From aea14c63e2efeda9d5f7492099389d439c65204f Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Thu, 3 Jan 2019 11:10:25 +0000 Subject: COMPMID-1764 NEON: Implement ArgMax/ArgMin Change-Id: Ibe23aa90b36ffd8553d1d1c35fada5d300fab829 Reviewed-on: https://review.mlplatform.org/475 Reviewed-by: Isabella Gottardi Tested-by: Arm Jenkins Reviewed-by: Giuseppe Rossini --- tests/validation/NEON/ArgMinMax.cpp | 167 +++++++++++++++++++++ tests/validation/fixtures/ArgMinMaxFixture.h | 60 ++++++-- tests/validation/fixtures/ReduceMeanFixture.h | 4 +- .../fixtures/ReductionOperationFixture.h | 4 +- tests/validation/reference/L2NormalizeLayer.cpp | 4 +- tests/validation/reference/ReductionOperation.cpp | 59 ++------ tests/validation/reference/ReductionOperation.h | 8 +- 7 files changed, 239 insertions(+), 67 deletions(-) create mode 100644 tests/validation/NEON/ArgMinMax.cpp (limited to 'tests') diff --git a/tests/validation/NEON/ArgMinMax.cpp b/tests/validation/NEON/ArgMinMax.cpp new file mode 100644 index 0000000000..611495a41d --- /dev/null +++ b/tests/validation/NEON/ArgMinMax.cpp @@ -0,0 +1,167 @@ +/* + * Copyright (c) 2018-2019 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/NEON/functions/NEArgMinMaxLayer.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" + +#include "tests/NEON/Accessor.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(NEON) +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 = NEArgMinMaxLayer::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 + Tensor ref_src = create_tensor(shape, data_type); + Tensor dst; + + // Create and Configure function + NEArgMinMaxLayer 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 NEArgMinMaxValidationFixture = ArgMinMaxValidationFixture; + +TEST_SUITE(Float) +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, + NEArgMinMaxValidationFixture, + 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(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, + NEArgMinMaxValidationFixture, + 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(Accessor(_target), _reference); +} +TEST_SUITE_END() // FP16 +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + +template +using NEArgMinMaxQuantizedValidationFixture = ArgMinMaxValidationQuantizedFixture; + +TEST_SUITE(QASYMM8) +FIXTURE_DATA_TEST_CASE(RunSmall, + NEArgMinMaxQuantizedValidationFixture, + framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::Small4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), + framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, + NEArgMinMaxQuantizedValidationFixture, + framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(datasets::Large4DShapes(), framework::dataset::make("DataType", DataType::QASYMM8)), framework::dataset::make("Axis", { 0, 1, 2, 3 })), + framework::dataset::make("Operation", { ReductionOperation::ARG_IDX_MIN, ReductionOperation::ARG_IDX_MAX })), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(5.f / 255.f, 20) }))) +{ + // Validate output + validate(Accessor(_target), _reference); +} +TEST_SUITE_END() // QASYMM8 + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, + NEArgMinMaxValidationFixture, + 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(Accessor(_target), _reference); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, + NEArgMinMaxValidationFixture, + 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(Accessor(_target), _reference); +} +TEST_SUITE_END() // FP32 +TEST_SUITE_END() // Float +TEST_SUITE_END() // ArgMinMax +TEST_SUITE_END() // NEON +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/fixtures/ArgMinMaxFixture.h b/tests/validation/fixtures/ArgMinMaxFixture.h index 5f5f85c104..e263b25bf2 100644 --- a/tests/validation/fixtures/ArgMinMaxFixture.h +++ b/tests/validation/fixtures/ArgMinMaxFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -42,28 +42,38 @@ namespace test namespace validation { template -class ArgMinMaxValidationFixture : public framework::Fixture +class ArgMinMaxValidationBaseFixture : public framework::Fixture { public: template - void setup(TensorShape shape, DataType data_type, int axis, ReductionOperation op) + void setup(TensorShape shape, DataType data_type, int axis, ReductionOperation op, QuantizationInfo q_info) { - _target = compute_target(shape, data_type, axis, op); - _reference = compute_reference(shape, data_type, axis, op); + _target = compute_target(shape, data_type, axis, op, q_info); + _reference = compute_reference(shape, data_type, axis, op, q_info); } protected: template void fill(U &&tensor) { - std::uniform_real_distribution<> distribution(-1.0f, 1.0f); - library->fill(tensor, distribution, 0); + if(!is_data_type_quantized(tensor.data_type())) + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, 0); + } + else + { + std::pair bounds = get_quantized_bounds(tensor.quantization_info(), -1.0f, 1.0f); + std::uniform_int_distribution distribution(bounds.first, bounds.second); + + library->fill(tensor, distribution, 0); + } } - TensorType compute_target(TensorShape &src_shape, DataType data_type, int axis, ReductionOperation op) + TensorType compute_target(TensorShape &src_shape, DataType data_type, int axis, ReductionOperation op, QuantizationInfo q_info) { // Create tensors - TensorType src = create_tensor(src_shape, data_type, 1); + TensorType src = create_tensor(src_shape, data_type, 1, q_info); TensorType dst; // Create and configure function @@ -89,21 +99,43 @@ protected: return dst; } - SimpleTensor compute_reference(TensorShape &src_shape, DataType data_type, int axis, ReductionOperation op) + SimpleTensor compute_reference(TensorShape &src_shape, DataType data_type, int axis, ReductionOperation op, QuantizationInfo q_info) { // Create reference - SimpleTensor src{ src_shape, data_type, 1 }; + SimpleTensor src{ src_shape, data_type, 1, q_info }; // Fill reference fill(src); TensorShape output_shape = src_shape; output_shape.set(axis, 1); - return reference::reduction_operation(src, output_shape, axis, op); + return reference::reduction_operation(src, output_shape, axis, op); } - TensorType _target{}; - SimpleTensor _reference{}; + TensorType _target{}; + SimpleTensor _reference{}; +}; + +template +class ArgMinMaxValidationQuantizedFixture : public ArgMinMaxValidationBaseFixture +{ +public: + template + void setup(const TensorShape &shape, DataType data_type, int axis, ReductionOperation op, QuantizationInfo quantization_info) + { + ArgMinMaxValidationBaseFixture::setup(shape, data_type, axis, op, quantization_info); + } +}; + +template +class ArgMinMaxValidationFixture : public ArgMinMaxValidationBaseFixture +{ +public: + template + void setup(const TensorShape &shape, DataType data_type, int axis, ReductionOperation op) + { + ArgMinMaxValidationBaseFixture::setup(shape, data_type, axis, op, QuantizationInfo()); + } }; } // namespace validation } // namespace test diff --git a/tests/validation/fixtures/ReduceMeanFixture.h b/tests/validation/fixtures/ReduceMeanFixture.h index 769d7f674f..44bb9fca6a 100644 --- a/tests/validation/fixtures/ReduceMeanFixture.h +++ b/tests/validation/fixtures/ReduceMeanFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -113,7 +113,7 @@ protected: { 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); + out = reference::reduction_operation(i == 0 ? src : out, output_shape, axis[i], ReductionOperation::MEAN_SUM); } if(!keep_dims) diff --git a/tests/validation/fixtures/ReductionOperationFixture.h b/tests/validation/fixtures/ReductionOperationFixture.h index 9079b47cbb..d01f41abf0 100644 --- a/tests/validation/fixtures/ReductionOperationFixture.h +++ b/tests/validation/fixtures/ReductionOperationFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -107,7 +107,7 @@ protected: // Fill reference fill(src); - return reference::reduction_operation(src, dst_shape, axis, op); + return reference::reduction_operation(src, dst_shape, axis, op); } TensorType _target{}; diff --git a/tests/validation/reference/L2NormalizeLayer.cpp b/tests/validation/reference/L2NormalizeLayer.cpp index fcd6226f07..43885b29e2 100644 --- a/tests/validation/reference/L2NormalizeLayer.cpp +++ b/tests/validation/reference/L2NormalizeLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -54,7 +54,7 @@ SimpleTensor l2_normalize(const SimpleTensor &src, unsigned int axis, floa SimpleTensor dst{ src.shape(), src.data_type() }; // Reduce across given axis - SimpleTensor sum = reduction_operation(src, get_output_shape(src.shape(), axis), axis, ReductionOperation::SUM_SQUARE); + SimpleTensor sum = reduction_operation(src, get_output_shape(src.shape(), axis), axis, ReductionOperation::SUM_SQUARE); // Compute reference const int upper_dims = src.shape().total_size_upper(axis + 1); diff --git a/tests/validation/reference/ReductionOperation.cpp b/tests/validation/reference/ReductionOperation.cpp index 37a9be86c0..fc12e31d75 100644 --- a/tests/validation/reference/ReductionOperation.cpp +++ b/tests/validation/reference/ReductionOperation.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -49,20 +49,20 @@ OT reduce_operation(const T *ptr, int reduce_elements, ReductionOperation op, in uint32_t int_res = 0; for(int i = 0; i < reduce_elements; ++i) { - auto elem = static_cast(*(ptr + stride * i)); + auto elem = *(ptr + stride * i); switch(op) { case ReductionOperation::ARG_IDX_MIN: - if(static_cast(*(ptr + stride * static_cast(res))) > elem) + if(*(ptr + stride * static_cast(int_res)) > elem) { - res = static_cast(i); + int_res = static_cast(i); } break; case ReductionOperation::ARG_IDX_MAX: - if(static_cast(*(ptr + stride * static_cast(res))) < elem) + if(*(ptr + stride * static_cast(int_res)) < elem) { - res = static_cast(i); + int_res = static_cast(i); } break; case ReductionOperation::SUM_SQUARE: @@ -122,13 +122,13 @@ OT reduce_operation(const T *ptr, int reduce_elements, ReductionOperation op, in } } // namespace -template -SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op) +template +SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op) { // Create reference 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() }; + 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(); @@ -143,14 +143,7 @@ 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; - 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); - } + dst[du] = reduce_operation(src_row_ptr, reduce_elems, op, 1); } } break; @@ -164,15 +157,7 @@ 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; - - 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); - } + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_width); } } } @@ -189,15 +174,7 @@ 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; - - 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); - } + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_height * src_width); } } } @@ -217,14 +194,7 @@ 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; - 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); - } + dst[out_offset] = reduce_operation(src_row_ptr, reduce_elems, op, src_width * src_height * src_depth); } } } @@ -238,6 +208,9 @@ SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShap return dst; } +template SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); +template SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); +template SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); template SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); template SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); template SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); diff --git a/tests/validation/reference/ReductionOperation.h b/tests/validation/reference/ReductionOperation.h index 859b57aa7b..9f7050f551 100644 --- a/tests/validation/reference/ReductionOperation.h +++ b/tests/validation/reference/ReductionOperation.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -35,10 +35,10 @@ namespace validation { namespace reference { -template -SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); +template +SimpleTensor reduction_operation(const SimpleTensor &src, const TensorShape &dst_shape, unsigned int axis, ReductionOperation op); } // namespace reference } // namespace validation } // namespace test } // namespace arm_compute -#endif /* __ARM_COMPUTE_TEST_FLOOR_H__ */ +#endif /* __ARM_COMPUTE_TEST_REDUCTION_OPERATION_H__ */ -- cgit v1.2.1