Functions
Node	batch_to_space (NodeInput data, NodeInput block_shape, NodeInput crops_begin, NodeInput crops_end, Optional[str] name=None)
	Perform BatchToSpace operation on the input tensor. More...

Node	gelu (NodeInput node, Optional[str] name=None)
	Perform Gaussian Error Linear Unit operation element-wise on data from input node. More...

Node	mvn (Node data, bool across_channels=False, bool normalize_variance=False, float eps=1e-9, str name=None)
	Perform Mean Variance Normalization operation on data from input node. More...

Node	reorg_yolo (Node input, List[int] stride, Optional[str] name=None)
	Return a node which produces the ReorgYolo operation. More...

Node	roi_pooling (NodeInput input, NodeInput coords, TensorShape output_size, NumericData spatial_scale, str method, Optional[str] name=None)
	Return a node which produces an ROIPooling operation. More...

Node	space_to_batch (NodeInput data, NodeInput block_shape, NodeInput pads_begin, NodeInput pads_end, Optional[str] name=None)
	Perform SpaceToBatch operation on the input tensor. More...

Function Documentation

◆ batch_to_space()

Node ngraph.opset2.ops.batch_to_space	(	NodeInput	data,
		NodeInput	block_shape,
		NodeInput	crops_begin,
		NodeInput	crops_end,
		Optional[str]	name = `None`
	)

Perform BatchToSpace operation on the input tensor.

BatchToSpace permutes data from the batch dimension of the data tensor into spatial dimensions.

@param data: Node producing the data tensor.
@param block_shape: The sizes of the block of values to be moved.
@param crops_begin: Specifies the amount to crop from the beginning along each axis of `data`.
@param crops_end: Specifies the amount to crop from the end along each axis of `data`.
@param name: Optional output node name.
@return The new node performing a BatchToSpace operation.

◆ gelu()

Node ngraph.opset2.ops.gelu	(	NodeInput	node,
		Optional[str]	name = `None`
	)

Perform Gaussian Error Linear Unit operation element-wise on data from input node.

Computes GELU function:

\f[ f(x) = 0.5\cdot x\cdot(1 + erf( \dfrac{x}{\sqrt{2}}) \f]

For more information refer to [Gaussian Error Linear Unit (GELU)](https://arxiv.org/pdf/1606.08415.pdf>)

@param node: Input tensor. One of: input node, array or scalar.
@param name: Optional output node name.
@return The new node performing a GELU operation on its input data element-wise.

◆ mvn()

Node ngraph.opset2.ops.mvn	(	Node	data,
		bool	across_channels = `False`,
		bool	normalize_variance = `False`,
		float	eps = `1e-9`,
		str	name = `None`
	)

Perform Mean Variance Normalization operation on data from input node.

Computes MVN on the input tensor `data` (called `X`) using formula:

\f[ Y = \dfrac{X-EX}{\sqrt{E(X-EX)^2}} \f]

@param data: The node with data tensor.
@param across_channels: Denotes if mean values are shared across channels.
@param normalize_variance: Denotes whether to perform variance normalization.
@param eps: The number added to the variance to avoid division by zero
           when normalizing the value. Scalar value.
@param name: Optional output node name.
@return The new node performing a MVN operation on input tensor.

◆ reorg_yolo()

Node ngraph.opset2.ops.reorg_yolo	(	Node	input,
		List[int]	stride,
		Optional[str]	name = `None`
	)

Return a node which produces the ReorgYolo operation.

@param input:   Input data
@param stride:  Stride to reorganize input by
@param name:    Optional name for output node.
@return ReorgYolo node

◆ roi_pooling()

Node ngraph.opset2.ops.roi_pooling	(	NodeInput	input,
		NodeInput	coords,
		TensorShape	output_size,
		NumericData	spatial_scale,
		str	method,
		Optional[str]	name = `None`
	)

Return a node which produces an ROIPooling operation.

@param input:          Input feature map {N, C, ...}
@param coords:         Coordinates of bounding boxes
@param output_size:    Height/Width of ROI output features (shape)
@param spatial_scale:  Ratio of input feature map over input image size (float)
@param method:         Method of pooling - string: "max" or "bilinear"
@return               ROIPooling node

◆ space_to_batch()

Node ngraph.opset2.ops.space_to_batch	(	NodeInput	data,
		NodeInput	block_shape,
		NodeInput	pads_begin,
		NodeInput	pads_end,
		Optional[str]	name = `None`
	)

Perform SpaceToBatch operation on the input tensor.

SpaceToBatch permutes data tensor blocks of spatial data into batch dimension.
The operator returns a copy of the input tensor where values from spatial blocks dimensions
are moved in the batch dimension

@param data: Node producing the data tensor.
@param block_shape: The sizes of the block of values to be moved.
@param pads_begin: Specifies the padding for the beginning along each axis of `data`.
@param pads_end: Specifies the padding for the ending along each axis of `data`.
@param name: Optional output node name.
@return The new node performing a SpaceToBatch operation.