From d004a7a707feab36e51f51cfc9eb2cb70729d5ad Mon Sep 17 00:00:00 2001 From: SiCong Li Date: Thu, 28 May 2020 15:26:41 +0100 Subject: COMPMID-3510 [Interface change] Fix definition of "axis" in NESoftmaxLayer and CLSoftmaxLayer * [Interface change] "axis" argument is renamed to "reduce_end_axis" * Unify the meaning of "axis"(now "reduce_end_axis") to be the last axis of the first n dimensions (inclusive)to reduce. This way the meaning of reduce_end_axis stays the same for both positive and negative values: it selects a dimension before which all dimensions (including the selected dimension) are reduced. Change-Id: I4ab03bd8360b1cd8cac4998df0b1571064a9d4ed Signed-off-by: SiCong Li Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3278 Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio Reviewed-by: Georgios Pinitas Comments-Addressed: Arm Jenkins --- arm_compute/core/Helpers.h | 13 +++++ arm_compute/runtime/CL/functions/CLSoftmaxLayer.h | 65 ++++++++++++---------- .../GLES_COMPUTE/functions/GCSoftmaxLayer.h | 19 ++++--- .../runtime/NEON/functions/NESoftmaxLayer.h | 58 ++++++++++--------- 4 files changed, 92 insertions(+), 63 deletions(-) (limited to 'arm_compute') diff --git a/arm_compute/core/Helpers.h b/arm_compute/core/Helpers.h index 09c672ecfa..8f1426a56e 100644 --- a/arm_compute/core/Helpers.h +++ b/arm_compute/core/Helpers.h @@ -801,6 +801,19 @@ inline T wrap_around(T x, T m) return x >= 0 ? x % m : (x % m + m) % m; } +/** Convert a dimension axis to the number of dimensions in the range [0, @p dim_axis] + * Handle negative axis, negative axis is used to specify axis from the end (e.g. -1 for the last axis). + * + * @param[in] dim_axis The last axis (inclusive) in the range [0, @p dim_axis] + * @param[in] num_dims The total number of dimensions + * + * @return The number of dimensions in the range [0, @p dim_axis] + */ +inline size_t dim_index_2_num_dims(int32_t dim_axis, int32_t num_dims) +{ + return static_cast(wrap_around(dim_axis, num_dims)) + 1; +} + /** Convert negative coordinates to positive in the range [0, num_dims_input] * * @param[out] coords Array of coordinates to be converted. diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h index fadbc430e6..231a56f712 100644 --- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h +++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h @@ -50,6 +50,10 @@ class ICLTensor; * -# @ref CLLogits1DMaxKernel * -# @ref CLLogits1DShiftExpSumKernel * -# @ref CLLogits1DNormKernel + * And if the reduce_end_axis is not 0, the function will use one of the the following kernels to reshape the input and + * perform softmax on the reshaped input: + * -# @ref CLFlattenLayerKernel + * -# @ref CLReshapeLayerKernel */ template class CLSoftmaxLayerGeneric : public IFunction @@ -59,36 +63,39 @@ public: CLSoftmaxLayerGeneric(std::shared_ptr memory_manager = nullptr); /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32 - * @param[out] output Destination tensor. Data types supported: same as @p input - * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f - * @param[in] axis (Optional) Reduction axis. 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. + * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32 + * @param[out] output Destination tensor. Data types supported: same as @p input + * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f + * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * Must be in range [0, input_num_dimensions). */ - void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t axis = 1); + void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t reduce_end_axis = 0); /** Set the input and output tensors. * * @param[in] compile_context The compile context to be used. * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32 * @param[out] output Destination tensor. Data types supported: same as @p input * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f - * @param[in] axis (Optional) Reduction axis. 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. + * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * Must be in range [0, input_num_dimensions). */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t axis = 1); + void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t reduce_end_axis = 0); /** Static function to check if given info will lead to a valid configuration of @ref CLSoftmaxLayer * - * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32 - * @param[in] output Destination tensor. Data types supported: same as @p input - * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f - * @param[in] axis (Optional) Reduction axis. 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. + * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32 + * @param[in] output Destination tensor. Data types supported: same as @p input + * @param[in] beta (Optional) A scaling factor for the exponent. Defaults to 1.f + * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * Must be in range [0, input_num_dimensions). * @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, size_t reduce_end_axis = 0); // Inherited methods overridden: void run() override; @@ -101,13 +108,14 @@ private: * it initializes the kernel @p _flatten_kernel and the tensors @p _input_flat and * @p _output_flat * - * @param[in] input Original source tensor. - * @param[in] output Original destination tensor. - * @param[in] axis (Optional) Reduction axis. 