DeformableConvolution

Versioned name: DeformableConvolution-1

Category: Convolution

Detailed description: Reference

Attributes

• strides
  • Description: strides is a distance (in pixels) to slide the filter on the feature map over the (z, y, x) axes for 3D convolutions and (y, x) axes for 2D convolutions. For example, strides equal 4,2,1 means sliding the filter 4 pixel at a time over depth dimension, 2 over height dimension and 1 over width dimension.
  • Range of values: integer values starting from 0
  • Type: int[]
  • Default value: None
  • Required: yes
• pads_begin
  • Description: pads_begin is a number of pixels to add to the beginning along each axis. For example, pads_begin equal 1,2 means adding 1 pixel to the top of the input and 2 to the left of the input.
  • Range of values: integer values starting from 0
  • Type: int[]
  • Default value: None
  • Required: yes
  • Note: the attribute is ignored when auto_pad attribute is specified.
• pads_end
  • Description: pads_end is a number of pixels to add to the ending along each axis. For example, pads_end equal 1,2 means adding 1 pixel to the bottom of the input and 2 to the right of the input.
  • Range of values: integer values starting from 0
  • Type: int[]
  • Default value: None
  • Required: yes
  • Note: the attribute is ignored when auto_pad attribute is specified.
• dilations
  • Description: dilations denotes the distance in width and height between elements (weights) in the filter. For example, dilation equal 1,1 means that all the elements in the filter are neighbors, so it is the same as for the usual convolution. dilation equal 2,2 means that all the elements in the filter are matched not to adjacent elements in the input matrix, but to those that are adjacent with distance 1.
  • Range of values: integer value starting from 0
  • Type: int[]
  • Default value: None
  • Required: yes
• auto_pad
  • Description: auto_pad how the padding is calculated. Possible values:
    • None (not specified): use explicit padding values.
    • same_upper (same_lower) the input is padded to match the output size. In case of odd padding value an extra padding is added at the end (at the beginning).
    • valid - do not use padding.
  • Type: string
  • Default value: None
  • Required: no
  • Note: pads_begin and pads_end attributes are ignored when auto_pad is specified.
• group
  • Description: group is the number of groups which output and input should be split into. For example, group equal to 1 means that all filters are applied to the whole input (usual convolution), group equal to 2 means that both input and output channels are separated into two groups and the i-th output group is connected to the i-th input group channel. group equal to a number of output feature maps implies depth-wise separable convolution.
  • Range of values: integer value starting from 1
  • Type: int
  • Default value: 1
  • Required: no
• deformable_group
  • Description: deformable_group is the number of groups which deformable values and output should be split into along the channel axis. Apply the deformable convolution using the i-th part of the offset part on the i-th out.
  • Range of values: integer value starting from 1
  • Type: int
  • Default value: 1
  • Required: no

Inputs:

• 1: Input tensor of rank 3 or greater. Required.
• 2: Deformable values tensor of rank 3 or higher. Required.
• 3: Convolution kernel tensor. Weights layout is OIYX (OIZYX for 3D convolution), which means that X is changing the fastest, then Y, then Input then Output. The size of kernel is derived from the shape of this input and not specified by any attribute. Required.

Example

<layer ... type="DeformableConvolution" ... >
        <data dilations="1,1" pads_begin="2,2" pads_end="3,3" strides="2,2"/>
        <input> ... </input>
        <output> ... </output>
</layer>