COMPMID-784: Doxygen fixes

Change-Id: I35f429fbf08dece7c759242c37e0a68b0851ce49
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/117231
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

7 files changed, 153 insertions, 70 deletions

diff --git a/arm_compute/core/NEON/kernels/NEWinogradLayerKernel.h b/arm_compute/core/NEON/kernels/NEWinogradLayerKernel.h
index 95261929ca..78ac56418f 100644
--- a/arm_compute/core/NEON/kernels/NEWinogradLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEWinogradLayerKernel.h
@@ -36,21 +36,35 @@ class NEWinogradLayerKernel;
 class Winograd3x3F32 final
 {
 public:
+    /** Create a new Winograd convolution layer.
+     *
+     * @param[in]  n_batches         Number of batches in the input and output tensors.
+     * @param[in]  n_input_channels  Number of feature maps in a batch of the input tensor.
+     * @param[in]  n_input_rows      Number of rows in a feature map of the input tensor.
+     * @param[in]  n_input_cols      Number of columns in a feature map of the input tensor.
+     * @param[in]  n_output_channels Number of feature maps in the output tensor.
+     * @param[in]  same_padding      Use "SAME" padding, otherwise use "VALID".
+     * @param[in]  weights           Pointer to weight tensor in spatial domain. Must be ordered as "Height x Rows x Input Feature Maps x Output Feature Maps.
+     * @param[out] weights_storage   Pointer to storage for weight tensor in the Winograd domain. Must be at least the size returned by `get_weight_storage_size
+     * @param[in]  input             Pointer to NHWC ordered input tensor, in the spatial domain.
+     * @param[out] winograd_input    Pointer to working space for the input tensor in the Winograd domain. Must be at least the size returned by `get_input_storage_size`.
+     * @param[out] output            Pointer to NHWC ordered output tensor, in the spatial domain.
+     * @param[out] winograd_output   Pointer to working space for the output tensor in the Winograd domain. Must be at least the size returned by `get_output_storage_size`.
+     */
     friend class NEWinogradLayerKernel;
     Winograd3x3F32(
-        const int          n_batches,         /** Number of batches in the input and output tensors. */
-        const int          n_input_channels,  /** Number of feature maps in a batch of the input tensor. */
-        const int          n_input_rows,      /** Number of rows in a feature map of the input tensor. */
-        const int          n_input_cols,      /** Number of columns in a feature map of the input tensor. */
-        const int          n_output_channels, /** Number of feature maps in the output tensor. */
-        const bool         same_padding,      /** Use "SAME" padding, otherwise use "VALID". */
-        const float *const weights,           /** Pointer to weight tensor in spatial domain. Must be ordered as "Height x Rows x Input Feature Maps x Output Feature Maps. */
-        float *const       weights_storage,   /** Pointer to storage for weight tensor in the Winograd domain. Must be at least the size returned by `get_weight_storage_size`. */
-        const float *const input,             /** Pointer to NHWC ordered input tensor, in the spatial domain. */
-        float *const       winograd_input,    /** Pointer to working space for the input tensor in the Winograd domain. Must be at least the size returned by `get_input_storage_size`. */
-        float *const       output,            /** Pointer to NHWC ordered output tensor, in the spatial domain. */
-        float *const       winograd_output    /** Pointer to working space for the output tensor in the Winograd domain. Must be at least the size returned by `get_output_storage_size`. */
-    );
+        const int          n_batches,
+        const int          n_input_channels,
+        const int          n_input_rows,
+        const int          n_input_cols,
+        const int          n_output_channels,
+        const bool         same_padding,
+        const float *const weights,
+        float *const       weights_storage,
+        const float *const input,
+        float *const       winograd_input,
+        float *const       output,
+        float *const       winograd_output);
 
     ~Winograd3x3F32();
     void transform_weights();
@@ -88,31 +102,47 @@ public:
     // Inherited methods overridden:
     void run(const Window &window, const ThreadInfo &info) override;
 
-    /* Get the memory required to instantiate a new Winograd operator.
-       */
-    static size_t get_weight_storage_size(
-        const int n_output_channels, /** Number of output feature maps. */
-        const int n_input_channels   /** Number of input feature maps. */
-    );
+    /** Determine how much memory (in units of TIn) to allocate for the
+     * transformed weights.
+     *
+     * @param[in] n_output_channels Number of output feature maps.
+     * @param[in] n_input_channels  Number of input feature maps.
+     */
+    static unsigned int get_weight_storage_size(
+        const int n_output_channels,
+        const int n_input_channels);
 
