"on fit_generator() / fit() and thread-safety" Code Answer
Answers related to “on fit_generator() / fit() and thread-safety”
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during my research on this i came across some information answering my questions.
note: as updated in the question in newer
fit_generator()is deprecated. instead, it is recommended to use
fit()with the generator. however, the answer still applies to
fit()using a generator as well.
taken from keras' gitrepo (training_generators.py) i found in lines
the definition of
is_sequence()taken from training_utils.py in lines
regarding this piece of code keras only checks if a passed generator is a keras-sequence (or rather uses keras' sequence api) and does not check if a generator is threadsafe in general.
as omer zohar has shown on github his decorator is threadsafe - i don't see any reason why it shouldn't be as threadsafe for keras (even though keras will warn as shown in 1.). the implementation of
thread.lock()can be concidered as threadsafe according to the docs:
the generator is also picklable, which can be tested like (see this so-q&a here for further information):
resuming this, i would even suggest to implement
thread.lock()when you extend keras'
self.lock = threading.lock()you might run into the following error:
in case this happens try to replace
with threading.lock():and comment out / delete the
self.lock = threading.lock()inside the
it seems there are some problems when storing the
lock-object inside a class (see for example this q&a).
during my research i did not encounter any other method. of course i cannot say this with 100% certainty.