# 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. |