diff options
| -rw-r--r-- | arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h | 10 | ||||
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NESoftmaxLayer.h | 21 | ||||
| -rw-r--r-- | src/runtime/NEON/functions/NESoftmaxLayer.cpp | 16 | ||||
| -rw-r--r-- | tests/validation/NEON/SoftmaxLayer.cpp | 10 | ||||
| -rw-r--r-- | tests/validation/fixtures/SoftmaxLayerFixture.h | 6 | ||||
| -rw-r--r-- | tests/validation/reference/LogSoftmaxLayer.cpp | 16 | ||||
| -rw-r--r-- | tests/validation/reference/LogSoftmaxLayer.h | 8 | ||||
| -rw-r--r-- | tests/validation/reference/SoftmaxLayer.cpp | 28 | ||||
| -rw-r--r-- | tests/validation/reference/SoftmaxLayer.h | 10 |
9 files changed, 70 insertions, 55 deletions
diff --git a/arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h b/arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h index dfcc2ffe2..0e0be7936 100644 --- a/arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h +++ b/arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -43,13 +43,13 @@ public: NELogits1DMaxKernel(); /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32. + * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[out] output Destination tensor. Data types supported: same as @p input */ void configure(const ITensor *input, ITensor *output); /** Static function to check if given info will lead to a valid configuration of @ref NELogits1DMaxKernel * - * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32. + * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] output Destination tensor. Data types supported: same as @p input * * @return a status @@ -98,7 +98,7 @@ public: ~NELogits1DSoftmaxKernel() = default; /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32. + * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] max Max values tensor. Same shape as input with dimension 0 set to 1. * Data types supported: same as @p input. * @param[out] output Destination tensor. Data types supported: same as @p input. @@ -109,7 +109,7 @@ public: void configure(const ITensor *input, const ITensor *max, ITensor *output, const float beta, ITensor *tmp); /** Static function to check if given info will lead to a valid configuration of @ref NELogits1DSoftmaxKernel * - * @param[in] input Source tensor info. Data types supported: QASYMM8/F16/F32. + * @param[in] input Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] max Max values tensor info. Same shape as input with dimension 0 set to 1. * Data types supported: same as @p input. * @param[in] output Destination tensor info. Data types supported: same as @p input. diff --git a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h index f89add71e..b80ceaf25 100644 --- a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h +++ b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -65,28 +65,30 @@ public: NESoftmaxLayerGeneric &operator=(NESoftmaxLayerGeneric &&) = default; /** Set the input and output tensors. * - * @param[in,out] input Source tensor. Data types supported: QASYMM8/F16/F32. If the width is not a + * @param[in,out] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. If the width is not a * multiple of the internal processing block size, @ref NEFillBorderKernel replicates the * last value of each row to the nearest multiple. * @param[out] output Destination tensor. Data types supported: same as @p input. * @param[in] beta (Optional) A scaling factor for the exponent. - * @param[in] axis (Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). + * @param[in] axis (Optional) Reduction axis. Defaults to -1. + * Negative index is used to specify axis from the end (e.g. -1 for the last axis).Must be in range [-input_num_dimensions, input_num_dimensions). * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image, * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image. */ - void configure(ITensor *input, ITensor *output, float beta = 1.0f, size_t axis = 1); + void configure(ITensor *input, ITensor *output, float beta = 1.0f, int32_t axis = -1); /** Static function to check if given info will lead to a valid configuration of @ref NESoftmaxLayer * - * @param[in] input Source tensor info. Data types supported: QASYMM8/F16/F32. + * @param[in] input Source tensor info. