I just rebuilt the docker image for label bot worker and when I ran the newly built docker image I started seeing these exceptions
Traceback (most recent call last):
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/py/label_microservice/worker.py", line 476, in <module>
fire.Fire(Worker)
File "/usr/local/lib/python3.6/dist-packages/fire/core.py", line 127, in Fire
component_trace = _Fire(component, args, context, name)
File "/usr/local/lib/python3.6/dist-packages/fire/core.py", line 366, in _Fire
component, remaining_args)
File "/usr/local/lib/python3.6/dist-packages/fire/core.py", line 542, in _CallCallable
result = fn(*varargs, **kwargs)
File "/py/label_microservice/worker.py", line 84, in subscribe_from_env
worker.subscribe()
File "/py/label_microservice/worker.py", line 245, in subscribe
logging.info(future.result())
File "/usr/local/lib/python3.6/dist-packages/google/cloud/pubsub_v1/futures.py", line 107, in result
raise err
File "/usr/local/lib/python3.6/dist-packages/google/cloud/pubsub_v1/subscriber/_protocol/streaming_pull_manager.py", line 70, in _wrap_callback_errors
callback(message)
File "/py/label_microservice/worker.py", line 145, in callback
self._predictor = issue_label_predictor.IssueLabelPredictor()
File "/py/label_microservice/issue_label_predictor.py", line 50, in __init__
self._load_models()
File "/py/label_microservice/issue_label_predictor.py", line 61, in _load_models
self._models[UNIVERSAL_MODEL_NAME] = universal_model.UniversalKindLabelModel()
File "/py/label_microservice/universal_kind_label_model.py", line 35, in __init__
self.title_pp = dpickle.load(f)
File "/usr/local/lib/python3.6/dist-packages/dill/_dill.py", line 270, in load
return Unpickler(file, ignore=ignore, **kwds).load()
File "/usr/local/lib/python3.6/dist-packages/dill/_dill.py", line 473, in load
obj = StockUnpickler.load(self)
File "/usr/local/lib/python3.6/dist-packages/dill/_dill.py", line 463, in find_class
return StockUnpickler.find_class(self, module, name)
File "/usr/local/lib/python3.6/dist-packages/ktext/preprocess.py", line 10, in <module>
from keras.preprocessing.sequence import pad_sequences
File "/usr/local/lib/python3.6/dist-packages/keras/__init__.py", line 6, in <module>
'Keras requires TensorFlow 2.2 or higher. '
ImportError: Keras requires TensorFlow 2.2 or higher. Install TensorFlow via `pip install tensorflow`
It looks like our requirements.txt files and Dockerfile pin TensorFlow but not keras. I suspect the ktext installation is pulling in Keras and so we started pulling in a newer version of Keras
I just rebuilt the docker image for label bot worker and when I ran the newly built docker image I started seeing these exceptions
It looks like our requirements.txt files and Dockerfile pin TensorFlow but not keras. I suspect the ktext installation is pulling in Keras and so we started pulling in a newer version of Keras