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feat: add progress bar in
record.py and visualize.py
* run `poetry lock --no-update` * add alive-progress via poetry and in code * add progress bar in visualization * add a check for MAX_EVENT = None * update the title for the Progress bAr (better for USer pov) * update the requirement.txt * ran ` black --line-length 80 <file>` on record.py and visualize.py * remove all progress bar from record * add tqdm progress bar in recrod.py * add tqdm for visualiztion * remove alive-progress * consistent tqdm api --add dynamic_cols: to enable adjustments when window is resized Order: --total -description --unit --Optional[bar_format] --colour --dynamic_ncols * Update requirements.txt Co-authored-by: Aaron <57018940+0dm@users.noreply.github.com> * Address comemnt: OpenAdaptAI#318 (comment) * remove incorrect indent * remove rows * try to fix distorted table in html * add custom queue class * lint --line-length 80 * fix `NotImplementedError` for MacOs -- using custom MyQueue class * rename custom -> thirdparty_customization * rename to something useful * address comments * rename dir to customized_imports * rename to extensions OpenAdaptAI#318 (comment) --------- Co-authored-by: Aaron <57018940+0dm@users.noreply.github.com>
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| """ | ||
| Module for customizing multiprocessing.Queue to avoid NotImplementedError in MacOS | ||
| """ | ||
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| from multiprocessing.queues import Queue | ||
| import multiprocessing | ||
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| # Credit: https://gist.github.com/FanchenBao/d8577599c46eab1238a81857bb7277c9 | ||
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| # The following implementation of custom SynchronizedQueue to avoid NotImplementedError | ||
| # when calling queue.qsize() in MacOS X comes almost entirely from this github | ||
| # discussion: https://github.com/keras-team/autokeras/issues/368 | ||
| # Necessary modification is made to make the code compatible with Python3. | ||
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| class SharedCounter(object): | ||
| """ A synchronized shared counter. | ||
| The locking done by multiprocessing.Value ensures that only a single | ||
| process or thread may read or write the in-memory ctypes object. However, | ||
| in order to do n += 1, Python performs a read followed by a write, so a | ||
| second process may read the old value before the new one is written by the | ||
| first process. The solution is to use a multiprocessing.Lock to guarantee | ||
| the atomicity of the modifications to Value. | ||
| This class comes almost entirely from Eli Bendersky's blog: | ||
| http://eli.thegreenplace.net/2012/01/04/ | ||
| shared-counter-with-pythons-multiprocessing/ | ||
| """ | ||
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| def __init__(self, n=0): | ||
| self.count = multiprocessing.Value('i', n) | ||
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| def increment(self, n=1): | ||
| """ Increment the counter by n (default = 1) """ | ||
| with self.count.get_lock(): | ||
| self.count.value += n | ||
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| @property | ||
| def value(self): | ||
| """ Return the value of the counter """ | ||
| return self.count.value | ||
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| class SynchronizedQueue(Queue): | ||
| """ A portable implementation of multiprocessing.Queue. | ||
| Because of multithreading / multiprocessing semantics, Queue.qsize() may | ||
| raise the NotImplementedError exception on Unix platforms like Mac OS X | ||
| where sem_getvalue() is not implemented. This subclass addresses this | ||
| problem by using a synchronized shared counter (initialized to zero) and | ||
| increasing / decreasing its value every time the put() and get() methods | ||
| are called, respectively. This not only prevents NotImplementedError from | ||
| being raised, but also allows us to implement a reliable version of both | ||
| qsize() and empty(). | ||
| Note the implementation of __getstate__ and __setstate__ which help to | ||
| serialize SynchronizedQueue when it is passed between processes. If these functions | ||
| are not defined, SynchronizedQueue cannot be serialized, which will lead to the error | ||
| of "AttributeError: 'SynchronizedQueue' object has no attribute 'size'". | ||
| See the answer provided here: https://stackoverflow.com/a/65513291/9723036 | ||
| For documentation of using __getstate__ and __setstate__ | ||
| to serialize objects, refer to here: | ||
| https://docs.python.org/3/library/pickle.html#pickling-class-instances | ||
| """ | ||
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| def __init__(self): | ||
| super().__init__(ctx=multiprocessing.get_context()) | ||
| self.size = SharedCounter(0) | ||
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| def __getstate__(self): | ||
| """Help to make SynchronizedQueue instance serializable. | ||
| Note that we record the parent class state, which is the state of the | ||
| actual queue, and the size of the queue, which is the state of SynchronizedQueue. | ||
| self.size is a SharedCounter instance. It is itself serializable. | ||
| """ | ||
| return { | ||
| 'parent_state': super().__getstate__(), | ||
| 'size': self.size, | ||
| } | ||
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| def __setstate__(self, state): | ||
| super().__setstate__(state['parent_state']) | ||
| self.size = state['size'] | ||
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| def put(self, *args, **kwargs): | ||
| super().put(*args, **kwargs) | ||
| self.size.increment(1) | ||
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| def get(self, *args, **kwargs): | ||
| item = super().get(*args, **kwargs) | ||
| self.size.increment(-1) | ||
| return item | ||
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| def qsize(self): | ||
| """ Reliable implementation of multiprocessing.Queue.qsize() """ | ||
| return self.size.value | ||
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| def empty(self): | ||
| """ Reliable implementation of multiprocessing.Queue.empty() """ | ||
| return not self.qsize() |
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