Interpolate
Interpolate#
Versioned name: Interpolate-1
Category: Image processing
Short description: Interpolate layer performs interpolation on input tensor at spatial dimensions.
Attributes
mode
Description: specifies type of interpolation
Range of values: one of
nearest
,linear
,bilinear
,trilinear
Type: string
Default value: none
Required: yes
coordinate_transformation_mode
Description: specifies how to transform the coordinate in the resized tensor to the coordinate in the original tensor
Range of values: name of the transformation mode in string format (here
scale[x]
isoutput_shape[x] / input_shape[x]
andx_resized
is a coordinate in axisx
, for any axisx
from the inputaxes
):half_pixel
- the coordinate in the original tensor axisx
is calculated as((x_resized + 0.5) / scale[x]) - 0.5
.align_corners
- the coordinate in the original tensor axisx
is calculated as0 if output_shape[x] == 1 else x_resized * (input_shape[x] - 1) / (output_shape[x] - 1)
.
Type: string
Default value:
half_pixel
Required: no
sizes
Description: specifies output shape for spatial axes. sizes and scales can’t be valid at the same time. When sizes is used, optional scales should not be set.
Range of values:positive s64
Type: s64[]
Default value: none
Required: no
scales
Description: specifies scales for spatial axes. sizes and scales can’t be valid at the same time. When scales is used, optional size should not be set.
Range of values: f32
Type: f32[]
Default value: none
Required: no
data_format
Description: data_format denotes the data format of the input and output data.
Range of values: NXC or NCX (X means HW for 2D, DHW for 3D)
Type: string
Default value: NXC
Required: no
Inputs
1:
data
- Input tensor with data for interpolation. Required.Type: T1
2:
sizes
- 1D tensor describing output shape for spatial axes. It is a non-differentiable tensor. optional.Type: T2
Outputs
1: Resulting interpolated tensor with elements of the same type as input
data
tensor. The shape of the output matches inputdata
shape except spatial dimensions. For spatial dimensions shape matches sizes fromsizes
or calculated from``scales``.Type: T1
Types:
T1: f32, f16, bf16.
T2: s32.
Note: The input tensor and the result tensor have the same data type denoted by T1. For example, if input is f32 tensor, then result tensor has f32 data type.