diff options
| author | Vidhya Sudhan Loganathan <vidhyasudhan.loganathan@arm.com> | 2018-07-04 15:13:14 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:10 +0000 |
| commit | f4cb81be294a1075ce3ce7d11dd60bdee5505ce9 (patch) | |
| tree | 33e903042fab84a7f469855078131bd3fd01df4e /arm_compute/core/CL | |
| parent | 060c4b784b1e66f937369e420fa97c7fb71d5fd4 (diff) | |
| download | ComputeLibrary-f4cb81be294a1075ce3ce7d11dd60bdee5505ce9.tar.gz | |
COMPMID-970 : Remove QS8 / QS16 support
Removed QS32 references
Change-Id: Ic7df02c08ae7aa1b7dcae15bdda113321af851b8
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/138703
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'arm_compute/core/CL')
| -rw-r--r-- | arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h | 4 | ||||
| -rw-r--r-- | arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h | 4 |
2 files changed, 4 insertions, 4 deletions
diff --git a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h index f5e2f0de89..b85f93e992 100644 --- a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h +++ b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h @@ -55,7 +55,7 @@ public: ~CLConvertFullyConnectedWeightsKernel() = default; /** Set the input and output tensor. * - * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/QS32/F16/F32. + * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32. * @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input. * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format. * @param[in] data_layout The data layout the weights have been trained in. @@ -63,7 +63,7 @@ public: void configure(const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout); /** Static function to check if given info will lead to a valid configuration of @ref CLConvertFullyConnectedWeightsKernel * - * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/QS32/F16/F32. + * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32. * @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input. * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format. * @param[in] data_layout The data layout the weights have been trained in. diff --git a/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h b/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h index 1947a98ba3..d90a2cf4b8 100644 --- a/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h +++ b/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h @@ -51,7 +51,7 @@ public: /** 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: S32/QS32/F16/F32 + * Data type supported: S32/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) * Required parameter if output is of QASYMM8 type. @@ -65,7 +65,7 @@ public: /** Static function to check if given info will lead to a valid configuration of @ref CLDirectConvolutionLayerOutputStageKernel * * @param[in] input Input to add the bias to. If @p output is not specified then accumulation is done in-place. - * Data type supported: QS32/F16/F32 + * 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 |