I’ve been seeing VERY high CPU utilization when using ToTensor in my transforms and its easily the slowest operation in my transformation compositions.
system:
torch: 1.8.1
torchvision: 0.9.1
been facing the same issue since 1.4.0, even tried building from source (tried 1.6.0 and 1.8.0)
def to_tensor(img): 
        img = np.array(img) 
        img = torch.from_numpy(img).float().permute(2,0,1) 
        img = img / 255.0 
        return img

In [12]: %%timeit 
    ...: to_tensor(img)                                                                                                                                                                                                                                                          
826 us +- 43.3 us per loop (mean +- std. dev. of 7 runs, 1000 loops each)

vs torchvision
    ...: tfunc.to_tensor(img)                                                                                                                                                                                                                                                         
1.49 ms +- 73.5 us per loop (mean +- std. dev. of 7 runs, 1000 loops each)

img is a 512x512 RGB PIL Image.
any particular reason this may be happening?