* **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.
