diff options
Diffstat (limited to 'arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h')
| -rw-r--r-- | arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h | 39 |
1 files changed, 20 insertions, 19 deletions
diff --git a/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h b/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h index 3f41edc5aa..b7632d70c4 100644 --- a/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h +++ b/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -24,6 +24,7 @@ #ifndef ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYEROUTPUTSTAGEKERNEL_H #define ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYEROUTPUTSTAGEKERNEL_H +#include "arm_compute/core/KernelDescriptors.h" #include "arm_compute/core/NEON/INEKernel.h" namespace arm_compute @@ -32,6 +33,8 @@ class ITensor; /** NEON kernel to accumulate the biases, if provided, or downscale in case of quantized input. * * @note We assume bias to be shared + * @note For quantized computations (i.e. @p input of S32 type) the output data type for auto-initialization must be passed as part + * of the @ref DirectConvolutionLayerOutputStageKernelInfo. */ class NEDirectConvolutionLayerOutputStageKernel : public INEKernel { @@ -54,32 +57,30 @@ public: ~NEDirectConvolutionLayerOutputStageKernel() = default; /** Set the accumulate buffer and the biases of the kernel. * - * @param[in, out] input Input to add the bias to. If @p output is not specified then accumulation is done in-place. - * Data type supported: F16/F32 - * @param[in] bias (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input - * @param[out] output (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr) - * Data type supported: F16/F32 - * @param[in] result_fixedpoint_multiplier (Optional) Fixed point value to be multiplied to each element of the input matrix once the result_offset has been added - * @param[in] result_shift (Optional) Integer value used to round the result of the fixed point multiplication to nearest division by a power-of-two - * @param[in] result_offset_after_shift (Optional) Offset to be applied to result before converting it back to QASYMM8 + * @param[in, out] input Input to add the bias to. If @p output is not specified then accumulation is done in-place. + * Data type supported: F16/F32/S32 + * @param[in] bias (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input + * @param[out] output (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr) + * Note that in-place computation is only supported for F16/F32. For S32 this must not be nullptr. + * Data type supported: F16/F32 or QASYMM8/QASYMM8_SIGNED if @p input is S32 + * @param[in] info (Optional) DirectConvolutionLayerOutputStageKernel descriptor metadata */ void configure(ITensor *input, const ITensor *bias = nullptr, ITensor *output = nullptr, - int result_fixedpoint_multiplier = 0, int result_shift = 0, int result_offset_after_shift = 0); + const DirectConvolutionLayerOutputStageKernelInfo &info = DirectConvolutionLayerOutputStageKernelInfo()); /** Static function to check if given info will lead to a valid configuration of @ref NEDirectConvolutionLayerOutputStageKernel * - * @param[in] input Input to add the bias to. If @p output is not specified then accumulation is done in-place. - * Data type supported: F16/F32 - * @param[in] bias (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input - * @param[in] output (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr) - * Data type supported: F16/F32 - * @param[in] result_fixedpoint_multiplier (Optional) Fixed point value to be multiplied to each element of the input matrix once the result_offset has been added - * @param[in] result_shift (Optional) Integer value used to round the result of the fixed point multiplication to nearest division by a power-of-two - * @param[in] result_offset_after_shift (Optional) Offset to be applied to result before converting it back to QASYMM8 + * @param[in] input Input to add the bias to. If @p output is not specified then accumulation is done in-place. + * Data type supported: F16/F32/S32 + * @param[in] bias (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input + * @param[in] output (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr) + * Note that in-place computation is only supported for F16/F32. For S32 this must not be nullptr. + * Data type supported: F16/F32 or QASYMM8/QASYMM8_SIGNED if @p input is S32 + * @param[in] info (Optional) DirectConvolutionLayerOutputStageKernel descriptor metadata * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *bias = nullptr, const ITensorInfo *output = nullptr, - int result_fixedpoint_multiplier = 0, int result_shift = 0, int result_offset_after_shift = 0); + const DirectConvolutionLayerOutputStageKernelInfo &info = DirectConvolutionLayerOutputStageKernelInfo()); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; |