AttributeError: 'Tensor' object has no attribute 'RandomCrop'

vision
1

I am trying to perform random cropping on an image. Here is my code. I tried following the examples given over here but got stuck.

import numpy as np
from sklearn.datasets import load_sample_images
import matplotlib.pyplot as plt
import torch
import torch.nn as nn

def random_crop(imgs, out=84):


    imgs = torch.tensor(84)
    transforms = torch.nn.Sequential(
        imgs.RandomCrop(84),
    )
    imgs = transforms.numpy()
    return imgs
    
dataset = load_sample_images()
first_img_data = dataset.images[0]
first_img_data  = first_img_data.reshape(-1, 427, 640)
first_img_data = first_img_data[1, :, :]
foo = random_crop(first_img_data.reshape(-1,1,427, 640), out=84)
2

Figured it out -

import numpy as np
from sklearn.datasets import load_sample_images
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torchvision.transforms as transforms

def random_crop(imgs, out=84):


    imgs = torch.tensor(imgs)
    change = torch.nn.Sequential(
        transforms.RandomCrop(84)
    )
    imgs = change(imgs).numpy()
    return imgs

dataset = load_sample_images()
first_img_data = dataset.images[0]
first_img_data  = first_img_data.reshape(-1, 427, 640)
first_img_data = first_img_data[1, :, :]
foo = random_crop(first_img_data.reshape(-1,1,427, 640), out=84)
plt.imshow(np.squeeze(foo))
plt.show()