COMPMID-1379: Created WindowIterator and TensorAccessor

- WindowIterator: used to iterate over arbitrary positions of a window. (More flexible than execute_window_loop which only can iterate over entire dimensions)
- TensorAccessor: RSH's code uses pointers to specialised types and strides in element sizes, this helps interfacing with their code.

Change-Id: I8ded8758d345668804873409f949b8cec694d289
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/139082
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 138 insertions, 0 deletions

diff --git a/tests/validation/UNIT/WindowIterator.cpp b/tests/validation/UNIT/WindowIterator.cpp
new file mode 100644
index 0000000000..0c1ab12fe7
--- /dev/null
+++ b/tests/validation/UNIT/WindowIterator.cpp
@@ -0,0 +1,138 @@
+/*
+ * Copyright (c) 2017-2018 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.
+ */
+#include "arm_compute/core/WindowIterator.h"
+#include "tests/Utils.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "utils/TypePrinter.h"
+
+#include <stdexcept>
+
+using namespace arm_compute;
+using namespace arm_compute::test;
+using namespace arm_compute::test::validation;
+
+TEST_SUITE(UNIT)
+TEST_SUITE(WindowIterator)
+
+template <typename Dim, typename... Dims>
+Window create_window(Dim &&dim0, Dims &&... dims)
+{
+    Window win;
+    const std::array < Dim, 1 + sizeof...(Dims) > dimensions{ { dim0, std::forward<Dims>(dims)... } };
+    for(size_t i = 0; i < dimensions.size(); i++)
+    {
+        win.set(i, dimensions[i]);
+    }
+    return win;
+}
+
+template <typename T>
+std::vector<T> create_vector(std::initializer_list<T> list_objs)
+{
+    std::vector<T> vec_objs;
+    for(auto it : list_objs)
+    {
+        vec_objs.push_back(it);
+    }
+    return vec_objs;
+}
+
+DATA_TEST_CASE(WholeWindow, framework::DatasetMode::ALL, zip(framework::dataset::make("Window", { create_window(Window::Dimension(0, 1)),
+                                                                                                  create_window(Window::Dimension(1, 5, 2), Window::Dimension(3, 5)),
+                                                                                                  create_window(Window::Dimension(4, 16, 4), Window::Dimension(3, 13, 5), Window::Dimension(1, 3, 2))
+                                                                                                }),
+                                                             framework::dataset::make("Expected", { create_vector({ Coordinates(0, 0) }),
+                                                                                                    create_vector({ Coordinates(1, 3), Coordinates(3, 3), Coordinates(1, 4), Coordinates(3, 4) }),
+                                                                                                    create_vector({ Coordinates(4, 3, 1), Coordinates(8, 3, 1), Coordinates(12, 3, 1), Coordinates(4, 8, 1), Coordinates(8, 8, 1), Coordinates(12, 8, 1) })
+                                                                                                  })),
+               window, expected)
+{
+    unsigned int i            = 0;
+    int          row_size     = 0;
+    TensorShape  window_shape = window.shape();
+    Coordinates  start_offset = index2coords(window_shape, 0);
+    Coordinates  end_offset   = index2coords(window_shape, window.num_iterations_total() - 1);
+    auto window_iterator      = create_window_iterator(window, start_offset, end_offset, [&](const Coordinates & id)
+    {
+        ARM_COMPUTE_EXPECT_EQUAL(row_size, (window[0].end() - window[0].start()), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_ASSERT(i < expected.size());
+        Coordinates expected_coords = expected[i++];
+        //Set number of dimensions to the maximum (To match the number of dimensions used by the id passed to the lambda function)
+        expected_coords.set_num_dimensions(Coordinates::num_max_dimensions);
+        ARM_COMPUTE_EXPECT_EQUAL(id, expected_coords, framework::LogLevel::ERRORS);
+    });
+    window_iterator.iterate_3D([&](int start, int end)
+    {
+        ARM_COMPUTE_EXPECT_EQUAL(window[0].start(), start, framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT_EQUAL(window[0].end(), end, framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(end > start, framework::LogLevel::ERRORS);
+        row_size = end - start;
+    });
+    ARM_COMPUTE_EXPECT_EQUAL(i, expected.size(), framework::LogLevel::ERRORS);
+}
+
+DATA_TEST_CASE(PartialWindow2D, framework::DatasetMode::ALL, zip(zip(zip(combine(framework::dataset::make("Window",
+                                                                                                          create_window(Window::Dimension(4, 20, 4), Window::Dimension(3, 18, 5), Window::Dimension(1, 2, 1))),
+                                                                                 framework::dataset::make("Start", { 0, 1, 3, 2, 4 })),
+                                                                         framework::dataset::make("End", { 0, 2, 5, 8, 7 })),
+                                                                     framework::dataset::make("RowSize",
+{
+    create_vector({ 4 }),
+    create_vector({ 8, 8 }),
+    create_vector({ 4, 8, 8 }),
+    create_vector({ 8, 8, 16, 16, 16, 16, 4 }),
+    create_vector({ 16, 16, 16, 16 }),
+})),
+framework::dataset::make("Expected", { create_vector({ Coordinates(4, 3, 1) }), create_vector({ Coordinates(8, 3, 1), Coordinates(12, 3, 1) }), create_vector({ Coordinates(16, 3, 1), Coordinates(4, 8, 1), Coordinates(8, 8, 1) }), create_vector({ Coordinates(12, 3, 1), Coordinates(16, 3, 1), Coordinates(4, 8, 1), Coordinates(8, 8, 1), Coordinates(12, 8, 1), Coordinates(16, 8, 1), Coordinates(4, 13, 1) }), create_vector({ Coordinates(4, 8, 1), Coordinates(8, 8, 1), Coordinates(12, 8, 1), Coordinates(16, 8, 1) }) })),
+window, start, end, expected_row_size, expected)
+{
+    unsigned int i            = 0;
+    int          row_size     = 0;
+    TensorShape  window_shape = window.shape();
+    Coordinates  start_offset = index2coords(window_shape, start);
+    Coordinates  end_offset   = index2coords(window_shape, end);
+    auto window_iterator      = create_window_iterator(window, start_offset, end_offset, [&](const Coordinates & id)
+    {
+        ARM_COMPUTE_ASSERT(i < expected.size());
+        ARM_COMPUTE_EXPECT_EQUAL(expected_row_size[i], row_size, framework::LogLevel::ERRORS);
+        Coordinates expected_coords = expected[i++];
+        //Set number of dimensions to the maximum (To match the number of dimensions used by the id passed to the lambda function)
+        expected_coords.set_num_dimensions(Coordinates::num_max_dimensions);
+        ARM_COMPUTE_EXPECT_EQUAL(id, expected_coords, framework::LogLevel::ERRORS);
+    });
+    window_iterator.iterate_3D([&](int start, int end)
+    {
+        ARM_COMPUTE_EXPECT(start >= window[0].start(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(end <= window[0].end(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(end > start, framework::LogLevel::ERRORS);
+        row_size = end - start;
+    });
+    ARM_COMPUTE_EXPECT_EQUAL(i, expected.size(), framework::LogLevel::ERRORS);
+}
+
+TEST_SUITE_END()
+TEST_SUITE_END()