make_grid¶
- torchvision.utils.make_grid(tensor: Union[Tensor, list[torch.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[source]¶
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:
