperation op) + { + _target = compute_target(shape, data_type, axis, op); + _reference = compute_reference(shape, data_type, axis, op); + } + +protected: + template + void fill(U &&tensor) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, 0); + } + + TensorType compute_target(TensorShape &src_shape, DataType data_type, int axis, ReductionOperation op) + { + // Create tensors + TensorType src = create_tensor(src_shape, data_type, 1); + TensorType dst; + + // Create and configure function + FunctionType arg_min_max_layer; + arg_min_max_layer.configure(&src, axis, &dst, op); + + ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Allocate tensors + src.allocator()->allocate(); + dst.allocator()->allocate(); + + ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + + // Fill tensors + fill(AccessorType(src)); + + // Compute function + arg_min_max_layer.run(); + + return dst; + } + + SimpleTensor compute_reference(TensorShape &src_shape, DataType data_type, int axis, ReductionOperation op) + { + // Create reference + SimpleTensor src{ src_shape, data_type, 1 }; + + // Fill reference + fill(src); + + TensorShape output_shape = src_shape; + output_shape.set(axis, 1); + return reference::reduction_operation(src, output_shape, axis, op); + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_ARG_MIN_MAX_FIXTURE */ diff --git a/tests/validation/reference/ReductionOperation.cpp b/tests/validation/reference/ReductionOperation.cpp index 2f103a6f65..37a9be86c0 100644 --- a/tests/validation/reference/ReductionOperation.cpp +++ b/tests/validation/reference/ReductionOperation.cpp @@ -38,10 +38,10 @@ namespace reference { namespace { -template -T reduce_operation(T *ptr, int reduce_elements, ReductionOperation op, int stride) +template +OT reduce_operation(const T *ptr, int reduce_elements, ReductionOperation op, int stride) { - using type = typename std::remove_cv::type; + using type = typename std::remove_cv::type; auto res = type(0); if(std::is_integral::value) @@ -50,7 +50,31 @@ T reduce_operation(T *ptr, int reduce_elements, ReductionOperation op, int strid for(int i = 0; i < reduce_elements; ++i) { auto elem = static_cast(*(ptr + stride * i)); - int_res += (op == ReductionOperation::SUM_SQUARE) ? elem * elem : elem; + + switch(op) + { + case ReductionOperation::ARG_IDX_MIN: + if(static_cast(*(ptr + stride * static_cast(res))) > elem) + { + res = static_cast(i); + } + break; + case ReductionOperation::ARG_IDX_MAX: + if(static_cast(*(ptr + stride * static_cast(res))) < elem) + { + res = static_cast(i); + } + break; + case ReductionOperation::SUM_SQUARE: + int_res += elem * elem; + break; + case ReductionOperation::MEAN_SUM: + case ReductionOperation::SUM: + int_res += elem; + break; + default: + ARM_COMPUTE_ERROR("Operation not supported"); + } } if(op == ReductionOperation::MEAN_SUM && reduce_elements > 0) { @@ -63,7 +87,30 @@ T reduce_operation(T *ptr, int reduce_elements, ReductionOperation op, int strid for(int i = 0; i < reduce_elements; ++i) { auto elem = *(ptr + stride * i); - res += (op == ReductionOperation::SUM_SQUARE) ? elem * elem : elem; + switch(op) + { + case ReductionOperation::ARG_IDX_MIN: + if(*(ptr + stride * static_cast(res)) > elem) + { + res = static_cast(i); + } + break; + case ReductionOperation::ARG_IDX_MAX: + if(*(ptr + stride * static_cast(res)) < elem) + { + res = static_cast(i); + } + break; + case ReductionOperation::SUM_SQUARE: + res += elem * elem; + break; + case ReductionOperation::MEAN_SUM: + case ReductionOperation::SUM: + res += elem; + break; + default: + ARM_COMPUTE_ERROR("Operation not supported"); + } } if(op == ReductionOperation::MEAN_SUM && reduce_elements > 0) { @@ -79,7 +126,9 @@ template SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op) { // Create reference - SimpleTensor dst{ dst_shape, src.data_type(), 1, src.quantization_info() }; + const bool is_arg_min_max = (op == ReductionOperation::ARG_IDX_MIN || op == ReductionOperation::ARG_IDX_MAX); + DataType output_data_type = is_arg_min_max ? DataType::U32 : src.data_type(); + SimpleTensor dst{ dst_shape, output_data_type, 1, src.quantization_info() }; const unsigned int src_width = src.shape().x(); const unsigned int src_height = src.shape().y(); const unsigned int src_depth = src.shape().z(); @@ -94,8 +143,14 @@ SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShap for(unsigned int du = 0; du < upper_dims; ++du) { const T *src_row_ptr = src.data() + du * reduce_elems; - auto res = reduce_operation(src_row_ptr, reduce_elems, op, 1); - dst[du] = res; + if(is_arg_min_max) + { + dst[du] = reduce_operation(src_row_ptr, reduce_elems, op, 1); + } + else + { + dst[du] = reduce_operation(src_row_ptr, reduce_elems, op, 1); + } } } break; @@ -109,8 +164,15 @@ SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShap const int in_offset = du * src_height * src_width + x; const int out_offset = du * src_width + x; const T *src_row_ptr = src.data() + in_offset; - auto res = reduce_operation(src_row_ptr, reduce_elems, op, src_width); - dst[out_offset] = res; + + if(is_arg_min_max) + { + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_width); + } + else + { + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_width); + } } } } @@ -127,8 +189,15 @@ SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShap const int in_offset = du * src_depth * src_height * src_width + y * src_width + x; const int out_offset = du * src_width * src_height + y * src_width + x; const T *src_row_ptr = src.data() + in_offset; - auto res = reduce_operation(src_row_ptr, reduce_elems, op, src_height * src_width); - dst[out_offset] = res; + + if(is_arg_min_max) + { + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_height * src_width); + } + else + { + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_height * src_width); + } } } } @@ -148,8 +217,14 @@ SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShap const int in_offset = du * src_batch * src_depth * src_height * src_width + z * src_width * src_height + y * src_width + x; const int out_offset = du * src_depth * src_height * src_width + z * src_width * src_height + y * src_width + x; const T *src_row_ptr = src.data() + in_offset; - auto res = reduce_operation(src_row_ptr, reduce_elems, op, src_width * src_height * src_depth); - dst[out_offset] = res; + if(is_arg_min_max) + { + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_width * src_height * src_depth); + } + else + { + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_width * src_height * src_depth); + } } } } -- cgit v1.2.1