+    /** Determine how much memory (in units of TIn) to allocate for the
+     * transformed input.
+     *
+     * @param[in] n_batches    Number of batches in the input tensor.
+     * @param[in] n_channels   Number of feature maps in the input tensor.
+     * @param[in] n_rows       Number of rows in each feature map.
+     * @param[in] n_cols       Number of columns in each feature map.
+     * @param[in] same_padding Use "SAME" padding, otherwise use "VALID".
+     */
     static unsigned int get_input_storage_size(
-        const int  n_batches,   /** Number of batches in the input tensor. */
-        const int  n_channels,  /** Number of feature maps in the input tensor. */
-        const int  n_rows,      /** Number of rows in each feature map. */
-        const int  n_cols,      /** Number of columns in each feature map. */
-        const bool same_padding /** Use "SAME" padding, otherwise use "VALID". */
-    );
+        const int  n_batches,
+        const int  n_channels,
+        const int  n_rows,
+        const int  n_cols,
+        const bool same_padding);
 
     /** Determine how much memory (in units of TOut) to allocate for the
      * (Winograd domain) output.
+     *
+     * @param[in] n_batches         Number of batches in the output tensor.
+     * @param[in] n_rows            Number of rows in each feature map of the input tensor.
+     * @param[in] n_cols            Number of columns in each feature map of the input tensor.
+     * @param[in] n_output_channels Number of feature maps in the output tensor.
+     * @param[in] same_padding      Use "SAME" padding, otherwise use "VALID".
      */
     static unsigned int get_output_storage_size(
-        const int  n_batches,         /** Number of batches in the output tensor. */
-        const int  n_rows,            /** Number of rows in each feature map of the input tensor. */
-        const int  n_cols,            /** Number of columns in each feature map of the input tensor. */
-        const int  n_output_channels, /** Number of feature maps in the output tensor. */
-        const bool same_padding       /** Use "SAME" padding, otherwise use "VALID". */
-    );
+        const int  n_batches,
+        const int  n_rows,
+        const int  n_cols,
+        const int  n_output_channels,
+        const bool same_padding);
 
 protected:
     Winograd3x3F32 *_convolver;
diff --git a/arm_compute/core/NEON/kernels/winograd/perf.h b/arm_compute/core/NEON/kernels/winograd/perf.h
index 0cdf742a25..3c0d36646d 100644
--- a/arm_compute/core/NEON/kernels/winograd/perf.h
+++ b/arm_compute/core/NEON/kernels/winograd/perf.h
@@ -1,3 +1,26 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
 #pragma once
 
 /* Prototypes from perf.c */
diff --git a/arm_compute/core/NEON/kernels/winograd/winograd_layer.hpp b/arm_compute/core/NEON/kernels/winograd/winograd_layer.hpp
index a3b3db42dd..4559312df4 100644
--- a/arm_compute/core/NEON/kernels/winograd/winograd_layer.hpp
+++ b/arm_compute/core/NEON/kernels/winograd/winograd_layer.hpp
@@ -74,55 +74,87 @@ class WinogradConvolutionLayer
 
     /** Determine how much memory (in units of TIn) to allocate for the
      * transformed weights.
+     *
+     * @param[in]  n_output_channels Number of output feature maps.
+     * @param[in]  n_input_channels  Number of input feature maps.
      */
     static unsigned int get_weight_storage_size(
-      const int n_output_channels,  /** Number of output feature maps. */
-      const int n_input_channels    /** Number of input feature maps. */
+      const int n_output_channels,
+      const int n_input_channels
     );
 
     /** Determine how much memory (in units of TIn) to allocate for the
      * transformed input.
+     *
+     * @param[in]  n_batches  Number of batches in the input tensor.
+     * @param[in]  n_channels Number of feature maps in the input tensor.
+     * @param[in]  n_rows Number of rows in each feature map.
+     * @param[in]  n_cols Number of columns in each feature map.
+     * @param[in]  same_padding Use "SAME" padding, otherwise use "VALID".
      */
     static unsigned int get_input_storage_size(
-      const int n_batches,     /** Number of batches in the input tensor. */
-      const int n_channels,    /** Number of feature maps in the input tensor. */
-      const int n_rows,        /** Number of rows in each feature map. */
-      const int n_cols,        /** Number of columns in each feature map. */
-      const bool same_padding  /** Use "SAME" padding, otherwise use "VALID". */
+      const int n_batches,
+      const int n_channels,
+      const int n_rows,
+      const int n_cols,
+      const bool same_padding
     );
 
