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authorPablo Tello <pablo.tello@arm.com>2018-11-22 16:14:36 +0000
committerGeorgios Pinitas <georgios.pinitas@arm.com>2018-12-21 18:28:31 +0000
commit543036904d5324c4738cdc8b586c301471046c8e (patch)
tree680efe9d7d02b23a0453495c13f4ece5d0a0edbd /tests/validation/reference/Unstack.cpp
parent8b6b4a959a49127d64293f8b60265f0f5ed486d4 (diff)
downloadComputeLibrary-543036904d5324c4738cdc8b586c301471046c8e.tar.gz
COMPMID-1726: Implement CLUnstack.
Change-Id: I94b0707d19757c5f5d7ca66d9c47e378867126a3 Reviewed-on: https://review.mlplatform.org/325 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
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+/*
+ * 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.
+ */
+#include "Unstack.h"
+
+#include "tests/validation/Helpers.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+namespace
+{
+inline Coordinates expand_coordinates(Coordinates in_coord, size_t axis, size_t slice, size_t num_dimensions)
+{
+ /*
+ Reconstruct input_coord to read the corresponding value from the correct slice. This is done by adding an extra dimension
+ to the coordinates and shuffling around the values based on the info below.
+
+ For example, if input tensor shape is (X, Y, Z, W);
+
+ If axis == 0, each slice will have the shape (Y, Z, W) and there will be X slices
+
+ If axis == 1, each slice will have the shape (X, Z, W) and there will be Y slices.
+ */
+ Coordinates expanded_coord;
+ expanded_coord.set_num_dimensions(num_dimensions);
+ expanded_coord.set(axis, slice);
+ for(size_t k = 0; k < axis; ++k)
+ {
+ expanded_coord.set(k, in_coord[k]);
+ }
+ for(size_t k = axis + 1; k < num_dimensions; ++k)
+ {
+ expanded_coord.set(k, in_coord[k - 1]);
+ }
+ return expanded_coord;
+}
+
+template <typename T>
+SimpleTensor<T> get_slice(const SimpleTensor<T> &input_tensor, size_t axis, size_t slice)
+{
+ TensorShape out_shape = input_tensor.shape();
+ out_shape.remove_dimension(axis);
+
+ const size_t unpacked_num_dimensions(input_tensor.shape().num_dimensions());
+
+ SimpleTensor<T> output{ out_shape, input_tensor.data_type() };
+
+ Window win;
+ win.use_tensor_dimensions(out_shape);
+ execute_window_loop(win, [&](const Coordinates & id)
+ {
+ const Coordinates input_coords = expand_coordinates(id, axis, slice, unpacked_num_dimensions);
+ *reinterpret_cast<T *>(output(id)) = *reinterpret_cast<const T *>(input_tensor(input_coords));
+ });
+
+ return output;
+}
+} // namespace
+
+template <typename T>
+std::vector<SimpleTensor<T>> unstack(const SimpleTensor<T> &input_tensor, std::vector<SimpleTensor<T>> &output_tensors, int axis)
+{
+ // Wrap around negative values
+ const unsigned int axis_u = wrap_around(axis, static_cast<int>(input_tensor.shape().num_dimensions()));
+ ARM_COMPUTE_ERROR_ON(axis_u >= input_tensor.shape().num_dimensions());
+ for(size_t k = 0; k < output_tensors.size(); ++k)
+ {
+ SimpleTensor<T> &output = output_tensors[k];
+ const SimpleTensor<T> kth_slice = get_slice(input_tensor, axis_u, k);
+ output = copy_tensor<T>(kth_slice);
+ }
+ return output_tensors;
+}
+
+template std::vector<SimpleTensor<float>> unstack(const SimpleTensor<float> &input_tensor, std::vector<SimpleTensor<float>> &output_tensors, int axis);
+template std::vector<SimpleTensor<half>> unstack(const SimpleTensor<half> &input_tensor, std::vector<SimpleTensor<half>> &output_tensors, int axis);
+template std::vector<SimpleTensor<uint8_t>> unstack(const SimpleTensor<uint8_t> &input_tensor, std::vector<SimpleTensor<uint8_t>> &output_tensors, int axis);
+
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute