def imshow(inp, title=None):
    """Display image for Tensor."""
    inp = inp.numpy().transpose((1, 2, 0))
    mean = np.array([0.485, 0.456, 0.406])
    std = np.array([0.229, 0.224, 0.225])
    inp = std * inp + mean
    inp = np.clip(inp, 0, 1)
    plt.imshow(inp)
    if title is not None:
        plt.title(title)
    plt.pause(0.001)  # pause a bit so that plots are updated


# Get a batch of training data
[inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"), [classes](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = next(iter(dataloaders['train']))

# Make a grid from batch
[out](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor") = [torchvision.utils.make_grid](https://docs.pytorch.org/vision/stable/generated/torchvision.utils.make_grid.html#torchvision.utils.make_grid "torchvision.utils.make_grid")([inputs](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"))

imshow([out](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor"), title=[class_names[x] for x in [classes](https://docs.pytorch.org/docs/stable/tensors.html#torch.Tensor "torch.Tensor")])