ngraph.tensor_iterator(inputs: List[_pyngraph.Node], graph_body: ngraph.utils.tensor_iterator_types.GraphBody, slice_input_desc: List[ngraph.utils.tensor_iterator_types.TensorIteratorSliceInputDesc], merged_input_desc: List[ngraph.utils.tensor_iterator_types.TensorIteratorMergedInputDesc], invariant_input_desc: List[ngraph.utils.tensor_iterator_types.TensorIteratorInvariantInputDesc], body_output_desc: List[ngraph.utils.tensor_iterator_types.TensorIteratorBodyOutputDesc], concat_output_desc: List[ngraph.utils.tensor_iterator_types.TensorIteratorConcatOutputDesc], name: Optional[str] = None) _pyngraph.Node

Perform recurrent execution of the network described in the body, iterating through the data.

  • inputs – The provided to TensorIterator operator.

  • graph_body – The graph representing the body we execute.

  • slice_input_desc – The descriptors describing sliced inputs, that is nodes representing tensors we iterate through, processing single data slice in one iteration.

  • merged_input_desc – The descriptors describing merged inputs, that is nodes representing variables with initial value at first iteration, which may be changing through iterations.

  • invariant_input_desc – The descriptors describing invariant inputs, that is nodes representing variable with persistent value through all iterations.

  • body_output_desc – The descriptors describing body outputs from specified iteration.

  • concat_output_desc – The descriptors describing specified output values through all the iterations concatenated into one node.

  • name – The optional name for output node.


Node representing TensorIterator operation.