Found a weird behavior here (bug), any advice?
Common code:
normalize = transforms.Normalize(
   mean=[0.485, 0.456, 0.406],
   std=[0.229, 0.224, 0.225]
)
preprocess = transforms.Compose([
   transforms.Resize(256),
   transforms.CenterCrop(224),
   transforms.ToTensor(),
   normalize
   # transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
])

resnet_model = torchvision.models.resnet50(pretrained=True, num_classes=1000)
resnet_model.eval()

for i in range(4):
    # An instance of your model.
    img_pil = Image.open("/home/alejandro/workspace/uav_detection/images/" + str(i + 1) + ".jpg")
    # img_pil.show()
    img_tensor = preprocess(img_pil).float()
    img_tensor = img_tensor.unsqueeze_(0)

    fc_out = resnet_model(Variable(img_tensor))

    output = fc_out.detach().numpy()
    print(output.argmax())

Results with:
Python 2.7 Anaconda and pytorch 1.0.0a0+37627a1 (built from source):
918
918
918
918

Python 2.7 Anaconda and pytorch 0.4.1.post2 (downloaded with pip):
834
208
285
478