ngraph.ops

Factory functions for all ngraph ops.

Functions

`absolute`	Return node which applies f(x) = abs(x) to the input node element-wise.
`acos`	Apply inverse cosine function on the input node element-wise.
`add`	Return node which applies f(x) = A+B to the input nodes element-wise.
`argmax`	Return a node which performs ArgMax index reduction operation.
`argmin`	Return a node which performs ArgMin index reduction operation.
`asin`	Apply inverse sine function on the input node element-wise.
`atan`	Apply inverse tangent function on the input node element-wise.
`avg_pool`	Return average pooling node.
`batch_norm`	Return batch normalization node.
`broadcast`	Create a node which broadcasts the input node’s values along specified axes to a desired shape.
`broadcast_to`	Create a node which broadcasts the input node’s values to a desired shape.
`ceiling`	Return node which applies ceiling to the input node element-wise.
`clamp`	Perform clamp element-wise on data from input node.
`concat`	Concatenate input nodes into single new node along specified axis.
`constant`	Create a Constant node from provided value.
`convert`	Return node which casts input node values to specified type.
`convolution`	Return node performing batched convolution operation.
`convolution_backprop_data`	Return node performing a batched-convolution data batch-backprop operation.
`cos`	Apply cosine function on the input node element-wise.
`cosh`	Apply hyperbolic cosine function on the input node element-wise.
`depth_to_space`	Rearranges input tensor from depth into blocks of spatial data.
`divide`	Return node which applies f(x) = A/B to the input nodes element-wise.
`dot`	Return node which performs generalized dot product of two input nodes.
`elu`	Perform Exponential Linear Unit operation element-wise on data from input node.
`equal`	Return node which checks if input nodes are equal element-wise.
`exp`	Return node which applies exp to the input node element-wise.
`fake_quantize`	Perform an element-wise linear quantization on input data.
`floor`	Return node which applies floor to the input node element-wise.
`gelu`	Perform Gaussian Error Linear Unit operation element-wise on data from input node.
`gemm`	Perform General matrix-matrix multiplication on input tensors A, B and C.
`get_output_element`	Return the n-th element of the input tuple.
`greater`	Return node which checks if left input node is greater than the right node element-wise.
`greater_eq`	Return node which checks if left node is greater or equal to the right node element-wise.
`grn`	Perform Global Response Normalization with L2 norm (across channels only).
`hard_sigmoid`	Perform Hard Sigmoid operation element-wise on data from input node.
`less`	Return node which checks if left input node is less than the right node element-wise.
`less_eq`	Return node which checks if left input node is less or equal the right node element-wise.
`log`	Return node which applies natural logarithm to the input node element-wise.
`logical_and`	Return node which perform logical and operation on input nodes element-wise.
`logical_not`	Return node which applies logical negation to the input node elementwise.
`logical_or`	Return node which performs logical or operation on input nodes element-wise.
`lrn`	Return a node which performs element-wise Local Response Normalization (LRN) operation.
`max`	Max-reduction operation on input tensor, eliminating the specified reduction axes.
`max_pool`	Return max pooling node.
`maximum`	Return node which applies the maximum operation to input nodes elementwise.
`min`	Min-reduction operation on input tensor, eliminating the specified reduction axes.
`minimum`	Return node which applies the minimum operation to input nodes elementwise.
`multiply`	Return node which applies f(x) = A*B to the input nodes elementwise.
`mvn`	Perform Mean Variance Normalization operation on data from input node.
`negative`	Return node which applies f(x) = -x to the input node elementwise.
`not_equal`	Return node which checks if input nodes are unequal element-wise.
`one_hot`	Create node performing one-hot encoding on input data.
`pad`	Return padding node.
`parameter`	Return an ngraph Parameter object.
`power`	Return node which perform element-wise exponentiation operation.
`prelu`	Perform Parametrized Relu operation element-wise on data from input node.
`prod`	Product-reduction operation on input tensor, eliminating the specified reduction axes.
`relu`	Perform rectified linear unit operation on input node element-wise.
`replace_slice`	Return a copy of dest_node with the specified slice overwritten by the src_node data.
`reshape`	Return reshaped node according to provided parameters.
`reverse`	Perform axis-reverse operation.
`scale_shift`	Perform ScaleShift transformation on input node.
`select`	Perform an element-wise selection operation on input tensors.
`sign`	Perform element-wise sign operation.
`sin`	Apply sine function on the input node element-wise.
`sinh`	Apply hyperbolic sine function on the input node element-wise.
`slice`	Take a slice of an input tensor, (sub-tensor) that resides within a bounding box.
`softmax`	Apply softmax operation on each element of input tensor.
`space_to_depth`	Perform SpaceToDepth operation on the input tensor.
`sqrt`	Return node which applies square root to the input node element-wise.
`subtract`	Return node which applies f(x) = A-B to the input nodes element-wise.
`sum`	Perform element-wise sums of the input tensor, eliminating the specified reduction axes.
`tan`	Apply tangent function on the input node element-wise.
`tanh`	Return node which applies hyperbolic tangent to the input node element-wise.
`topk`	Return a node which performs TopK.
`unsqueeze`	Perform unsqueeze operation on input tensor.