Port DepthwiseConvolution to new API

Resolves: COMPMID-4185

Change-Id: Ib5f22356356a022d567bb18d44ea272b62d10ebf
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5424
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

2 files changed, 19 insertions, 9 deletions

diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index 53333ff608..b1f340d18e 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -1861,6 +1861,19 @@ private:
     bool _broadcast_bias;
 };
 
+struct ConvolutionInfo
+{
+    ConvolutionInfo() = default;
+    ConvolutionInfo(const PadStrideInfo &pad_stride_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation)
+        : pad_stride_info(pad_stride_info), depth_multiplier(depth_multiplier), act_info(act_info), dilation(dilation)
+    {
+    }
+    PadStrideInfo       pad_stride_info{};        /**< Convolution info (Pads, strides,...) */
+    unsigned int        depth_multiplier{ 1 };    /**< Multiplier to apply to input's depth to retrieve the output depth. Defaults to 1 */
+    ActivationLayerInfo act_info{};               /**< Fused activation to apply after convolution. */
+    Size2D              dilation{ Size2D(1, 1) }; /**< Dilation, in elements, across x and y. Defaults to (1, 1). */
+};
+
 struct DepthwiseConvolutionReshapeInfo
 {
     unsigned int c0{ 1 };            /**< Number of channels processed by the depth-wise convolution */
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 56038dd853..ba37f9a61e 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -435,16 +435,13 @@ inline TensorShape compute_transposed_shape(const ITensorInfo &input)
 
 /** Calculate the depthwise convolution output shape of a tensor
  *
- * @param[in] input            Input tensor info
- * @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).
+ * @param[in] input   Input tensor info
+ * @param[in] weights Weights tensor info
+ * @param[in] info    Convolution info
  *
  * @return the calculated shape
  */
-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))
+inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, const ConvolutionInfo &info)
 {
     const TensorShape input_shape{ input.tensor_shape() };
     const TensorShape weights_shape{ weights.tensor_shape() };
@@ -462,12 +459,12 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input,
     unsigned int output_height = 0;
     std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx],
                                                               weights_shape[weights_width_idx], weights_shape[weights_height_idx],
-                                                              conv_info, dilation);
+                                                              info.pad_stride_info, info.dilation);
 
     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);
+    output_shape.set(channel_idx, input_shape[channel_idx] * info.depth_multiplier);
 
     return output_shape;
 }