diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLSoftmaxLayer.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLSoftmaxLayer.h | 57 |
1 files changed, 18 insertions, 39 deletions
diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h index bb01584ff4..fd71f3ed4d 100644 --- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h +++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h @@ -26,8 +26,7 @@ #include "arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h" #include "arm_compute/runtime/CL/CLTensor.h" -#include "arm_compute/runtime/CL/functions/CLFlattenLayer.h" -#include "arm_compute/runtime/CL/functions/CLReshapeLayer.h" +#include "arm_compute/runtime/CL/functions/CLPermute.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/IMemoryManager.h" #include "arm_compute/runtime/MemoryGroup.h" @@ -47,7 +46,10 @@ class ICLTensor; * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f] * * This function runs the following kernels: + * -# If axis is not 0: + * -# @ref CLPermute * -# @ref CLLogits1DNormKernel + * -# @ref CLLogits1DMaxShiftExpSumKernel */ template <bool IS_LOG = false> class CLSoftmaxLayerGeneric : public IFunction @@ -60,70 +62,47 @@ public: * @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) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0. + * @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 = 0); + 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/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) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0. + * @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 = 0); + 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/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) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0. + * @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 = 0); + 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) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0. - */ - 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) The last axis of the first n dimensions (inclusive)to reduce. Only supports axis 0. - */ - void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t axis); - MemoryGroup _memory_group; + CLPermute _permute_input; + CLPermute _permute_output; CLLogits1DMaxShiftExpSumKernel _max_shift_exp_sum_kernel; CLLogits1DNormKernel _norm_kernel; - std::unique_ptr<IFunction> _flatten_ptr; - CLReshapeLayer _reshape; CLTensor _max; CLTensor _sum; CLTensor _tmp; - CLTensor _input_flattened; - CLTensor _output_flattened; - bool _needs_flattening; + CLTensor _input_permuted; + CLTensor _output_permuted; + bool _needs_permute; }; using CLSoftmaxLayer = CLSoftmaxLayerGeneric<false>; |