From 81e671ef4f2a8fb3128fba402610b9de28b57891 Mon Sep 17 00:00:00 2001 From: Usama Arif Date: Mon, 13 May 2019 13:33:14 +0100 Subject: COMPMID-2269: Implement POW operator for NEON Change-Id: I7135f665d89da3c24c9bbe00e991a64713a41d0e Signed-off-by: Usama Arif Reviewed-on: https://review.mlplatform.org/c/1128 Reviewed-by: Michalis Spyrou Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins --- .../NEON/kernels/NEElementwiseOperationKernel.h | 29 ++++ arm_compute/core/Types.h | 1 + .../NEON/functions/NEElementwiseOperations.h | 27 ++++ .../NEON/kernels/NEElementwiseOperationKernel.cpp | 38 +++++ .../NEON/functions/NEElementwiseOperators.cpp | 12 ++ tests/validation/NEON/ElementwisePower.cpp | 155 +++++++++++++++++++++ .../fixtures/ElementwiseOperationsFixture.h | 38 ++++- .../validation/reference/ElementwiseOperations.cpp | 71 ++++++---- 8 files changed, 341 insertions(+), 30 deletions(-) create mode 100644 tests/validation/NEON/ElementwisePower.cpp diff --git a/arm_compute/core/NEON/kernels/NEElementwiseOperationKernel.h b/arm_compute/core/NEON/kernels/NEElementwiseOperationKernel.h index 351b346c5a..195fd8951d 100644 --- a/arm_compute/core/NEON/kernels/NEElementwiseOperationKernel.h +++ b/arm_compute/core/NEON/kernels/NEElementwiseOperationKernel.h @@ -151,6 +151,35 @@ protected: static Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output); }; +class NEPowerOperationKernel : public NEArithmeticOperationKernel +{ +public: + /** Default constructor */ + NEPowerOperationKernel() = default; + + /** Static function to check if given info will lead to a valid configuration of @ref NEArithmeticOperationKernel + * + * @param[in] input1 First tensor input. Data types supported: F16/F32. + * @param[in] input2 Second tensor input. Data types supported: Same as @p input1. + * @param[out] output Output tensor. Data types supported: Same as @p input1. + */ + void configure(const ITensor *input1, const ITensor *input2, ITensor *output); + + /** Static function to check if given info will lead to a valid configuration of @ref NEArithmeticOperationKernel + * + * @param[in] input1 First tensor input info. Data types supported: F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: Same as @p input1. + * @param[out] output Output tensor info. Data types supported: Same as @p input1. + * + * @return a Status + */ + static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output); + +protected: + // Inherited methods overridden: + static Status validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output); +}; + class NEComparisonOperationKernel : public NEElementwiseOperationKernel { public: diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h index 9ecd7ff2e1..99ec44d5e0 100644 --- a/arm_compute/core/Types.h +++ b/arm_compute/core/Types.h @@ -571,6 +571,7 @@ enum class ArithmeticOperation MIN, /**< Min(x, y) */ MAX, /**< Max(x, y) */ SQUARED_DIFF, /**< (x - y)^2 */ + POWER, /**< x ^ y */ }; /** Available element wise unary operations */ diff --git a/arm_compute/runtime/NEON/functions/NEElementwiseOperations.h b/arm_compute/runtime/NEON/functions/NEElementwiseOperations.h index ca3717a709..586546c8bc 100644 --- a/arm_compute/runtime/NEON/functions/NEElementwiseOperations.h +++ b/arm_compute/runtime/NEON/functions/NEElementwiseOperations.h @@ -135,6 +135,33 @@ public: static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output); }; +/** Basic function to run @ref NEArithmeticOperationKernel for power + * + * @note The tensor data type for the inputs must be F16/F32. + * @note The function performs a elementwise power of in1 to in2 (i.e., out[i] = in1[i] ^ in2[i]) + * @note For an exponent that is a float, this function will only work with a positive base. + */ +class NEElementwisePower : public INESimpleFunction +{ +public: + /** Initialise the kernel's inputs, output and conversion policy. + * + * @param[in, out] input1 First tensor input. Data types supported: F16/F32. + * @param[in, out] input2 Second tensor input. Data types supported: Same as @p input1. + * @param[out] output Output tensor. Data types