COMPMID-3532: Align data type support between doxygen and implementation - CL

Also removes some unused code.

Change-Id: I85687c40999c3cdf9e6fccfcd020b0901a9515fe
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3581
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 18 insertions, 20 deletions

diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
index 93ad24e893..ec57bacf07 100644
--- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
+++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
@@ -47,8 +47,6 @@ class ICLTensor;
  * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f]
  *
  * This function runs the following kernels:
- * -# @ref CLLogits1DMaxKernel
- * -# @ref CLLogits1DShiftExpSumKernel
  * -# @ref CLLogits1DNormKernel
  * And if the reduce_end_axis is not 0, the function will use one of the the following kernels to reshape the input and
  * perform softmax on the reshaped input:
@@ -63,36 +61,36 @@ public:
     CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
     /** Set the input and output tensors.
      *
-     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32 for Softmax and F16/F32 for Log Softmax
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax
      * @param[out] output          Destination tensor. Data types supported: same as @p input
      * @param[in]  beta            (Optional) A scaling factor for the exponent. Defaults to 1.f
      * @param[in]  reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
-     *                   It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
-     *                   when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
-     *                   Must be in range [0, input_num_dimensions).
+     *                             It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
+     *                             when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
+     *                             Must be in range [0, input_num_dimensions).
      */
     void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t reduce_end_axis = 0);
     /** Set the input and output tensors.
      *
      * @param[in]  compile_context The compile context to be used.
-     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32 for Softmax and F16/F32 for Log Softmax
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax
      * @param[out] output          Destination tensor. Data types supported: same as @p input
      * @param[in]  beta            (Optional) A scaling factor for the exponent. Defaults to 1.f
      * @param[in]  reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
-     *                   It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
-     *                   when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
-     *                   Must be in range [0, input_num_dimensions).
+     *                             It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
+     *                             when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
+     *                             Must be in range [0, input_num_dimensions).
      */
     void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t reduce_end_axis = 0);
     /** Static function to check if given info will lead to a valid configuration of @ref CLSoftmaxLayer
      *
-     * @param[in] input           Source tensor. Data types supported: QASYMM8/F16/F32 for Softmax and F16/F32 for Log Softmax
+     * @param[in] input           Source tensor. Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32 for Softmax and F16/F32 for Log Softmax
      * @param[in] output          Destination tensor. Data types supported: same as @p input
      * @param[in] beta            (Optional) A scaling factor for the exponent. Defaults to 1.f
      * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
-     *                   It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
-     *                   when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
-     *                   Must be in range [0, input_num_dimensions).
+     *                            It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
+     *                            when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
+     *                            Must be in range [0, input_num_dimensions).
      * @return a status
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *output, float beta = 1.0f, size_t reduce_end_axis = 0);
@@ -111,9 +109,9 @@ private:
      * @param[in] input           Original source tensor.
      * @param[in] output          Original destination tensor.
      * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
-     *                   It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
-     *                   when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
-     *                   Must be in range [0, input_num_dimensions).
+     *                            It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
+     *                            when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
+     *                            Must be in range [0, input_num_dimensions).
      */
     void configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t reduce_end_axis);
     /** Utility method to configure the kernels needed to flatten the input
@@ -127,9 +125,9 @@ private:
      * @param[in] input           Original source tensor.
      * @param[in] output          Original destination tensor.
      * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
-     *                   It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
-     *                   when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
-     *                   Must be in range [0, input_num_dimensions).
+     *                            It has the purpose of squashing together the first n dimensions till (including) the @p reduce_end_axis. For instance, given a [2x3x4x5] image,
+     *                            when @p reduce_end_axis is 1, the reduction will be applied to axes 0 and 1, and the Softmax op will be applied on each of the [2x3] planes of the input image.
+     *                            Must be in range [0, input_num_dimensions).
      */
     void configure_reshape_input_kernel(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *output, size_t reduce_end_axis);