     /** Determine how much memory (in units of TOut) to allocate for the
      * (Winograd domain) output.
+     *
+     * @param[in]  n_batches  Number of batches in the output tensor.
+     * @param[in]  n_rows Number of rows in each feature map of the input tensor.
+     * @param[in]  n_cols Number of columns in each feature map of the input tensor.
+     * @param[in]  n_output_channels Number of feature maps in the output tensor.
+     * @param[in]  same_padding Use "SAME" padding, otherwise use "VALID".
      */
     static unsigned int get_output_storage_size(
-      const int n_batches,          /** Number of batches in the output tensor. */
-      const int n_rows,             /** Number of rows in each feature map of the input tensor. */
-      const int n_cols,             /** Number of columns in each feature map of the input tensor. */
-      const int n_output_channels,  /** Number of feature maps in the output tensor. */
-      const bool same_padding       /** Use "SAME" padding, otherwise use "VALID". */
+      const int n_batches,
+      const int n_rows,
+      const int n_cols,
+      const int n_output_channels,
+      const bool same_padding
     );
 
-    /** Get the shape (rows, cols) of a feature map of the output tensor. */
+    /** Get the shape (rows, cols) of a feature map of the output tensor.
+     *
+     * @param[in]  n_input_rows  Number of rows in the input feature map.
+     * @param[in]  n_input_cols  Number of columns in the input feature map.
+     * @param[in]  same_padding Use "SAME" padding, otherwise use "VALID".
+    */
     static std::pair<int, int> get_output_feature_map_shape(
-      const int n_input_rows,  /** Number of rows in the input feature map. */
-      const int n_input_cols,  /** Number of columns in the input feature map. */
-      const bool same_padding  /** Use "SAME" padding, otherwise use "VALID". */
+      const int n_input_rows,
+      const int n_input_cols,
+      const bool same_padding
     );
 
     /** Create a new Winograd convolution layer.
+     * @param[in]  n_batches Number of batches in the input and output tensors.
+     * @param[in]  n_input_channels Number of feature maps in a batch of the input tensor.
+     * @param[in]  n_input_rows Number of rows in a feature map of the input tensor.
+     * @param[in]  n_input_cols Number of columns in a feature map of the input tensor.
+     * @param[in]  n_output_channels Number of feature maps in the output tensor.
+     * @param[in]  same_padding Use "SAME" padding, otherwise use "VALID".
+     * @param[in]  weights Pointer to weight tensor in spatial domain. Must be ordered as "Height x Rows x Input Feature Maps x Output Feature Maps.
+     * @param[out]  weights_storage Pointer to storage for weight tensor in the Winograd domain. Must be at least the size returned by `get_weight_storage_size
+     * @param[in]  input Pointer to NHWC ordered input tensor, in the spatial domain.
+     * @param[out] winograd_input Pointer to working space for the input tensor in the Winograd domain. Must be at least the size returned by `get_input_storage_size`.
+     * @param[out]  output Pointer to NHWC ordered output tensor, in the spatial domain.
+     * @param[out]  winograd_output Pointer to working space for the output tensor in the Winograd domain. Must be at least the size returned by `get_output_storage_size`.
      */
     WinogradConvolutionLayer(
-      const int n_batches,          /** Number of batches in the input and output tensors. */
-      const int n_input_channels,   /** Number of feature maps in a batch of the input tensor. */
-      const int n_input_rows,       /** Number of rows in a feature map of the input tensor. */
-      const int n_input_cols,       /** Number of columns in a feature map of the input tensor. */
-      const int n_output_channels,  /** Number of feature maps in the output tensor. */
-      const bool same_padding,      /** Use "SAME" padding, otherwise use "VALID". */
-      const TIn* const weights,     /** Pointer to weight tensor in spatial domain. Must be ordered as "Height x Rows x Input Feature Maps x Output Feature Maps. */
-      TIn* const weights_storage,   /** Pointer to storage for weight tensor in the Winograd domain. Must be at least the size returned by `get_weight_storage_size`. */
-      const TIn* const input,       /** Pointer to NHWC ordered input tensor, in the spatial domain. */
-      TIn* const winograd_input,    /** Pointer to working space for the input tensor in the Winograd domain. Must be at least the size returned by `get_input_storage_size`. */
-      TOut* const output,           /** Pointer to NHWC ordered output tensor, in the spatial domain. */
-      TOut* const winograd_output   /** Pointer to working space for the output tensor in the Winograd domain. Must be at least the size returned by `get_output_storage_size`. */
+      const int n_batches,
+      const int n_input_channels,
+      const int n_input_rows,
+      const int n_input_cols,
+      const int n_output_channels,
+      const bool same_padding,
+      const TIn* const weights,
+      TIn* const weights_storage,
+      const TIn* const input,
+      TIn* const winograd_input,
+      TOut* const output,
+      TOut* const winograd_output
     );
 };
diff --git a/docs/Doxyfile b/docs/Doxyfile
index de0320f38b..59aa780fd3 100644
--- a/docs/Doxyfile
+++ b/docs/Doxyfile
@@ -855,7 +855,8 @@ RECURSIVE              = YES
 # Note that relative paths are relative to the directory from which doxygen is
 # run.
 