supported: Same as @p input1. + */ + void configure(ITensor *input1, ITensor *input2, ITensor *output); + /** Static function to check if given info will lead to a valid configuration of @ref NEArithmeticOperationKernel for power + * + * @param[in] input1 First tensor input info. Data types supported: F16/F32. + * @param[in] input2 Second tensor input info. Data types supported: Same as @p input1. + * @param[in] output Output tensor info. Data types supported: Same as @p input1. + * + * @return a status + */ + static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output); +}; + /** Basic function to run @ref NEComparisonOperationKernel. * * @note The tensor data type for the inputs must be QASYMM8/S16/F16/S32/F32. diff --git a/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp b/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp index 6b87ea017b..33457e1fca 100644 --- a/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp +++ b/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp @@ -130,6 +130,11 @@ inline ScalarType elementwise_arithm_op_scalar(const ScalarType &a, const Scalar res = a / b; break; } + case ArithmeticOperation::POWER: + { + res = std::pow(a, b); + break; + } default: ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); } @@ -174,12 +179,24 @@ inline float32x4_t elementwise_arithm_op( return wrapper::vdiv(a, b); } +template <> +inline float32x4_t elementwise_arithm_op(const float32x4_t &a, const float32x4_t &b) +{ + return wrapper::vpow(a, b); +} + #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC template <> inline float16x8_t elementwise_arithm_op(const float16x8_t &a, const float16x8_t &b) { return wrapper::vdiv(a, b); } + +template <> +inline float16x8_t elementwise_arithm_op(const float16x8_t &a, const float16x8_t &b) +{ + return wrapper::vpow(a, b); +} #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC template @@ -879,6 +896,27 @@ Status NEDivisionOperationKernel::validate(const ITensorInfo *input1, const ITen return Status{}; } +/** The power operator */ +void NEPowerOperationKernel::configure(const ITensor *input1, const ITensor *input2, ITensor *output) +{ + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*input1->info(), *input2->info(), *output->info())); + configure_common(input1, input2, output); + _function = configure_arithm_func(input1, input2, output); +} + +Status NEPowerOperationKernel::validate_arguments(const ITensorInfo &input1, const ITensorInfo &input2, const ITensorInfo &output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&input1, 1, DataType::F16, DataType::F32); + return NEArithmeticOperationKernel::validate_arguments(input1, input2, output); +} + +Status NEPowerOperationKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*input1, *input2, *output)); + return Status{}; +} + /** Comparison operators (equal, not equal, less than, greater than, less than or equal, greater than or equal) */ void NEComparisonOperationKernel::configure(ComparisonOperation op, const ITensor *input1, const ITensor *input2, ITensor *output) diff --git a/src/runtime/NEON/functions/NEElementwiseOperators.cpp b/src/runtime/NEON/functions/NEElementwiseOperators.cpp index 74c195764b..699363111d 100644 --- a/src/runtime/NEON/functions/NEElementwiseOperators.cpp +++ b/src/runtime/NEON/functions/NEElementwiseOperators.cpp @@ -79,6 +79,18 @@ Status NEElementwiseDivision::validate(const ITensorInfo *input1, const ITensorI return NEDivisionOperationKernel::validate(input1, input2, output); } +void NEElementwisePower::configure(ITensor *input1, ITensor *input2, ITensor *output) +{ + auto k = arm_compute::support::cpp14::make_unique(); + k->configure(input1, input2, output); + _kernel = std::move(k); +} + +Status NEElementwisePower::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output) +{ + return NEPowerOperationKernel::validate(input1, input2, output); +} + template void NEElementwiseComparisonStatic::configure(ITensor *input1, ITensor *input2, ITensor *output) { diff --git a/tests/validation/NEON/ElementwisePower.cpp b/tests/validation/NEON/ElementwisePower.cpp new file mode 100644 index 0000000000..3ca39e840a --- /dev/null +++ b/tests/validation/NEON/ElementwisePower.cpp @@ -0,0 +1,155 @@ +/* + * Copyright (c) 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/NEElementwiseOperations.