COMPMID-2047: Add support for dilation in CLDepthwiseConvolution.

Change-Id: I3106aa34bd168985a56791613d95072756be6e9b
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/958
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 8 insertions, 34 deletions

diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 26b337d5c5..b46b1b2535 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -402,10 +402,12 @@ inline TensorShape compute_transposed_shape(const ITensorInfo &input)
  * @param[in] weights          Weights tensor info
  * @param[in] conv_info        Padding and stride information to use for the convolution.
  * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth.
+ * @param[in] dilation         Dilation, in elements, across x and y. Defaults to (1, 1).
  *
  * @return the calculated shape
  */
-inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info, unsigned int depth_multiplier)
+inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info, unsigned int depth_multiplier, const Size2D &dilation = Size2D(1U,
+                                                       1U))
 {
     const TensorShape input_shape{ input.tensor_shape() };
     const TensorShape weights_shape{ weights.tensor_shape() };
@@ -415,43 +417,15 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input,
     const int        height_idx  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
     const int        channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
 
-    unsigned int output_width  = 0;
-    unsigned int output_height = 0;
-    std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx],
-                                                              weights_shape[width_idx], weights_shape[height_idx],
-                                                              conv_info);
-
-    TensorShape output_shape{ input_shape };
-    output_shape.set(width_idx, output_width);
-    output_shape.set(height_idx, output_height);
-    output_shape.set(channel_idx, input_shape[channel_idx] * depth_multiplier);
-
-    return output_shape;
-}
-
-/** Calculate the depthwise convolution output shape of a tensor
- *
- * @param[in] input            Input tensor info
- * @param[in] weights_width    Weights width
- * @param[in] weights_height   Weights height
- * @param[in] conv_info        Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth.
- *
- * @return the calculated shape
- */
-inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, int weights_width, int weights_height, PadStrideInfo conv_info, unsigned int depth_multiplier)
-{
-    const TensorShape input_shape{ input.tensor_shape() };
-
-    const DataLayout data_layout = input.data_layout();
-    const int        width_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
-    const int        height_idx  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
-    const int        channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+    const DataLayout weights_data_layout = weights.data_layout();
+    const int        weights_width_idx   = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::WIDTH);
+    const int        weights_height_idx  = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::HEIGHT);
 
     unsigned int output_width  = 0;
     unsigned int output_height = 0;
     std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx],
-                                                              weights_width, weights_width, conv_info);
+                                                              weights_shape[weights_width_idx], weights_shape[weights_height_idx],
+                                                              conv_info, dilation);
 
     TensorShape output_shape{ input_shape };
     output_shape.set(width_idx, output_width);