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... | |
Node ngraph.opset2.ops.batch_to_space | ( | NodeInput | data, |
NodeInput | block_shape, | ||
NodeInput | crops_begin, | ||
NodeInput | crops_end, | ||
Optional[str] | name = None |
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) |
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.
Node ngraph.opset2.ops.gelu | ( | NodeInput | node, |
Optional[str] | name = None |
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) |
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.
Node ngraph.opset2.ops.mvn | ( | Node | data, |
bool | across_channels = False , |
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bool | normalize_variance = False , |
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float | eps = 1e-9 , |
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str | name = None |
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) |
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.
Node ngraph.opset2.ops.reorg_yolo | ( | Node | input, |
List[int] | stride, | ||
Optional[str] | name = None |
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) |
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
Node ngraph.opset2.ops.roi_pooling | ( | NodeInput | input, |
NodeInput | coords, | ||
TensorShape | output_size, | ||
NumericData | spatial_scale, | ||
str | method, | ||
Optional[str] | name = None |
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) |
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
Node ngraph.opset2.ops.space_to_batch | ( | NodeInput | data, |
NodeInput | block_shape, | ||
NodeInput | pads_begin, | ||
NodeInput | pads_end, | ||
Optional[str] | name = None |
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) |
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.