diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLSoftmaxLayer.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLSoftmaxLayer.h | 38 |
1 files changed, 18 insertions, 20 deletions
diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h index 93ad24e893..ec57bacf07 100644 --- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h +++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h @@ -47,8 +47,6 @@ class ICLTensor; * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f] * * This function runs the following kernels: - * -# @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: @@ -63,36 +61,36 @@ public: CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr); /** Set the input and output tensors. * - * @param[in] input Source tensor. Data types supported: QASYMM8/F16/F32 for Softmax and F16/F32 for Log Softmax + * @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] 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). + * 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 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 for Softmax and F16/F32 for Log Softmax + * @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] 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). + * 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 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 for Softmax and F16/F32 for Log Softmax + * @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] 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). + * 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 reduce_end_axis = 0); @@ -111,9 +109,9 @@ private: * @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). + * 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 reduce_end_axis); /** Utility method to configure the kernels needed to flatten the input @@ -127,9 +125,9 @@ private: * @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). + * 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 reduce_end_axis); |