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-rw-r--r--arm_compute/core/CL/kernels/CLCol2ImKernel.h2
-rw-r--r--arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h2
-rw-r--r--arm_compute/core/CL/kernels/CLIm2ColKernel.h2
-rw-r--r--arm_compute/core/CL/kernels/CLTransposeKernel.h2
-rw-r--r--arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h2
-rw-r--r--arm_compute/runtime/CL/functions/CLConvolutionLayer.h4
-rw-r--r--arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h2
7 files changed, 8 insertions, 8 deletions
diff --git a/arm_compute/core/CL/kernels/CLCol2ImKernel.h b/arm_compute/core/CL/kernels/CLCol2ImKernel.h
index 63b0b63f20..9866c44011 100644
--- a/arm_compute/core/CL/kernels/CLCol2ImKernel.h
+++ b/arm_compute/core/CL/kernels/CLCol2ImKernel.h
@@ -66,7 +66,7 @@ public:
/** Set the input and output of the kernel.
*
- * @param[in] input The input tensor to convert. Data types supported: QS8/F16/F32
+ * @param[in] input The input tensor to convert. Data types supported: QS8/QS16/F16/F32
* @param[out] output The output tensor. 3 lower dimensions represent a single output [width, height, OFM],
* while the rest represent batch of outputs. Data types supported: Same as @p input
* @param[in] convolved_dims Output convolved dimensions.
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
index 74a7a0e4a6..167664f493 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
@@ -46,7 +46,7 @@ public:
CLGEMMMatrixAccumulateBiasesKernel &operator=(CLGEMMMatrixAccumulateBiasesKernel &&) = default;
/** Set the accumulate buffer and the biases of the kernel.
*
- * @param[in, out] accum The accumulate tensor to convert. Data types supported: QS8/F16/F32
+ * @param[in, out] accum The accumulate tensor to convert. Data types supported: QS8/QS16/F16/F32
* @param[in] biases The shared biases tensor to append. It must be 1D tensor. Data types supported: Same as @p input
*/
void configure(ICLTensor *accum, const ICLTensor *biases);
diff --git a/arm_compute/core/CL/kernels/CLIm2ColKernel.h b/arm_compute/core/CL/kernels/CLIm2ColKernel.h
index e9f1a3f8e2..b9eeb2e088 100644
--- a/arm_compute/core/CL/kernels/CLIm2ColKernel.h
+++ b/arm_compute/core/CL/kernels/CLIm2ColKernel.h
@@ -69,7 +69,7 @@ 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. First 2 lower dimensions represent a transform of each 3D input,
* while every dimension above represents a batch. Data types supported: Same as @p input
* @param[in] kernel_dims The kernel dimensions (width and height).
diff --git a/arm_compute/core/CL/kernels/CLTransposeKernel.h b/arm_compute/core/CL/kernels/CLTransposeKernel.h
index 79596f34a1..98c69f4d67 100644
--- a/arm_compute/core/CL/kernels/CLTransposeKernel.h
+++ b/arm_compute/core/CL/kernels/CLTransposeKernel.h
@@ -40,7 +40,7 @@ class CLTransposeKernel : public ICLSimple2DKernel
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 ICLTensor *input, ICLTensor *output);
diff --git a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
index 8732c6094b..099348fb15 100644
--- a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
+++ b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
@@ -47,7 +47,7 @@ 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/F16/F32
+ * and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches] if unshared. Data types supported: QS8/QS16/F16/F32
* @param[in] biases 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. Should be a 2D Tensor. Data types supported: Same as @p input
diff --git a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
index 50a7dc95eb..aba88bd856 100644
--- a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
@@ -53,7 +53,7 @@ public:
CLConvolutionLayerReshapeWeights();
/** 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/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QS8/QS16/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[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.
@@ -88,7 +88,7 @@ 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/F16/F32.
+ * Data types supported: QS8/QS16/F16/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/CL/functions/CLFullyConnectedLayer.h b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
index 807ff693bc..64d56894d3 100644
--- a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
+++ b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
@@ -50,7 +50,7 @@ public:
CLFullyConnectedLayerReshapeWeights();
/** Set the input and output tensors.
*
- * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported: QS8/F16/F32.
+ * @param[in] input Weights tensor. The weights must be 2 dimensional. Data types supported: QS8/QS16/F16/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