GridSample

Description

Uses a given input tensor x and an input tensor grid, and pads the specified position in the grid with the value of the corresponding position in x based on the coordinate information provided by each position in the grid to obtain the final output tensor y.

Input

• x: 4D tensor of type float16 or float32, with shape [batch, channels, height_in, width_in]. Discontinuous tensors are supported. The data format is ND.
• grid: 4D tensor of type float16 or float32, with shape [batch, height_out, width_out, 2]. Discontinuous tensors are supported. The data format is ND.

Attribute

• interpolation_mode: string, specifying the optional character string of the interpolation method. The value 0 indicates bilinear interpolation, 1 indicates nearest interpolation, and 2 indicates bicubic interpolation. Currently, only bilinear and nearest are supported. The default value is 0.
• padding_mode: string, specifying the padding mode. When the value of (x, y) exceeds the sampling range of the input feature map, a specific value is returned. The value can be 0 (zeros), 1 (border), or 2 (reflection).
• align_corners: bool. The default value is 0. If the value is true, the corner pixels of the input and output tensors are aligned. The default value is false.

Output

y: 4D tensor with shape [batch, channels, height_out, width_out]. The data type is the same as that of x. Inconsecutive tensors are supported. The data format can be ND and the data type can be float16 or float32.

Constraints

None.

ONNX Opset Support

Opset v16