gistfile1.txt

import torch as th
from torchvision import models, transforms
from PIL import Image
import numpy as np
model = models.resnet18(pretrained=True)


class Identity(th.nn.Module):
    def __init__(self):
        super(Identity, self).__init__()

    def forward(self, x):
        return x

model.fc = Identity()

model = th.jit.script(model)
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])
crop = transforms.CenterCrop(224)

# th.save(model, "/tmp/resnet18-headless.th")

image =  Image.open("/tmp/dog.jpg")
# image_th = th.Tensor(np.asarray(image))
image_th = th.Tensor(np.asarray(crop(image)))
image_th = normalize(image_th)
image_th = image_th.reshape(1,3, 224, 224)

result = model.forward(image_th)
print(result)