COMPMID-970 : Remove QS8 / QS16 support

Removed QS32 references

Change-Id: Ic7df02c08ae7aa1b7dcae15bdda113321af851b8
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/138703
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

7 files changed, 9 insertions, 13 deletions

diff --git a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h
index f5e2f0de89..b85f93e992 100644
--- a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h
+++ b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h
@@ -55,7 +55,7 @@ public:
     ~CLConvertFullyConnectedWeightsKernel() = default;
     /** Set the input and output tensor.
      *
-     * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/QS32/F16/F32.
+     * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
      * @param[out] output               The converted weights tensor. Shape and Data Type: Same as @p input.
      * @param[in]  original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format.
      * @param[in]  data_layout          The data layout the weights have been trained in.
@@ -63,7 +63,7 @@ public:
     void configure(const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
     /** Static function to check if given info will lead to a valid configuration of @ref CLConvertFullyConnectedWeightsKernel
      *
-     * @param[in] input                Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/QS32/F16/F32.
+     * @param[in] input                Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
      * @param[in] output               The converted weights tensor info. Shape and Data Type: Same as @p input.
      * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format.
      * @param[in] data_layout          The data layout the weights have been trained in.
diff --git a/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h b/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h
index 1947a98ba3..d90a2cf4b8 100644
--- a/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h
+++ b/arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h
@@ -51,7 +51,7 @@ public:
     /** Set the accumulate buffer and the biases of the kernel.
      *
      * @param[in, out] input                        Input to add the bias to. If @p output is not specified then accumulation is done in-place.
-     *                                              Data type supported: S32/QS32/F16/F32
+     *                                              Data type supported: S32/F16/F32
      * @param[in]      bias                         (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input
      * @param[out]     output                       (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr)
      *                                              Required parameter if output is of QASYMM8 type.
@@ -65,7 +65,7 @@ public:
     /** Static function to check if given info will lead to a valid configuration of @ref CLDirectConvolutionLayerOutputStageKernel
      *
      * @param[in] input  Input to add the bias to. If @p output is not specified then accumulation is done in-place.
-     *                   Data type supported: QS32/F16/F32
+     *                   Data type supported: F16/F32
      * @param[in] bias   (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input
      * @param[in] output (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr)
      *                         Data type supported: F16/F32
diff --git a/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h b/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h
index d5c9e3bbe9..1a276c353e 100644
--- a/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h
+++ b/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h
@@ -59,7 +59,7 @@ public:
     ~NEConvertFullyConnectedWeightsKernel() = default;
     /** Set the input and output tensor.
      *
-     * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/QS32/F16/F32.
+     * @param[in]  input                Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
      * @param[out] output               The converted weights tensor. Shape and Data Type: Same as @p input.
      * @param[in]  original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format.
      * @param[in]  data_layout          The data layout the weights have been trained in.
@@ -67,7 +67,7 @@ public:
     void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
     /** Static function to check if given info will lead to a valid configuration of @ref NEConvertFullyConnectedWeightsKernel
      *
-     * @param[in] input                Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/QS32/F16/F32.
+     * @param[in] input                Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
      * @param[in] output               The converted weights tensor info. Shape and Data Type: Same as @p input.
      * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format.
      * @param[in] data_layout          The data layout the weights have been trained in.
diff --git a/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerKernel.h b/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerKernel.h
index 589725ab01..e9349a3197 100644
--- a/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerKernel.h
@@ -74,7 +74,7 @@ public:
      *                      The 3rd dimension must be the same as the input's volume 3rd dimension.
      *                      Data type supported:Same as @p input.
      * @param[in] output    Output tensor.
-     *                      The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: QS32/F16/F32
+     *                      The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: F16/F32
      * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
      *
      * @return a status
diff --git a/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h b/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h
index 7fd1d70374..9af3de5ffe 100644
--- a/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h
+++ b/arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h
@@ -55,7 +55,7 @@ public:
     /** Set the accumulate buffer and the biases of the kernel.
      *
      * @param[in, out] input                        Input to add the bias to. If @p output is not specified then accumulation is done in-place.
-     *                                              Data type supported: QS32/F16/F32
+     *                                              Data type supported: F16/F32
      * @param[in]      bias                         (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input
      * @param[out]     output                       (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr)
      *                                              Data type supported: F16/F32
@@ -68,7 +68,7 @@ public:
     /** Static function to check if given info will lead to a valid configuration of @ref NEDirectConvolutionLayerOutputStageKernel
      *
      * @param[in] input  Input to add the bias to. If @p output is not specified then accumulation is done in-place.
-     *                   Data type supported: QS32/F16/F32
+     *                   Data type supported: F16/F32
      * @param[in] bias   (Optional) The shared bias tensor to add. It must be 1D Tensor. Data type supported: Same as @p input
      * @param[in] output (Optional) If the output tensor is specified the accumulation is done out-of-place. (Defaults to nullptr)
      *                         Data type supported: F16/F32
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index 89fd4b8bb4..1363324e3b 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -79,7 +79,6 @@ enum class DataType
     S16,     /**< signed 16-bit number */
     U32,     /**< unsigned 32-bit number */
     S32,     /**< signed 32-bit number */
-    QS32,    /**< quantized, symmetric fixed-point 32-bit number */
     U64,     /**< unsigned 64-bit number */
     S64,     /**< signed 64-bit number */
     F16,     /**< 16-bit floating-point number */
diff --git a/arm_compute/core/Utils.h b/arm_compute/core/Utils.h
index cfebfa1506..729a46fe3f 100644
--- a/arm_compute/core/Utils.h
+++ b/arm_compute/core/Utils.h
@@ -119,7 +119,6 @@ inline size_t data_size_from_type(DataType data_type)
         case DataType::F32:
         case DataType::U32:
         case DataType::S32:
-        case DataType::QS32:
             return 4;
         case DataType::F64:
         case DataType::U64:
@@ -192,7 +191,6 @@ inline size_t element_size_from_data_type(DataType dt)
         case DataType::U32:
         case DataType::S32:
         case DataType::F32:
-        case DataType::QS32:
             return 4;
         default:
             ARM_COMPUTE_ERROR("Undefined element size for given data type");
@@ -527,7 +525,6 @@ inline DataType get_promoted_data_type(DataType dt)
         case DataType::U32:
         case DataType::S32:
         case DataType::F32:
-        case DataType::QS32:
             ARM_COMPUTE_ERROR("Unsupported data type promotions!");
         default:
             ARM_COMPUTE_ERROR("Undefined data type!");