diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLSoftmaxLayer.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLSoftmaxLayer.h | 109 |
1 files changed, 39 insertions, 70 deletions
diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h index fadbc430e6..68541e35c5 100644 --- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h +++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2017-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -21,13 +21,9 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#ifndef ARM_COMPUTE_CLSOFTMAXLAYER_H -#define ARM_COMPUTE_CLSOFTMAXLAYER_H +#ifndef ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLSOFTMAXLAYER_H +#define ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLSOFTMAXLAYER_H -#include "arm_compute/core/CL/kernels/CLFlattenLayerKernel.h" -#include "arm_compute/core/CL/kernels/CLReshapeLayerKernel.h" -#include "arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h" -#include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/IMemoryManager.h" #include "arm_compute/runtime/MemoryGroup.h" @@ -37,6 +33,8 @@ namespace arm_compute { class ICLTensor; +class ITensorInfo; +class CLCompileContext; /** Basic function to compute a SoftmaxLayer. * @@ -44,12 +42,7 @@ class ICLTensor; * @f[ out = exp((x - max(x)) * beta) / sum(exp((x - max(x)) * beta)) @f] * * Log Softmax is calculated by : - * @f[ out = (x - max(x) * beta) - \sum{e^{x - max(x) * beta}} @f] - * - * This function runs the following kernels: - * -# @ref CLLogits1DMaxKernel - * -# @ref CLLogits1DShiftExpSumKernel - * -# @ref CLLogits1DNormKernel + * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f] */ template <bool IS_LOG = false> class CLSoftmaxLayerGeneric : public IFunction @@ -57,87 +50,63 @@ class CLSoftmaxLayerGeneric : public IFunction public: /** Constructor */ CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr); + /** Default destructor */ + ~CLSoftmaxLayerGeneric(); /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32 + * Valid data layouts: + * - All + * + * Valid data type configurations: + * |src |dst | + * |:--------------|:--------------| + * |QASYMM8 |QASYMM8 | + * |QASYMM8_SIGNED |QASYMM8_SIGNED | + * |F16 |F16 | + * |F32 |F32 | + * + * @param[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax * @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] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and + * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0 */ - 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, int32_t 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[in] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax * @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] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and + * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0 */ - 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, + int32_t 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] input Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax * @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] axis (Optional) The dimension in which to apply the function. E.g. for input of shape 4x5x6 and + * axis=1, softmax will be applied to 4x6=24 vectors of size 5. Defaults to 0 + * * @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 = 0); // Inherited methods overridden: void run() override; private: - /** Utility method to configure the kernels needed to flatten the input - * tensor. - * - * @note This function changes the internal state of this class. In particular, - * 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. - */ - void configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t axis); - /** Utility method to configure the kernels needed to flatten the input - * tensor. - * - * @note This function changes the internal state of this class. In particular, - * it initializes the kernel @p _flatten_kernel and the tensors @p _input_flat and - * @p _output_flat - * - * @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. - */ - void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t axis); - - MemoryGroup _memory_group; - CLLogits1DMaxShiftExpSumKernel _max_shift_exp_sum_kernel; - CLLogits1DNormKernel _norm_kernel; - std::unique_ptr<ICLKernel> _flatten_kernel_ptr; - CLReshapeLayerKernel _reshape_kernel; - CLTensor _max; - CLTensor _sum; - CLTensor _tmp; - CLTensor _input_flattened; - CLTensor _output_flattened; - bool _needs_flattening; + struct Impl; + std::unique_ptr<Impl> _impl; }; using CLSoftmaxLayer = CLSoftmaxLayerGeneric<false>; using CLLogSoftmaxLayer = CLSoftmaxLayerGeneric<true>; } // namespace arm_compute -#endif /* ARM_COMPUTE_CLSOFTMAXLAYER_H */ +#endif // ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLSOFTMAXLAYER_H |