How can I generate and display a grid of images in PyTorch with plt.imshow and torchvision.utils.make_grid?

There's a small mistake in your code. For example, the below code works fine:

In [107]: import torchvision

# sample input (10 RGB images containing just Gaussian Noise)
In [108]: batch_tensor = torch.randn(*(10, 3, 256, 256))   # (N, C, H, W)

# make grid (2 rows and 5 columns) to display our 10 images
In [109]: grid_img = torchvision.utils.make_grid(batch_tensor, nrow=5)

# check shape
In [110]: grid_img.shape
Out[110]: torch.Size([3, 518, 1292])

# reshape and plot (because MPL needs channel as the last dimension)
In [111]: plt.imshow(grid_img.permute(1, 2, 0))
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
Out[111]: <matplotlib.image.AxesImage at 0x7f62081ef080>

which shows the output as:

You have to convert to numpy first

import numpy as np

def show(img):
    npimg = img.numpy()
    plt.imshow(np.transpose(npimg, (1,2,0)), interpolation='nearest')

w = torch.randn(10,3,640,640)
grid = torchvision.utils.make_grid(w, nrow=10, padding=100)
show(grid)