diff options
Diffstat (limited to 'arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h')
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h | 24 |
1 files changed, 12 insertions, 12 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h index 8150737ebe..784637a796 100644 --- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h +++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h @@ -131,7 +131,7 @@ public: * If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions. * If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension. * Data type supported: Same as @p input. - * @param[in] biases Bias tensor. Can be nullptr. Data type supported:Same as @p input. + * @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8. * @param[out] output Destination tensor. Its shape should be equal to the output of a matrix multiplication between: * - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer * - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer. @@ -142,17 +142,17 @@ public: FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); /** Static function to check if given info will lead to a valid configuration of @ref NEFullyConnectedLayer * - * @param[in] input Source tensor info. Data type supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor info. The weights must be 2 dimensional. - * If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions. - * If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension. - * Data type supported: Same as @p input. - * @param[in] biases Bias tensor info. Can be nullptr. Data type supported:Same as @p input. - * @param[out] output Destination tensor info. Its shape should be equal to the output of a matrix multiplication between: - * - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer - * - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer. - * Data type supported: Same as @p input. - * @param[in] fc_info (Optional) Fully connected layer additional info + * @param[in] input Source tensor info. Data type supported: QASYMM8/F16/F32. + * @param[in] weights Weights tensor info. The weights must be 2 dimensional. + * If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions. + * If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension. + * Data type supported: Same as @p input. + * @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8. + * @param[in] output Destination tensor info. Its shape should be equal to the output of a matrix multiplication between: + * - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer + * - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer. + * Data type supported: Same as @p input. + * @param[in] fc_info (Optional) Fully connected layer additional info * * @return a status */ |