COMPMID-436, COMPMID-437 - Port NEConvolutionLayer & NEFullyConnectedLayer to support 16 bit fixed point

Change-Id: I69edf2dac242f941bac95c8479d921e7be6abca7
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79725
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>

6 files changed, 9 insertions, 9 deletions

diff --git a/arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h b/arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h
index c0ecafcd39..1eed4e7a84 100644
--- a/arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h
+++ b/arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h
@@ -47,7 +47,7 @@ public:
     ~NEGEMMMatrixAccumulateBiasesKernel() = default;
     /** Set the accumulate buffer and the biases of the kernel.
      *
-     * @param[in, out] accum  The accumulate tensor to convert. Data type supported: QS8/F32
+     * @param[in, out] accum  The accumulate tensor to convert. Data type supported: QS8/QS16/F32
      * @param[in]      biases The shared biases tensor to append. It must be 1D Tensor. Data type supported: Same as @p input
      */
     void configure(ITensor *accum, const ITensor *biases);
diff --git a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h
index 9b8b98b388..87d7cc0a8b 100644
--- a/arm_compute/core/NEON/kernels/NEIm2ColKernel.h
+++ b/arm_compute/core/NEON/kernels/NEIm2ColKernel.h
@@ -73,7 +73,7 @@ public:
     /** Set the input and output of the kernel.
      *
      * @param[in]  input       The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
-     *                         while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/F16/F32
+     *                         while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QS16/F16/F32
      * @param[out] output      The output tensor. Data types supported: Same as @p input
      * @param[in]  kernel_dims The kernel dimensions (width and height).
      * @param[in]  conv_info   Contains padding and stride information described in @ref PadStrideInfo.
diff --git a/arm_compute/core/NEON/kernels/NETransposeKernel.h b/arm_compute/core/NEON/kernels/NETransposeKernel.h
index ac9449ff92..2f757f18eb 100644
--- a/arm_compute/core/NEON/kernels/NETransposeKernel.h
+++ b/arm_compute/core/NEON/kernels/NETransposeKernel.h
@@ -53,7 +53,7 @@ public:
 
     /** Initialise the kernel's input and output.
      *
-     * @param[in]  input  Input tensor. Data types supported: U8/S8/QS8/U16/S16/F16/U32/S32/F32
+     * @param[in]  input  Input tensor. Data types supported: U8/S8/QS8/U16/S16/QS16/F16/U32/S32/F32
      * @param[out] output Output tensor. Data type supported: Same as @p input
      */
     void configure(const ITensor *input, ITensor *output);
@@ -64,7 +64,7 @@ public:
 private:
     /** Common signature for all the transpose functions
      *
-     * @param[in]  input  An input tensor. Data types supported: U8/S8/QS8/U16/S16/F16/U32/S32/F32
+     * @param[in]  input  An input tensor. Data types supported: U8/S8/QS8/U16/S16/QS16/F16/U32/S32/F32
      * @param[out] output The output tensor. Data type supported: same as @p input
      * @param[in]  window Region on which to execute the kernel.
      */
diff --git a/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h b/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h
index cad2d00b1f..6b76d19314 100644
--- a/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h
+++ b/arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h
@@ -71,7 +71,7 @@ public:
     /** Set the input and output of the kernel.
      *
      * @param[in]  input  The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared,
-     *                    and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QS8/F32
+     *                    and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QS8/QS16/F32
      * @param[in]  bias   The shared biases tensor to append.  Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with
      *                    dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input
      * @param[out] output The output tensor. Data types supported: Same as @p input
diff --git a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h
index a8fff8d047..1bd7e6a95f 100644
--- a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h
@@ -51,7 +51,7 @@ public:
     NEConvolutionLayerReshapeWeights();
     /** 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: QS8/F32.
+     * @param[in]  weights      Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QS8/QS16/F32.
      * @param[in]  biases       Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
      * @param[out] output       Destination tensor. Data types supported: Same as @p weights.
      * @param[in]  transpose1xW True if the weights are to undergo a 1xW transposition after reshaping (in case of GEMM operation), false otherwise.
@@ -84,7 +84,7 @@ public:
      *
      * @param[in]  input        Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
      *                          while every optional dimension from 4 and above represent a batch of inputs.
-     *                          Data types supported: QS8/F32.
+     *                          Data types supported: QS8/QS16/F32.
      * @param[in]  weights      Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
      * @param[in]  biases       Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
      * @param[out] output       Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
diff --git a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
index 33ec4ef721..af571d1057 100644
--- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
@@ -50,7 +50,7 @@ public:
     NEFullyConnectedLayerReshapeWeights();
     /** Set the input and output tensors.
      *
-     * @param[in]  input               Weights tensor. The weights must be 2 dimensional. Data types supported: QS8/F32.
+     * @param[in]  input               Weights tensor. The weights must be 2 dimensional. Data types supported: QS8/QS16/F32.
      * @param[out] output              Destination tensor. Data type supported: Same as @p input.
      * @param[in]  transpose_weights   True if the weights must be transposed. Data types supported: Same as @p weights.
      * @param[in]  is_batched_fc_layer True if it is a batched fully connected layer
@@ -84,7 +84,7 @@ public:
     NEFullyConnectedLayer();
     /** Set the input and output tensors.
      *
-     * @param[in]  input                Source tensor. Data type supported: QS8/F32.
+     * @param[in]  input                Source tensor. Data type supported: QS8/QS16/F32.
      * @param[in]  weights              Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input.
      * @param[in]  biases               Bias tensor. Can be nullptr. Data type supported:Same as @p input.
      * @param[out] output               Destination tensor. Data type supported: Same as @p input.