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. + * @param[in] input Original source tensor. + * @param[in] output Original destination tensor. + * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * Must be in range [0, input_num_dimensions). */ - void configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t axis); + void configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t reduce_end_axis); /** Utility method to configure the kernels needed to flatten the input * tensor. * @@ -118,11 +126,12 @@ private: * @param[in] compile_context The compile context to be used. * @param[in] input Original source tensor. * @param[in] output Original destination tensor. - * @param[in] axis (Optional) Reduction axis. 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. + * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * Must be in range [0, input_num_dimensions). */ - void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t axis); + void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t reduce_end_axis); MemoryGroup _memory_group; CLLogits1DMaxShiftExpSumKernel _max_shift_exp_sum_kernel; diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h index 33faae5e06..e29322c052 100644 --- a/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h +++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -50,16 +50,17 @@ public: GCSoftmaxLayer(std::shared_ptr memory_manager = nullptr); /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: F16/F32 - * @param[out] output Destination tensor. Data types supported: same as @p input - * @param[in] beta (Optional) A scaling factor for the exponent. Only beta = 1 is supported - * @param[in] axis (Optional) Reduction axis. 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. + * @param[in] input Source tensor. Data types supported: F16/F32 + * @param[out] output Destination tensor. Data types supported: same as @p input + * @param[in] beta (Optional) A scaling factor for the exponent. Only beta = 1 is supported + * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * Must be in range [0, input_num_dimensions). * - * @note The value of @p axis must be always 1 for GLES + * @note The value of @p reduce_end_axis must be always 0 for GLES */ - void configure(const IGCTensor *input, IGCTensor *output, float beta = 1.0f, size_t axis = 1); + void configure(const IGCTensor *input, IGCTensor *output, float beta = 1.0f, size_t reduce_end_axis = 0); // Inherited methods overridden: void run() override; diff --git a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h index b80ceaf25c..c5c83d8b5a 100644 --- a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h +++ b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h @@ -48,6 +48,10 @@ class ITensor; * -# @ref NEFillBorderKernel * -# @ref NELogits1DMaxKernel * -# @ref NELogits1DSoftmaxKernel + * And if the reduce_end_axis is not 0 or -input_num_dimensions, the function will use one of the the following kernels + * to reshape the input and perform softmax on the reshaped input: + * -# @ref NEFlattenLayerKernel + * -# @ref NEReshapeLayerKernel */ template class NESoftmaxLayerGeneric : public IFunction @@ -65,30 +69,31 @@ public: NESoftmaxLayerGeneric &operator=(NESoftmaxLayerGeneric &&) = default; /** Set the input and output tensors. * - * @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. - * 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. + * @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] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * 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). */ - void configure(ITensor *input, ITensor *output, float beta = 1.0f, int32_t axis = -1); + void configure(ITensor *input, ITensor *output, float beta = 1.0f, int32_t reduce_end_axis = 0); /** 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/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. - * 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. - * + * @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] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * 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). * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t axis = -1); + static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, int32_t reduce_end_axis = 0); // Inherited methods overridden: void run() override; @@ -101,14 +106,15 @@ private: * it initializes the kernel @p _flatten_kernel and the tensors @p _input_flat and * @p _output_flat * - * @param[in] input Original source tensor. - * @param[in] output Original destination tensor. - * @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. + * @param[in] input Original source tensor. + * @param[in] output Original destination tensor. + * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0. + * It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image, + * when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image. + * 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). */ - void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, int32_t axis); + void configure_reshape_input_kernel(const ITensor *input, const ITensor *output, int32_t reduce_end_axis); MemoryGroup _memory_group; NELogits1DMaxKernel _max_kernel; -- cgit v1.2.1