laion-ai / clip-based-nsfw-detector Goto Github PK

class SafetyClassifier:
    def __init__(self, model_cache_dir=None):
        self.model = self.load_safety_model(cache_folder=model_cache_dir)

    def load_safety_model(self, cache_folder=None):
        if cache_folder is None:
            home = expanduser("~")
            cache_folder = home + "/.cache/clip_retrieval"
        model_dir = cache_folder + "/clip_autokeras_binary_nsfw"
        if not os.path.exists(model_dir):
            os.makedirs(cache_folder, exist_ok=True)
            path_to_zip_file = cache_folder + "/clip_autokeras_binary_nsfw.zip"
            url_model = (
                "https://raw.githubusercontent.com/LAION-AI/CLIP-based-NSFW-Detector/main/clip_autokeras_binary_nsfw.zip"
            )
            urlretrieve(url_model, path_to_zip_file)
            with zipfile.ZipFile(path_to_zip_file, "r") as zip_ref:
                zip_ref.extractall(cache_folder)

        loaded_model = load_model(model_dir, custom_objects=ak.CUSTOM_OBJECTS)
        # print(loaded_model.predict(np.random.rand(10**3, 768).astype("float32"), batch_size=10**3))
        return loaded_model
    
    def __call__(self, clip_embs):
        if isinstance(clip_embs, torch.Tensor):
            clip_embs = clip_embs.cpu().numpy()
        return self.model.predict_on_batch(clip_embs)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-2-969c26cf53fe>](https://localhost:8080/#) in <module>
     39     return loaded_model
     40 
---> 41 safety_model = load_safety_model()
     42 
     43 

2 frames
[<ipython-input-2-969c26cf53fe>](https://localhost:8080/#) in load_safety_model(clip_model)
     35             zip_ref.extractall(cache_folder)
     36 
---> 37     loaded_model = load_model(model_dir, custom_objects=ak.CUSTOM_OBJECTS)
     38 
     39     return loaded_model

[/usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py](https://localhost:8080/#) in error_handler(*args, **kwargs)
     68             # To get the full stack trace, call:
     69             # `tf.debugging.disable_traceback_filtering()`
---> 70             raise e.with_traceback(filtered_tb) from None
     71         finally:
     72             del filtered_tb

[/usr/local/lib/python3.8/dist-packages/keras/saving/legacy/serialization.py](https://localhost:8080/#) in class_and_config_for_serialized_keras_object(config, module_objects, custom_objects, printable_module_name)
    383     )
    384     if cls is None:
--> 385         raise ValueError(
    386             f"Unknown {printable_module_name}: '{class_name}'. "
    387             "Please ensure you are using a `keras.utils.custom_object_scope` "

ValueError: Unknown optimizer: 'Custom>AdamWeightDecay'. Please ensure you are using a `keras.utils.custom_object_scope` and that this object is included in the scope. See https://www.tensorflow.org/guide/keras/save_and_serialize#registering_the_custom_object for details.