group_convolution(data: Union[_pyngraph.Node, int, float, numpy.ndarray], filters: Union[_pyngraph.Node, int, float, numpy.ndarray], strides: List[int], pads_begin: List[int], pads_end: List[int], dilations: List[int], auto_pad: str = 'EXPLICIT', name: Optional[str] = None) → _pyngraph.Node¶
Perform Group Convolution operation on data from input node.
data – The node producing input data.
filters – The node producing filters data.
strides – The distance (in pixels) to slide the filter on the feature map over the axes.
pads_begin – The number of pixels to add at the beginning along each axis.
pads_end – The number of pixels to add at the end along each axis.
dilations – The distance in width and height between elements (weights) in the filter.
auto_pad – Describes how to perform padding. Possible values: EXPLICIT: Pad dimensions are explicity specified SAME_LOWER: Pad dimensions computed to match input shape Ceil(num_dims/2) at the beginning and Floor(num_dims/2) at the end SAME_UPPER: Pad dimensions computed to match input shape Floor(num_dims/2) at the beginning and Ceil(num_dims/2) at the end VALID: No padding
name – Optional output node name.
The new node performing a Group Convolution operation on tensor from input node.