I am working on a project to simulate the autonomous car driving using CARLA simulator. I read somewhere that keras doesn't handle threading well, is it true?
Also, while running the training script using Tensorflow, we created multiple threads for reinforcement learning. However, we are getting the following error. What could be the reason?
(P.S. I have already tried the session variable tweak for providing more memory.)
Exception in thread Thread-2:
Traceback (most recent call last):
File "C:\Users\Ankit\Anaconda\envs\navigate\lib\threading.py", line 926, in _bootstrap_inner
self.run()
File "C:\Users\Ankit\Anaconda\envs\navigate\lib\threading.py", line 870, in run
self._target(*self._args, **self._kwargs)
File "D:\SDC\Carla-RL-master\sources\trainer.py", line 223, in train_in_loop
if not self.train():
File "D:\SDC\Carla-RL-master\sources\trainer.py", line 110, in train
current_qs_list = self.model.predict(current_states, settings.PREDICTION_BATCH_SIZE)
File "C:\Users\Ankit\Anaconda\envs\navigate\lib\site-packages\keras\engine\training.py", line 1462, in predict
callbacks=callbacks)
File "C:\Users\Ankit\Anaconda\envs\navigate\lib\site-packages\keras\engine\training_arrays.py", line 324, in predict_loop
batch_outs = f(ins_batch)
File "C:\Users\Ankit\Anaconda\envs\navigate\lib\site-packages\tensorflow\python\keras\backend.py", line 3076, in __call__
run_metadata=self.run_metadata)
File "C:\Users\Ankit\Anaconda\envs\navigate\lib\site-packages\tensorflow\python\client\session.py", line 1439, in __call__
run_metadata_ptr)
File "C:\Users\Ankit\Anaconda\envs\navigate\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 528, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error while reading resource variable conv2d_3/kernel from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv2d_3/kernel)
[[{{node conv2d_3/convolution/ReadVariableOp}}]]
[[{{node dense_2/BiasAdd}}]]