ngraph.interpolate

ngraph.interpolate(image: Union[_pyngraph.Node, int, float, numpy.ndarray], scales_or_sizes: Union[_pyngraph.Node, int, float, numpy.ndarray], mode: str, shape_calculation_mode: str, pads_begin: Optional[List[int]] = None, pads_end: Optional[List[int]] = None, coordinate_transformation_mode: str = 'half_pixel', nearest_mode: str = 'round_prefer_floor', antialias: bool = False, cube_coeff: float = - 0.75, axes: Optional[Union[_pyngraph.Node, int, float, numpy.ndarray]] = None, name: Optional[str] = None) → _pyngraph.Node

Performs the interpolation of the input tensor.

Parameters

• image – The node providing input tensor with data for interpolation.

• scales_or_sizes – 1D tensor providing information used to calculate the output shape of the operation. It might contain floats (scales) or integers(sizes).

• mode – Specifies type of interpolation. Possible values are: nearest, linear, linear_onnx, cubic, bilinear_pillow, bicubic_pillow.

• shape_calculation_mode – Specifies how the scales_or_sizes input should be interpreted.

• pads_begin – Specifies the number of pixels to add to the beginning of the image being interpolated. Default is None.

• pads_end – Specifies the number of pixels to add to the end of the image being interpolated. Default is None.

• coordinate_transformation_mode – Specifies how to transform the coordinate in the resized tensor to the coordinate in the original tensor. Default is “half_pixel”.

• nearest_mode – Specifies round mode when mode == nearest and is used only when mode == nearest. Default is “round_prefer_floor”.

• antialias – Specifies whether to perform anti-aliasing. Default is False.

• cube_coeff – Specifies the parameter a for cubic interpolation. Default is -0.75.

• axes – 1D tensor specifying dimension indices where interpolation is applied. The default is None.

• name – Optional name for the output node. The default is None.

Returns

Node representing the interpolation operation.