# Disable gradient computation since we're only doing inference with torch.no_grad(): features = model(input_data)
import torch import torchvision import torchvision.transforms as transforms
# Load a pre-trained model model = torchvision.models.resnet50(pretrained=True)
# Disable gradient computation since we're only doing inference with torch.no_grad(): features = model(input_data)
import torch import torchvision import torchvision.transforms as transforms
# Load a pre-trained model model = torchvision.models.resnet50(pretrained=True)