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" +#include "tests/NEON/Accessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/ElementwiseOperationsFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +RelativeTolerance tolerance_fp32(0.001f); +/** Input data sets **/ +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +RelativeTolerance tolerance_fp16(static_cast(0.01f)); +const auto ElementwisePowerFP16Dataset = combine(combine(framework::dataset::make("DataType", DataType::F16), framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("DataType", DataType::F16)); +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ +const auto ElementwisePowerFP32Dataset = combine(combine(framework::dataset::make("DataType", DataType::F32), framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("DataType", DataType::F32)); +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(ElementwisePower) + +template +using NEElementwisePowerFixture = ElementwisePowerValidationFixture; + +// *INDENT-OFF* +// clang-format off +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("Input1Info", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Invalid data type combination + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), // Mismatching shapes + }), + framework::dataset::make("Input2Info",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::S32), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32), + TensorInfo(TensorShape(48U, 11U, 2U), 1, DataType::F32), + })), + framework::dataset::make("Expected", { true, true, true, false, false})), + input1_info, input2_info, output_info, expected) +{ + ARM_COMPUTE_EXPECT(bool(NEElementwisePower::validate(&input1_info.clone()->set_is_resizable(false), &input2_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false))) == expected, framework::LogLevel::ERRORS); +} +// clang-format on +// *INDENT-ON* + +TEST_SUITE(Float) +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(F16) +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwisePowerFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwisePowerFP16Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp16, 0.01); +} +TEST_SUITE_END() // F16 +#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ + +TEST_SUITE(F32) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), + shape) +{ + // Create tensors + Tensor ref_src1 = create_tensor(shape, DataType::F32); + Tensor ref_src2 = create_tensor(shape, DataType::F32); + Tensor dst = create_tensor(shape, DataType::F32); + + // Create and Configure function + NEElementwisePower power; + power.configure(&ref_src1, &ref_src2, &dst); + + // Validate valid region + const ValidRegion valid_region = shape_to_valid_region(shape); + validate(dst.info()->valid_region(), valid_region); +} + +FIXTURE_DATA_TEST_CASE(RunSmall, NEElementwisePowerFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), ElementwisePowerFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32, 0.01); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, NEElementwisePowerFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), ElementwisePowerFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32, 0.01); +} + +template +using NEElementwisePowerBroadcastFixture = ElementwisePowerBroadcastValidationFixture; + +FIXTURE_DATA_TEST_CASE(RunSmallBroadcast, NEElementwisePowerBroadcastFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapesBroadcast(), + ElementwisePowerFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32, 0.01); +} + +FIXTURE_DATA_TEST_CASE(RunLargeBroadcast, NEElementwisePowerBroadcastFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapesBroadcast(), + ElementwisePowerFP32Dataset)) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32, 0.01); +} +TEST_SUITE_END() // F32 +TEST_SUITE_END() // Float + +TEST_SUITE_END() // ElementwisePower +TEST_SUITE_END() // NEON +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation/fixtures/ElementwiseOperationsFixture.h b/tests/validation/fixtures/ElementwiseOperationsFixture.h index 53030842e7..e86e7a0f20 100644 --- a/tests/validation/fixtures/ElementwiseOperationsFixture.h +++ b/tests/validation/fixtures/ElementwiseOperationsFixture.h @@ -58,7 +58,17 @@ protected: template void fill(U &&tensor, int i) { - (_op == ArithmeticOperation::DIV) ? library->fill_tensor_uniform_ranged(tensor, i, { std::pair(-0.001f, 0.001f) }) : library->fill_tensor_uniform(tensor, i); + switch(_op) + { + case ArithmeticOperation::DIV: + library->fill_tensor_uniform_ranged(tensor, i, { std::pair(-0.001f, 0.001f) }); + break; + case ArithmeticOperation::POWER: + library->fill_tensor_uniform(tensor, i, 0.0f, 5.0f); + break; + default: + library->fill_tensor_uniform(tensor, i); + } } TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type, @@ -382,6 +392,32 @@ public: } }; +template +class ElementwisePowerBroadcastValidationFixture : public ArithmeticOperationsGenericFixture +{ +public: + template + void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture::setup(ArithmeticOperation::POWER, shape0, shape1, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + +template +class ElementwisePowerValidationFixture : public ArithmeticOperationsGenericFixture +{ +public: + template + void setup(const TensorShape &shape, DataType data_type0, DataType data_type1, DataType output_data_type) + { + ArithmeticOperationsGenericFixture::setup(ArithmeticOperation::POWER, shape, shape, + data_type0, data_type1, output_data_type, + QuantizationInfo(), QuantizationInfo(), QuantizationInfo()); + } +}; + } // namespace validation } // namespace test } // namespace arm_compute diff --git a/tests/validation/reference/ElementwiseOperations.cpp b/tests/validation/reference/ElementwiseOperations.cpp index 2ffb0faa75..82f42a0c21 100644 --- a/tests/validation/reference/ElementwiseOperations.cpp +++ b/tests/validation/reference/ElementwiseOperations.cpp @@ -43,38 +43,51 @@ T arithm_op(ArithmeticOperation op, T src1, T src2, ConvertPolicy convert_policy intermediate_type val; - if(op == ArithmeticOperation::ADD) + switch(op) { - val = static_cast(src1) + static_cast(src2); - } - else if(op == ArithmeticOperation::SUB) - { - val = static_cast(src1) - static_cast(src2); - } - else if(op == ArithmeticOperation::MIN) - { - val = std::min(static_cast(src1), static_cast(src2)); - } - else if(op == ArithmeticOperation::MAX) - { - val = std::max(static_cast(src1), static_cast(src2)); - } - else if(op == ArithmeticOperation::SQUARED_DIFF) - { - intermediate_type tmp = (static_cast(src1) - static_cast(src2)); - val = tmp * tmp; - } - else if(op == ArithmeticOperation::DIV) - { - val = (static_cast(src1) / static_cast(src2)); - } - else - { - ARM_COMPUTE_ERROR("Not handled"); + case ArithmeticOperation::ADD: + { + val = static_cast(src1) + static_cast(src2); + break; + } + case ArithmeticOperation::SUB: + { + val = static_cast(src1) - static_cast(src2); + break; + } + case ArithmeticOperation::MIN: + { + val = std::min(static_cast(src1), static_cast(src2)); + break; + } + case ArithmeticOperation::MAX: + { + val = std::max(static_cast(src1), static_cast(src2)); + break; + } + case ArithmeticOperation::SQUARED_DIFF: + { + intermediate_type tmp = (static_cast(src1) - static_cast(src2)); + val = tmp * tmp; + break; + } + case ArithmeticOperation::DIV: + { + val = (static_cast(src1) / static_cast(src2)); + break; + } + case ArithmeticOperation::POWER: + { + val = std::pow(static_cast(src1), static_cast(src2)); + break; + } + default: + { + ARM_COMPUTE_ERROR("Not handled"); + } } - T result; - if(op == ArithmeticOperation::ADD || op == ArithmeticOperation::SUB || op == ArithmeticOperation::DIV) + if(op == ArithmeticOperation::ADD || op == ArithmeticOperation::SUB || op == ArithmeticOperation::DIV || op == ArithmeticOperation::POWER) { result = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast(val) : static_cast(val); 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