composer.algorithms.functional.resize_inputs

composer.algorithms.functional.resize_inputs(X: torch.Tensor, y: torch.Tensor, scale_factor: float, mode: str = 'resize', resize_targets: bool = False) → Tuple[torch.Tensor, torch.Tensor]

Resize inputs and optionally outputs by cropping or interpolating.

Parameters

• X – input tensor of shape (N, C, H, W). Resizing will be done along dimensions H and W using the constant factor scale_factor.

• y – output tensor of shape (N, C, H, W) that will also be resized if resize_targets is True,

• scale_factor – scaling coefficient for the height and width of the input/output tensor. 1.0 keeps the original size.

• mode – type of scaling to perform. Value must be one of 'crop' or 'resize'. 'crop' performs a random crop, whereas 'resize' performs a bilinear interpolation.

• resize_targets – whether to resize the targets, y, as well

Returns

• X_sized – resized input tensor of shape (N, C, H * scale_factor, W * scale_factor).

• y_sized – if resized_targets is True, resized output tensor of shape (N, C, H * scale_factor, W * scale_factor). Otherwise returns original y.