diff options
Diffstat (limited to 'arm_compute/runtime')
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h | 24 | ||||
| -rw-r--r-- | arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h | 8 |
2 files changed, 17 insertions, 15 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 */ diff --git a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h index 665d4f1bae..660f55953e 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h @@ -64,15 +64,17 @@ public: /** Set the input and output tensors. * * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED. * @param[out] output Destination tensor. Data types supported: Same as @p weights. */ void configure(const ITensor *weights, const ITensor *biases, ITensor *output); /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayerReshapeWeights * * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. - * @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. - * @param[in] output Destination tensor info. Data types supported: Same as @p weights. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED. + * @param[in] output Destination tensor. Data types supported: Same as @p weights. * * @return an error status */ |