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] output Destination tensor info. Data types supported: same as @p input * @param[in] beta (Optional) A scaling factor for the exponent. - * @param[in] axis (Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). + * @param[in] axis (Optional) Reduction axis. Defaults to -1. + * Negative index is used to specify axis from the end (e.g. -1 for the last axis).Must be in range [-input_num_dimensions, input_num_dimensions). * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image, * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image. * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, size_t axis = 1); + static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t axis = -1); // Inherited methods overridden: void run() override; @@ -101,11 +103,12 @@ private: * * @param[in] input Original source tensor. * @param[in] output Original destination tensor. - * @param[in] axis (Optional) Reduction axis. Defaults to 1. Must be in range [1, input_num_dimensions). + * @param[in] axis (Optional) Reduction axis. Defaults to -1. + * Negative index is used to specify axis from the end (e.g. -1 for the last axis).Must be in range [-input_num_dimensions, input_num_dimensions). * It has the purpose of squashing the first @p axis dimensions together. For instance, given a [4x4x4x4] image, * when @p axis is 2, the Softmax reduction will be applied on each of the [4x4] planes of the input image. */ - void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, size_t axis); + void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, int32_t axis); MemoryGroup _memory_group; NELogits1DMaxKernel _max_kernel; diff --git a/src/runtime/NEON/functions/NESoftmaxLayer.cpp b/src/runtime/NEON/functions/NESoftmaxLayer.cpp index f530a87d0..57d75af77 100644 --- a/src/runtime/NEON/functions/NESoftmaxLayer.cpp +++ b/src/runtime/NEON/functions/NESoftmaxLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -41,7 +41,7 @@ NESoftmaxLayerGeneric<IS_LOG>::NESoftmaxLayerGeneric(std::shared_ptr<IMemoryMana } template <bool IS_LOG> -void NESoftmaxLayerGeneric<IS_LOG>::configure_reshape_input_kernel(const ITensor *input, const ITensor *output, size_t axis) +void NESoftmaxLayerGeneric<IS_LOG>::configure_reshape_input_kernel(const ITensor *input, const ITensor *output, int32_t axis) { // Flatten the input const TensorShape shape_flatten = misc::shape_calculator::compute_softmax_shape(input->info(), axis); @@ -71,12 +71,15 @@ void NESoftmaxLayerGeneric<IS_LOG>::configure_reshape_input_kernel(const ITensor } template <bool IS_LOG> -void NESoftmaxLayerGeneric<IS_LOG>::configure(ITensor *input, ITensor *output, float beta, size_t axis) +void NESoftmaxLayerGeneric<IS_LOG>::configure(ITensor *input, ITensor *output, float beta, int32_t axis) { // Perform validation step ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_THROW_ON(NESoftmaxLayerGeneric::validate(input->info(), output->info(), beta, axis)); + // Handle negative axis, negative index is used to specify axis from the end (e.g. -1 for the last axis). + axis = wrap_around(axis, static_cast<int32_t>(input->info()->num_dimensions())); + // We don't need flattening only in the case the input is 2D and axis is 1 _needs_flattening = axis != 1; @@ -142,13 +145,16 @@ void NESoftmaxLayerGeneric<IS_LOG>::configure(ITensor *input, ITensor *output, f } template <bool IS_LOG> -Status NESoftmaxLayerGeneric<IS_LOG>::validate(const ITensorInfo *input, const ITensorInfo *output, float beta, size_t axis) +Status NESoftmaxLayerGeneric<IS_LOG>::validate(const ITensorInfo *input, const ITensorInfo *output, float beta, int32_t axis) { // Perform validation step ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 4, "Only up to 4 dimensions are supported"); ARM_COMPUTE_UNUSED(beta); - ARM_COMPUTE_RETURN_ERROR_ON(axis < 1 || input->num_dimensions() < axis); + ARM_COMPUTE_RETURN_ERROR_ON(axis < static_cast<int32_t>(-input->num_dimensions()) || static_cast<int32_t>(input->num_dimensions()) <= axis); + + // Handle negative axis, negative index is used to specify axis from the end (e.g. -1 for the last axis). + axis = wrap_around(axis, static_cast<int32_t>(input->num_dimensions())); // Create intermediate tensor info DataType tmp_data_type = input->data_type(); diff --git a/tests/validation/NEON/SoftmaxLayer.cpp b/tests/validation/NEON/SoftmaxLayer.cpp index c429782e6..8af3847cf 100644 --- a/tests/validation/NEON/SoftmaxLayer.cpp +++ b/tests/validation/NEON/SoftmaxLayer.cpp @@ -97,9 +97,9 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( framework::dataset::make("axis", { 1, 1, 1, + -1, 1, - 1, - 0, + -3, })), framework::dataset::make("Expected", { false, false, false, true, true, false })), input_info, output_info, beta, axis, expected) @@ -188,7 +188,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerQuantizedFixture<uint8_t>, fram framework::dataset::make("DataType", DataType::QASYMM8)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.f }))), - framework::dataset::make("Axis", { 1, 2, 3 }))) + framework::dataset::make("Axis", { -1, 2, 3 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); @@ -209,7 +209,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall2D, NESoftmaxLayerQuantizedFixture<int8_t>, frame framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.f }))), - framework::dataset::make("Axis", { 1 }))) + framework::dataset::make("Axis", { -1, 1 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8_signed); @@ -218,7 +218,7 @@ FIXTURE_DATA_TEST_CASE(RunSmall4D, NESoftmaxLayerQuantizedFixture<int8_t>, frame framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), combine(framework::dataset::make("QuantizationInfo", { QuantizationInfo(0.5f, -10) }), framework::dataset::make("Beta", { 1.0f, 2.f }))), - framework::dataset::make("Axis", { 1, 2, 3 }))) + framework::dataset::make("Axis", { -2, 2, 3 }))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8_signed); diff --git a/tests/validation/fixtures/SoftmaxLayerFixture.h b/tests/validation/fixtures/SoftmaxLayerFixture.h index 82daf34f1..aeff77777 100644 --- a/tests/validation/fixtures/SoftmaxLayerFixture.h +++ b/tests/validation/fixtures/SoftmaxLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -73,7 +73,7 @@ protected: } TensorType compute_target(const TensorShape &shape, DataType data_type, - QuantizationInfo quantization_info, float beta, size_t axis) + QuantizationInfo quantization_info, float beta, int32_t axis) { // Create tensors TensorType src = create_tensor<TensorType>(shape, data_type, 1, quantization_info); @@ -103,7 +103,7 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, - QuantizationInfo quantization_info, float beta, size_t axis) + QuantizationInfo quantization_info, float beta, int32_t axis) { // Create reference SimpleTensor<T> src{ shape, data_type, 1, quantization_info }; diff --git a/tests/validation/reference/LogSoftmaxLayer.cpp b/tests/validation/reference/LogSoftmaxLayer.cpp index e4403956a..edb208e6a 100644 --- a/tests/validation/reference/LogSoftmaxLayer.cpp +++ b/tests/validation/reference/LogSoftmaxLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 ARM Limited. + * Copyright (c) 2019-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -35,13 +35,13 @@ namespace validation namespace reference { template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type> -SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis) +SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis) { return softmax_layer_generic<T>(src, beta, axis, true); } -template <typename T, typename std::enable_if<std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int>::type> -SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis) +template < typename T, typename std::enable_if < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int >::type > +SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis) { const QuantizationInfo output_quantization_info = arm_compute::get_softmax_output_quantization_info(src.data_type(), true); @@ -51,10 +51,10 @@ SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, size_t return dst; } -template SimpleTensor<float> log_softmax_layer(const SimpleTensor<float> &src, float beta, size_t axis); -template SimpleTensor<half> log_softmax_layer(const SimpleTensor<half> &src, float beta, size_t axis); -template SimpleTensor<uint8_t> log_softmax_layer(const SimpleTensor<uint8_t> &src, float beta, size_t axis); -template SimpleTensor<int8_t> log_softmax_layer(const SimpleTensor<int8_t> &src, float beta, size_t axis); +template SimpleTensor<float> log_softmax_layer(const SimpleTensor<float> &src, float beta, int32_t axis); +template SimpleTensor<half> log_softmax_layer(const SimpleTensor<half> &src, float beta, int32_t axis); +template SimpleTensor<uint8_t> log_softmax_layer(const SimpleTensor<uint8_t> &src, float beta, int32_t axis); +template SimpleTensor<int8_t> log_softmax_layer(const SimpleTensor<int8_t> &src, float beta, int32_t axis); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/LogSoftmaxLayer.h b/tests/validation/reference/LogSoftmaxLayer.h index c2e3f5974..48ffdcfbc 100644 --- a/tests/validation/reference/LogSoftmaxLayer.h +++ b/tests/validation/reference/LogSoftmaxLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 ARM Limited. + * Copyright (c) 2019-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -36,10 +36,10 @@ namespace validation namespace reference { template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type = 0> -SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis = 1); +SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis = -1); -template <typename T, typename std::enable_if<std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int>::type = 0> -SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis = 1); +template < typename T, typename std::enable_if < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int >::type = 0 > +SimpleTensor<T> log_softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis = -1); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/SoftmaxLayer.cpp b/tests/validation/reference/SoftmaxLayer.cpp index ee7a5f175..2fe1faef5 100644 --- a/tests/validation/reference/SoftmaxLayer.cpp +++ b/tests/validation/reference/SoftmaxLayer.cpp @@ -34,23 +34,29 @@ namespace validation namespace reference { template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type> -SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, size_t axis, bool is_log) +SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log) { // Create reference SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 }; + // Negative index is used to specify axis from the end (e.g. -1 for the last axis). + if(axis < 0) + { + axis += src.shape().num_dimensions(); + } + // Compute reference. Lower dims are the collapsing of the first axis // dimensions (i.e., the flattened dimension of each batch). The upper dims are // instead the batches we want to normalize int lower_dims = 1; - for(size_t i = 0; i < axis; i++) + for(size_t i = 0; i < static_cast<size_t>(axis); ++i) { lower_dims *= src.shape()[i]; } int upper_dims = 1; - for(size_t i = axis; i < TensorShape::num_max_dimensions; i++) + for(size_t i = static_cast<size_t>(axis); i < TensorShape::num_max_dimensions; ++i) { upper_dims *= src.shape()[i]; } @@ -101,17 +107,17 @@ SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, si return dst; } -template SimpleTensor<float> softmax_layer_generic(const SimpleTensor<float> &src, float beta, size_t axis, bool is_log); -template SimpleTensor<half> softmax_layer_generic(const SimpleTensor<half> &src, float beta, size_t axis, bool is_log); +template SimpleTensor<float> softmax_layer_generic(const SimpleTensor<float> &src, float beta, int32_t axis, bool is_log); +template SimpleTensor<half> softmax_layer_generic(const SimpleTensor<half> &src, float beta, int32_t axis, bool is_log); template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type> -SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis) +SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis) { return softmax_layer_generic<T>(src, beta, axis, false); } template < typename T, typename std::enable_if < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int >::type > -SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis) +SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis) { const QuantizationInfo output_quantization_info = arm_compute::get_softmax_output_quantization_info(src.data_type(), false); @@ -121,10 +127,10 @@ SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, size_t axi return dst; } -template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src, float beta, size_t axis); -template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src, float beta, size_t axis); -template SimpleTensor<uint8_t> softmax_layer(const SimpleTensor<uint8_t> &src, float beta, size_t axis); -template SimpleTensor<int8_t> softmax_layer(const SimpleTensor<int8_t> &src, float beta, size_t axis); +template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src, float beta, int32_t axis); +template SimpleTensor<half> softmax_layer(const SimpleTensor<half> &src, float beta, int32_t axis); +template SimpleTensor<uint8_t> softmax_layer(const SimpleTensor<uint8_t> &src, float beta, int32_t axis); +template SimpleTensor<int8_t> softmax_layer(const SimpleTensor<int8_t> &src, float beta, int32_t axis); } // namespace reference } // namespace validation } // namespace test diff --git a/tests/validation/reference/SoftmaxLayer.h b/tests/validation/reference/SoftmaxLayer.h index 2be575c2a..f819853d9 100644 --- a/tests/validation/reference/SoftmaxLayer.h +++ b/tests/validation/reference/SoftmaxLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -36,13 +36,13 @@ namespace validation namespace reference { template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type = 0> -SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, size_t axis, bool is_log = false); +SimpleTensor<T> softmax_layer_generic(const SimpleTensor<T> &src, float beta, int32_t axis, bool is_log = false); template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type = 0> -SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis = 1); +SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis = -1); -template <typename T, typename std::enable_if<std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int>::type = 0> -SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, size_t axis = 1); +template < typename T, typename std::enable_if < std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value, int >::type = 0 > +SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src, float beta, int32_t axis = -1); } // namespace reference } // namespace validation } // namespace test |