Adds Conv3d reference implementation support.

Expands the interface with the following items:
- Size3D Class.
- Conv3dInfo Struct.
- Padding3D Struct.
- Add 'NDHWC' to supported Tensor Data Layouts.
- Add function to compute expected size of Conv3d.

Resolves COMPMID-4658 & COMPMID-4657

Signed-off-by: Adnan AlSinan <adnan.alsinan@arm.com>
Change-Id: Ic7452c48461eedaa38eaf3ac458f54b031e7dfa8
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6187
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 66 insertions, 0 deletions

diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index d0dc202f91..f18f5b7a42 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -28,6 +28,7 @@
 #include "arm_compute/core/ITensorInfo.h"
 #include "arm_compute/core/KernelDescriptors.h"
 #include "arm_compute/core/Utils.h"
+#include "arm_compute/runtime/FunctionDescriptors.h"
 
 #include "arm_compute/core/utils/helpers/tensor_transform.h"
 
@@ -1383,6 +1384,71 @@ inline TensorShape compute_stack_shape(const ITensorInfo &a, unsigned int axis,
     return shape_out;
 }
 
+/** Calculate the output shape of 3d Convolution
+ *
+ * @param[in] src         Input tensor shape
+ * @param[in] weights     Weights tensor shape
+ * @param[in] conv3d_info 3d Convolution Parameters object
+ *
+ * @return the calculated shape
+ */
+inline TensorShape compute_conv3d_shape(const TensorShape &src, const TensorShape &weights, const Conv3dInfo &conv3d_info)
+{
+    // Weight tensor shape indices (D H W Cin Cout)
+    constexpr unsigned int weights_depth_dim  = 4u;
+    constexpr unsigned int weights_height_dim = 3u;
+    constexpr unsigned int weights_width_dim  = 2u;
+    constexpr unsigned int weights_CHout_dim  = 0u;
+
+    // Source/Destination Tensor shape indices (N D H W C)
+    constexpr unsigned int batch_dim   = 4u;
+    constexpr unsigned int depth_dim   = 3u;
+    constexpr unsigned int height_dim  = 2u;
+    constexpr unsigned int width_dim   = 1u;
+    constexpr unsigned int channel_dim = 0u;
+
+    TensorShape  output_shape{ src };
+    const size_t pad_left   = conv3d_info.padding.left;
+    const size_t pad_right  = conv3d_info.padding.right;
+    const size_t pad_top    = conv3d_info.padding.top;
+    const size_t pad_bottom = conv3d_info.padding.bottom;
+    const size_t pad_front  = conv3d_info.padding.front;
+    const size_t pad_back   = conv3d_info.padding.back;
+    const size_t dilation_x = conv3d_info.dilation.width;
+    const size_t dilation_y = conv3d_info.dilation.height;
+    const size_t dilation_z = conv3d_info.dilation.depth;
+    const size_t stride_x   = conv3d_info.stride.x();
+    const size_t stride_y   = conv3d_info.stride.y();
+    const size_t stride_z   = conv3d_info.stride.z();
+
+    int output_width_size  = 0;
+    int output_height_size = 0;
+    int output_depth_size  = 0;
+
+    switch(conv3d_info.round_type)
+    {
+        case DimensionRoundingType::FLOOR:
+            output_width_size  = static_cast<int>(std::floor((static_cast<float>(src[width_dim] + pad_left + pad_right - (dilation_x * (weights[weights_width_dim] - 1) + 1)) / stride_x) + 1));
+            output_height_size = static_cast<int>(std::floor((static_cast<float>(src[height_dim] + pad_top + pad_bottom - (dilation_y * (weights[weights_height_dim] - 1) + 1)) / stride_y) + 1));
+            output_depth_size  = static_cast<int>(std::floor((static_cast<float>(src[depth_dim] + pad_front + pad_back - (dilation_z * (weights[weights_depth_dim] - 1) + 1)) / stride_z) + 1));
+            break;
+        case DimensionRoundingType::CEIL:
+            output_width_size  = static_cast<int>(std::ceil((static_cast<float>(src[width_dim] + pad_left + pad_right - (dilation_x * (weights[weights_width_dim] - 1) + 1)) / stride_x) + 1));
+            output_height_size = static_cast<int>(std::ceil((static_cast<float>(src[height_dim] + pad_top + pad_bottom - (dilation_y * (weights[weights_height_dim] - 1) + 1)) / stride_y) + 1));
+            output_depth_size  = static_cast<int>(std::ceil((static_cast<float>(src[depth_dim] + pad_front + pad_back - (dilation_z * (weights[weights_depth_dim] - 1) + 1)) / stride_z) + 1));
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Unsupported rounding type");
+    }
+
+    output_shape.set(batch_dim, src[batch_dim]);
+    output_shape.set(width_dim, output_width_size);
+    output_shape.set(height_dim, output_height_size);
+    output_shape.set(depth_dim, output_depth_size);
+    output_shape.set(channel_dim, weights[weights_CHout_dim]);
+    return output_shape;
+}
+
 inline TensorShape compute_gather_shape(const TensorShape &input_shape, const TensorShape &indices_shape, uint32_t actual_axis)
 {
     ARM_COMPUTE_ERROR_ON(indices_shape.num_dimensions() > 1);