-EXCLUDE                = 
+EXCLUDE                = ./arm_compute/core/NEON/kernels/assembly/ \ 
+                         ./arm_compute/core/NEON/kernels/winograd/
 
 # The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
 # directories that are symbolic links (a Unix file system feature) are excluded
diff --git a/src/core/CL/kernels/CLPermuteKernel.cpp b/src/core/CL/kernels/CLPermuteKernel.cpp
index 7001c5565b..132de60b68 100644
--- a/src/core/CL/kernels/CLPermuteKernel.cpp
+++ b/src/core/CL/kernels/CLPermuteKernel.cpp
@@ -46,7 +46,8 @@ TensorShape get_output_shape(const ITensorInfo *input, const PermutationVector &
     permute(output_shape, perm);
     return output_shape;
 }
-}
+} // namespace
+
 void CLPermuteKernel::configure(const ICLTensor *input, ICLTensor *output, const PermutationVector &perm)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::QS8, DataType::QASYMM8,
diff --git a/src/core/CPP/kernels/CPPPermuteKernel.cpp b/src/core/CPP/kernels/CPPPermuteKernel.cpp
index c7bae870d1..298c700809 100644
--- a/src/core/CPP/kernels/CPPPermuteKernel.cpp
+++ b/src/core/CPP/kernels/CPPPermuteKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017, 2018 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -76,17 +76,13 @@ inline void permute_strides(Dimensions<T> &dimensions, const PermutationVector &
 
 } // namespace
 
-
-
-
 template <typename T>
 void CPPPermuteKernel::run_permute(const Window &window)
 {
-
-    Strides strides = _output->info()->strides_in_bytes();
+    Strides strides      = _output->info()->strides_in_bytes();
     Strides perm_strides = strides;
-    permute_strides(perm_strides,_perm);
-    const int output_stride_w = strides[3];
+    permute_strides(perm_strides, _perm);
+    const int               output_stride_w = strides[3];
     Window                  window_out(window);
     const Window::Dimension zero_window = Window::Dimension(0, 0, 0);
     for(size_t d = 0; d <= _perm.num_dimensions(); ++d)
diff --git a/src/core/NEON/kernels/NEWinogradLayerKernel.cpp b/src/core/NEON/kernels/NEWinogradLayerKernel.cpp
index 24d72eddd8..ea48e1f32b 100644
--- a/src/core/NEON/kernels/NEWinogradLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEWinogradLayerKernel.cpp
@@ -118,7 +118,7 @@ unsigned int NEWinogradLayerKernel::get_output_storage_size(
     return T::get_output_storage_size(n_batches, n_rows, n_cols, n_output_channels, same_padding);
 }
 
-size_t NEWinogradLayerKernel::get_weight_storage_size(const int n_output_channels, const int n_input_channels)
+unsigned int NEWinogradLayerKernel::get_weight_storage_size(const int n_output_channels, const int n_input_channels)
 {
     return T::get_weight_storage_size(n_output_channels, n_input_channels);
 }