COMPMID-2608: Enable quantization with multiplier greater than 1 on NEON
Change-Id: Ib2b0c9ac88fc2b645f478c9981f71ee28f2c77fd
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2425
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
index 8150737..784637a 100644
--- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
@@ -131,7 +131,7 @@
* 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 @@
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 665d4f1..660f559 100644
--- a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h
@@ -64,15 +64,17 @@
/** 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
*/