From e4563a032aaa71de5efdb83fc04ff2933338e02d Mon Sep 17 00:00:00 2001 From: Adnan AlSinan Date: Wed, 1 Sep 2021 15:32:03 +0100 Subject: 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 Change-Id: Ic7452c48461eedaa38eaf3ac458f54b031e7dfa8 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6187 Reviewed-by: Giorgio Arena Reviewed-by: Gian Marco Iodice Tested-by: Arm Jenkins --- arm_compute/core/utils/misc/ShapeCalculator.h | 66 +++++++++++++++++++++++++++ 1 file changed, 66 insertions(+) (limited to 'arm_compute/core/utils') 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(std::floor((static_cast(src[width_dim] + pad_left + pad_right - (dilation_x * (weights[weights_width_dim] - 1) + 1)) / stride_x) + 1)); + output_height_size = static_cast(std::floor((static_cast(src[height_dim] + pad_top + pad_bottom - (dilation_y * (weights[weights_height_dim] - 1) + 1)) / stride_y) + 1)); + output_depth_size = static_cast(std::floor((static_cast(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(std::ceil((static_cast(src[width_dim] + pad_left + pad_right - (dilation_x * (weights[weights_width_dim] - 1) + 1)) / stride_x) + 1)); + output_height_size = static_cast(std::ceil((static_cast(src[height_dim] + pad_top + pad_bottom - (dilation_y * (weights[weights_height_dim] - 1) + 1)) / stride_y) + 1)); + output_depth_size = static_cast(std::ceil((static_cast(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); -- cgit v1.2.1