class torchvision.transforms.v2.Pad(padding: Union[int, Sequence[int]], fill: Union[int, float, Sequence[int], Sequence[float], None, Dict[Union[Type, str], Optional[Union[int, float, Sequence[int], Sequence[float]]]]] = 0, padding_mode: Literal['constant', 'edge', 'reflect', 'symmetric'] = 'constant')[source]

Pad the input on all sides with the given “pad” value.

If the input is a torch.Tensor or a TVTensor (e.g. Image, Video, BoundingBoxes etc.) it can have arbitrary number of leading batch dimensions. For example, the image can have [..., C, H, W] shape. A bounding box can have [..., 4] shape.

  • padding (int or sequence) –

    Padding on each border. If a single int is provided this is used to pad all borders. If sequence of length 2 is provided this is the padding on left/right and top/bottom respectively. If a sequence of length 4 is provided this is the padding for the left, top, right and bottom borders respectively.


    In torchscript mode padding as single int is not supported, use a sequence of length 1: [padding, ].

  • fill (number or tuple or dict, optional) – Pixel fill value used when the padding_mode is constant. Default is 0. If a tuple of length 3, it is used to fill R, G, B channels respectively. Fill value can be also a dictionary mapping data type to the fill value, e.g. fill={tv_tensors.Image: 127, tv_tensors.Mask: 0} where Image will be filled with 127 and Mask will be filled with 0.

  • padding_mode (str, optional) –

    Type of padding. Should be: constant, edge, reflect or symmetric. Default is “constant”.

    • constant: pads with a constant value, this value is specified with fill

    • edge: pads with the last value at the edge of the image.

    • reflect: pads with reflection of image without repeating the last value on the edge. For example, padding [1, 2, 3, 4] with 2 elements on both sides in reflect mode will result in [3, 2, 1, 2, 3, 4, 3, 2]

    • symmetric: pads with reflection of image repeating the last value on the edge. For example, padding [1, 2, 3, 4] with 2 elements on both sides in symmetric mode will result in [2, 1, 1, 2, 3, 4, 4, 3]

Examples using Pad:

Illustration of transforms

Illustration of transforms


Access comprehensive developer documentation for PyTorch

View Docs


Get in-depth tutorials for beginners and advanced developers

View Tutorials


Find development resources and get your questions answered

View Resources