From 7e9391bb14d219cda310bff355669b5964b1f576 Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Fri, 5 Oct 2018 14:49:28 +0100 Subject: COMPMID-1574 Implement ReduceMean in OpenCL Change-Id: Id331199f569f52a37280a9ada5bf84694580b93c Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/152843 Tested-by: bsgcomp Reviewed-by: Michele DiGiorgio --- tests/validation/fixtures/ReduceMeanFixture.h | 161 ++++++++++++++++++++++++++ 1 file changed, 161 insertions(+) create mode 100644 tests/validation/fixtures/ReduceMeanFixture.h (limited to 'tests/validation/fixtures') diff --git a/tests/validation/fixtures/ReduceMeanFixture.h b/tests/validation/fixtures/ReduceMeanFixture.h new file mode 100644 index 0000000000..6debd4a038 --- /dev/null +++ b/tests/validation/fixtures/ReduceMeanFixture.h @@ -0,0 +1,161 @@ +/* + * 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_REDUCE_MEAN_FIXTURE +#define ARM_COMPUTE_TEST_REDUCE_MEAN_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/reference/ReductionOperation.h" +#include "tests/validation/reference/ReshapeLayer.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template +class ReduceMeanValidationFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info) + { + _target = compute_target(shape, data_type, axis, keep_dims, quantization_info); + _reference = compute_reference(shape, data_type, axis, keep_dims, quantization_info); + } + +protected: + template + void fill(U &&tensor) + { + if(!is_data_type_quantized(tensor.data_type())) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, 0); + } + else + { + const QuantizationInfo quant_info = tensor.quantization_info(); + const int min_bound = quant_info.quantize(-1.f, RoundingPolicy::TO_NEAREST_UP); + const int max_bound = quant_info.quantize(1.f, RoundingPolicy::TO_NEAREST_UP); + std::uniform_int_distribution<> distribution(min_bound, max_bound); + + library->fill(tensor, distribution, 0); + } + } + + TensorType compute_target(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info) + { + // Create tensors + TensorType src = create_tensor(src_shape, data_type, 1, quantization_info); + TensorType dst; + + // Create and configure function + FunctionType reduction_mean; + reduction_mean.configure(&src, axis, keep_dims, &dst); + + 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 + reduction_mean.run(); + + return dst; + } + + SimpleTensor compute_reference(TensorShape &src_shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info) + { + // Create reference + SimpleTensor src{ src_shape, data_type, 1, quantization_info }; + + // Fill reference + fill(src); + + SimpleTensor out; + for(unsigned int i = 0; i < axis.num_dimensions(); ++i) + { + TensorShape output_shape = i == 0 ? src_shape : out.shape(); + output_shape.set(axis[i], 1); + out = reference::reduction_operation(i == 0 ? src : out, output_shape, axis[i], ReductionOperation::MEAN_SUM); + } + + if(!keep_dims) + { + TensorShape output_shape = src_shape; + for(unsigned int i = 0; i < axis.num_dimensions(); ++i) + { + output_shape.remove_dimension(axis[i]); + } + + out = reference::reshape_layer(out, output_shape); + } + return out; + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; + +template +class ReduceMeanQuantizedFixture : public ReduceMeanValidationFixture +{ +public: + template + void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims, QuantizationInfo quantization_info = QuantizationInfo()) + { + ReduceMeanValidationFixture::setup(shape, data_type, axis, keep_dims, quantization_info); + } +}; + +template +class ReduceMeanFixture : public ReduceMeanValidationFixture +{ +public: + template + void setup(TensorShape shape, DataType data_type, Coordinates axis, bool keep_dims) + { + ReduceMeanValidationFixture::setup(shape, data_type, axis, keep_dims, QuantizationInfo()); + } +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_REDUCE_MEAN_FIXTURE */ -- cgit v1.2.1