Trying to use jit.trace, results in 'AttributeError: 'FaceAlignment' object has no attribute '__name__' error

jit
1

Hello everyone,
I’m trying to have weight caching , but on one of my models it fails . for caching I’m simply running this snippet :

fname = 'cached_weights_s3fd.pt'
test_imgs = Detector.gen_fake_img(batch=1)
traced = torch.jit.trace(self.detector, test_imgs, check_trace=False)
script = traced.save(fname)
self.detector = torch.jit.load(fname)

and the full stacktrace is as follows:

Traceback (most recent call last):
  File "d:\Codes\Pytorch_Retinaface\detection_core\main_detector.py", line 2074, in <module>
    run_test()
  File "d:\Codes\Pytorch_Retinaface\detection_core\main_detector.py", line 2065, in run_test
    run_capture_sfd()
  File "d:\Codes\Pytorch_Retinaface\detection_core\main_detector.py", line 2002, in run_capture_sfd
    after_detection_fn=None)
  File "Pytorch\detection_core\main_detector.py", line 1523, in __init__
    self._init()
  File "Pytorch\detection_core\main_detector.py", line 1536, in _init
    traced = torch.jit.trace(self.detector, test_imgs, check_trace=False)
  File "C:\Users\User\Anaconda3\lib\site-packages\torch\jit\__init__.py", line 911, in trace
    name = _qualified_name(func)
  File "C:\Users\User\Anaconda3\lib\site-packages\torch\_jit_internal.py", line 683, in _qualified_name
    name = obj.__name__
AttributeError: 'FaceAlignment' object has no attribute '__name__'

Whats wrong?
As far as I know all classes has __name__ attribute, including the mentioned class in the error.(the name is ‘FaceAlignment’ obviously)
So I’m not sure why I’m getting this. Any help is greatly appreciated.

2

Upon further investigations, I turns out in \torch\_jit_internal.py", line 684, the object that is causing the error is

Object is type: <class 'function'> and the object itself is : <function LSTM.forward at 0x00000214C495D048>

The Irony is, I do not have any LSTM cell in my model!
What am I seeing this?

3

Thanks for doing some investigation! Are you able to share the binary for cached_weights_s3fd.pt so we can try to debug this on our end?

I think what you’re seeing here is some initialization the jit does when you first call torch.jit.script or torch.jit.trace. We have to grab the qualified names for a few modules that have overloaded forward methods (only nn.LSTM and nn.GRU), which is what you’re seeing. You could try setting a breakpoint and skipping past these calls to get to the time it’s actually invoked with your class.

4

The cached weights are not generated, it fails before that.
You can replicate the issue by cloning this repo : GitHub - 1adrianb/face-alignment: 🔥 2D and 3D Face alignment library build using pytorch
and running this snippet :

import face_alignment
import torch
import torchvision as tv

def gen_fake_img(samples=1000, batch=10, image_size=(3, 224, 224), num_classes=2):
        fake_dt = tv.datasets.FakeData(samples,
                             image_size, num_classes,
                             tv.transforms.ToTensor())
        dt_ldr = torch.utils.data.DataLoader(fake_dt, batch, pin_memory=True)
        sample_imgs, _ = next(iter(dt_ldr))
        return sample_imgs

detector = face_alignment.FaceAlignment(face_alignment.LandmarksType._2D, device='cpu')

fname = 'cached_weights_s3fd.pt'
test_imgs = gen_fake_img(batch=1)
traced = torch.jit.trace(detector, test_imgs, check_trace=False)
script = traced.save(fname)
detector = torch.jit.load(fname)

fa.get_landmarks('test/assets/aflw-test.jpg')
5

Found the casue, I was sending the wrong model!
its all fixed and fine now!

1 Like
6

Hi @Shisho_Sama ,
I am also having the same error.
I used the same github repo.

What changes did you make in the code to make it up and running
?

I used the below code.

import torch
import torchvision
import face_alignment

Optionally set detector and some additional detector parameters

face_detector = ‘sfd’
face_detector_kwargs = {
“filter_threshold” : 0.8
}

model = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, device=‘cpu’, flip_input=True,face_detector=face_detector)

example = io.imread(’/test/assets/aflw-test.jpg’)
traced_script_module = torch.jit.trace(model,example)
traced_script_module.save(“traced_facealignment_model.pt”)