diff options
Diffstat (limited to 'arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h')
-rw-r--r-- | arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h b/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h index c54339da72..d45191949a 100644 --- a/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h +++ b/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h @@ -28,6 +28,7 @@ namespace arm_compute { +// Forward declarations class ITensor; /** Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa. @@ -59,7 +60,7 @@ public: ~NEConvertFullyConnectedWeightsKernel() = 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/F16/F32. + * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: All. * @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). * @param[in] data_layout The data layout the weights have been trained in. @@ -67,7 +68,7 @@ public: void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout); /** Static function to check if given info will lead to a valid configuration of @ref NEConvertFullyConnectedWeightsKernel * - * @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] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All. * @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). * @param[in] data_layout The data layout the weights have been trained in. |