diff options
Diffstat (limited to 'arm_compute/runtime/NEON/functions/NESoftmaxLayer.h')
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NESoftmaxLayer.h | 36 |
1 files changed, 13 insertions, 23 deletions
diff --git a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h index 9fb4d85262..20b20201d5 100644 --- a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h +++ b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h @@ -28,8 +28,7 @@ #include "arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h" #include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/MemoryGroup.h" -#include "arm_compute/runtime/NEON/functions/NEFlattenLayer.h" -#include "arm_compute/runtime/NEON/functions/NEReshapeLayer.h" +#include "arm_compute/runtime/NEON/functions/NEPermute.h" #include "arm_compute/runtime/Tensor.h" namespace arm_compute @@ -44,7 +43,9 @@ class ITensor; * Log Softmax is calculated by : * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f] * - * This function runs the following kernels: + * This function runs the following function/kernels: + * -# If axis is not 0: + * -# @ref NEPermute * -# @ref NEFillBorderKernel * -# @ref NELogits1DMaxKernel * -# @ref NELogits1DSoftmaxKernel @@ -70,7 +71,8 @@ public: * 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) 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(ITensor *input, ITensor *output, float beta = 1.0f, int32_t axis = 0); /** Static function to check if given info will lead to a valid configuration of @ref NESoftmaxLayer @@ -78,7 +80,8 @@ public: * @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) 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 */ @@ -88,30 +91,17 @@ public: 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 ITensor *input, const ITensor *output, int32_t axis); - MemoryGroup _memory_group; + NEPermute _permute_input; + NEPermute _permute_output; NELogits1DMaxKernel _max_kernel; NELogits1DSoftmaxKernel<IS_LOG> _softmax_kernel; - std::unique_ptr<IFunction> _flat_or_reshape_ptr; NEFillBorderKernel _fill_border_kernel; - NEReshapeLayer _reshape; Tensor _max; Tensor _tmp; - Tensor _input_flattened; - Tensor _output_flattened; - bool _needs_flattening; + Tensor _input_permuted; + Tensor _output_permuted; + bool _needs_permute; }; using NESoftmaxLayer = NESoftmaxLayerGeneric<false>; |