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# make_grid

torchvision.utils.make_grid(tensor: Union[Tensor, List[Tensor]], nrow: int = 8, padding: int = 2, normalize: bool = False, value_range: Optional[Tuple[int, int]] = None, scale_each: bool = False, pad_value: float = 0.0) → Tensor

  Make a grid of images.

  Parameters:

    - tensor (Tensor or list) – 4D mini-batch Tensor of shape (B x C x H x W) or a list of images all of the same size.

    - nrow (int, optional) – Number of images displayed in each row of the grid. The final grid size is `(B / nrow, nrow)`. Default: `8`.

    - padding (int, optional) – amount of padding. Default: `2`.

    - normalize (bool, optional) – If True, shift the image to the range (0, 1), by the min and max values specified by `value_range`. Default: `False`.

    - value_range (tuple, optional) – tuple (min, max) where min and max are numbers, then these numbers are used to normalize the image. By default, min and max are computed from the tensor.

    - scale_each (bool, optional) – If `True`, scale each image in the batch of images separately rather than the (min, max) over all images. Default: `False`.

    - pad_value (float, optional) – Value for the padded pixels. Default: `0`.

  Returns:

    the tensor containing grid of images.

  Return type:

    grid (Tensor)

  Examples using `make_grid`:

  Visualization utilities

  Visualization utilities

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