COMPMID-1235: Implements StridedSlice for CL

Change-Id: If2b44da31fae528c76be742b4b3a21fb0eb06b49
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/145284
Reviewed-by: Giuseppe Rossini <giuseppe.rossini@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

1 files changed, 142 insertions, 0 deletions

diff --git a/src/core/utils/helpers/tensor_transform.cpp b/src/core/utils/helpers/tensor_transform.cpp
new file mode 100644
index 0000000000..5c83a8bdb5
--- /dev/null
+++ b/src/core/utils/helpers/tensor_transform.cpp
@@ -0,0 +1,142 @@
+/*
+ * 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 "arm_compute/core/utils/helpers/tensor_transform.h"
+
+namespace arm_compute
+{
+namespace helpers
+{
+namespace tensor_transform
+{
+Coordinates strided_slice_absolute_start_coords(TensorShape input_shape, Coordinates starts, Coordinates strides, int32_t begin_mask)
+{
+    Coordinates starts_abs;
+    for(unsigned int i = 0; i < starts.num_dimensions(); ++i)
+    {
+        // Get start index
+        int start_i = starts[i];
+
+        // Reset in case of begin mask present
+        if((begin_mask & 1 << i) != 0)
+        {
+            start_i = strides[i] > 0 ? std::numeric_limits<int>::lowest() : std::numeric_limits<int>::max();
+        }
+
+        // Account negative start points
+        const int dim_size = input_shape[i];
+        if(start_i < 0)
+        {
+            start_i += dim_size;
+        }
+
+        // Final clamp
+        start_i = utility::clamp(start_i, 0, dim_size - 1);
+        starts_abs.set(i, start_i);
+    }
+
+    // Fill remaining
+    for(unsigned int i = starts_abs.num_dimensions(); i < input_shape.num_dimensions(); ++i)
+    {
+        starts_abs.set(i, 0);
+    }
+
+    return starts_abs;
+}
+
+Coordinates strided_slice_absolute_end_coords(TensorShape input_shape, Coordinates starts_abs, Coordinates ends, Coordinates strides,
+                                              int32_t end_mask, int32_t shrink_axis_mask)
+{
+    Coordinates ends_abs;
+    for(unsigned int i = 0; i < ends.num_dimensions(); ++i)
+    {
+        // Get end index
+        int stop_i = ends[i];
+
+        // Shrink dimension
+        if((shrink_axis_mask & (1 << i)) != 0)
+        {
+            stop_i = starts_abs[i] + 1;
+        }
+
+        // Reset in case of begin mask present
+        if((end_mask & 1 << i) != 0)
+        {
+            stop_i = (strides[i] > 0) ? std::numeric_limits<int>::max() : std::numeric_limits<int>::lowest();
+        }
+
+        // Account negative end points
+        const int dim_size = input_shape[i];
+        if(stop_i < 0)
+        {
+            stop_i += dim_size;
+        }
+
+        // Final clamp
+        stop_i = (strides[i] > 0) ? utility::clamp(stop_i, 0, dim_size) : utility::clamp(stop_i, -1, dim_size - 1);
+        ends_abs.set(i, stop_i);
+    }
+
+    // Fill remaining ends
+    for(unsigned int i = ends_abs.num_dimensions(); i < input_shape.num_dimensions(); ++i)
+    {
+        ends_abs.set(i, input_shape[i]);
+    }
+
+    return ends_abs;
+}
+
+Coordinates strided_slice_strides(TensorShape input_shape, Coordinates strides)
+{
+    for(unsigned int i = strides.num_dimensions(); i < input_shape.num_dimensions(); ++i)
+    {
+        strides.set(i, 1);
+    }
+    return strides;
+}
+
+TensorShape compute_strided_slice_output_shape(TensorShape input_shape, Coordinates starts_abs, Coordinates ends_abs, Coordinates final_strides)
+{
+    TensorShape output_shape = input_shape;
+    for(unsigned int i = 0; i < input_shape.num_dimensions(); ++i)
+    {
+        const int stride_i = final_strides[i];
+        const int range    = ends_abs[i] - starts_abs[i];
+        if((range == 0) ||                 // Zero range
+           (range < 0 && stride_i >= 0) || // Negative range with positive stride
+           (range > 0 && stride_i <= 0))   // Positive range with negative stride
+        {
+            output_shape.set(i, 0);
+            return output_shape;
+        }
+        else
+        {
+            int dim = range / stride_i + (range % stride_i != 0 ? 1 : 0);
+            output_shape.set(i, dim);
+        }
+    }
+    return output_shape;
+}
+} // namespace tensor_transform
+} // namespace helpers
+} // namespace arm_compute