openvino.runtime.opset4.strided_slice

openvino.runtime.opset4.strided_slice(data: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], begin: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], end: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], strides: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], begin_mask: List[int], end_mask: List[int], new_axis_mask: Optional[List[int]] = None, shrink_axis_mask: Optional[List[int]] = None, ellipsis_mask: Optional[List[int]] = None, name: Optional[str] = None) → openvino._pyopenvino.Node

Return a node which dynamically repeats(replicates) the input data tensor.

Parameters

• data – The tensor to be sliced

• begin – 1D tensor with begin indexes for input blob slicing

• end – 1D tensor with end indexes for input blob slicing

• strides – The slicing strides

• begin_mask – A mask applied to the ‘begin’ input indicating which elements shoud be ignored

• end_mask – A mask applied to the ‘end’ input indicating which elements shoud be ignored

• new_axis_mask – A mask indicating dimensions where ‘1’ should be inserted

• shrink_axis_mask – A mask indicating which dimensions should be deleted

• ellipsis_mask – Indicates positions where missing dimensions should be inserted

Returns

StridedSlice node