COMPMID-344 Updated doxygen

Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae

1 files changed, 164 insertions, 0 deletions

diff --git a/src/core/Helpers.cpp b/src/core/Helpers.cpp
new file mode 100644
index 0000000000..ff903e9802
--- /dev/null
+++ b/src/core/Helpers.cpp
@@ -0,0 +1,164 @@
+/*
+ * Copyright (c) 2016, 2017 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.
+ */
+#include "arm_compute/core/Helpers.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/IKernel.h"
+#include "arm_compute/core/ITensorInfo.h"
+#include "arm_compute/core/Utils.h"
+
+#include <algorithm>
+#include <cstdint>
+
+using namespace arm_compute;
+
+Window arm_compute::calculate_max_window(const ITensorInfo &info, const Steps &steps, bool skip_border, BorderSize border_size)
+{
+    if(!skip_border)
+    {
+        border_size = BorderSize(0);
+    }
+
+    const Coordinates &anchor = info.valid_region().anchor;
+    const TensorShape &shape  = info.valid_region().shape;
+
+    Window window;
+
+    window.set(0, Window::Dimension(
+                   // Skip the border left of the image
+                   anchor[0] + border_size.left,
+                   // Skip the border right of the image
+                   // Make sure the window width is a multiple of the step size
+                   anchor[0] + border_size.left + ceil_to_multiple(shape[0] - border_size.left - border_size.right, steps[0]),
+                   steps[0]));
+
+    size_t             n            = 1;
+    const TensorShape &tensor_shape = info.tensor_shape();
+
+    if(tensor_shape.num_dimensions() > 1)
+    {
+        window.set(1, Window::Dimension(
+                       // Skip the border above the image
+                       anchor[1] + border_size.top,
+                       // Skip the border below the image
+                       anchor[1] + border_size.top + ceil_to_multiple(shape[1] - border_size.top - border_size.bottom, steps[1]),
+                       steps[1]));
+
+        ++n;
+    }
+
+    for(; n < Coordinates::num_max_dimensions; ++n)
+    {
+        window.set(n, Window::Dimension(0, std::max<size_t>(1, tensor_shape[n])));
+    }
+
+    return window;
+}
+
+Window arm_compute::calculate_max_enlarged_window(const ITensorInfo &info, const Steps &steps, BorderSize border_size)
+{
+    const Coordinates &anchor = info.valid_region().anchor;
+    const TensorShape &shape  = info.valid_region().shape;
+
+    Window window;
+
+    window.set(0, Window::Dimension(
+                   // move the anchor to the start from the border
+                   anchor[0] - border_size.left,
+                   // move the anchor to include the right end border
+                   // Make sure the window width is a multiple of the step size
+                   anchor[0] - border_size.left + ceil_to_multiple(shape[0] + border_size.left + border_size.right, steps[0]),
+                   steps[0]));
+
+    size_t             n            = 1;
+    const TensorShape &tensor_shape = info.tensor_shape();
+
+    if(tensor_shape.num_dimensions() > 1)
+    {
+        window.set(1, Window::Dimension(
+                       // Include the border above the image
+                       anchor[1] - border_size.top,
+                       // Include the border below the image
+                       anchor[1] - border_size.top + ceil_to_multiple(shape[1] + border_size.top + border_size.bottom, steps[1]),
+                       steps[1]));
+
+        ++n;
+    }
+
+    for(; n < Coordinates::num_max_dimensions; ++n)
+    {
+        window.set(n, Window::Dimension(0, std::max<size_t>(1, tensor_shape[n])));
+    }
+
+    return window;
+}
+
+Window arm_compute::calculate_max_window_horizontal(const ITensorInfo &info, const Steps &steps, bool skip_border, BorderSize border_size)
+{
+    if(skip_border)
+    {
+        border_size.top    = 0;
+        border_size.bottom = 0;
+    }
+    else
+    {
+        border_size.left  = 0;
+        border_size.right = 0;
+    }
+
+    const Coordinates &anchor = info.valid_region().anchor;
+    const TensorShape &shape  = info.valid_region().shape;
+
+    Window window;
+
+    window.set(0, Window::Dimension(
+                   // Skip the border left of the image
+                   anchor[0] + border_size.left,
+                   // Skip the border right of the image
+                   // Make sure the window width is a multiple of the step size
+                   anchor[0] + border_size.left + ceil_to_multiple(shape[0] - border_size.left - border_size.right, steps[0]),
+                   steps[0]));
+
+    size_t             n            = 1;
+    const TensorShape &tensor_shape = info.tensor_shape();
+
+    if(tensor_shape.num_dimensions() > 1)
+    {
+        window.set(1, Window::Dimension(
+                       // Skip the border above the image
+                       anchor[1] - border_size.top,
+                       // Skip the border below the image
+                       anchor[1] + shape[1] + border_size.bottom,
+                       1));
+
+        ++n;
+    }
+
+    for(; n < Coordinates::num_max_dimensions; ++n)
+    {
+        window.set(n, Window::Dimension(0, std::max<size_t>(1, tensor_shape[n])));
+    }
+
+    return window;
+}