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"""The event-based main loop of Blocks.""" |
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from abc import ABCMeta |
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from collections import defaultdict |
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from numbers import Integral |
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from uuid import uuid4 |
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import six |
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@six.add_metaclass(ABCMeta) |
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class TrainingLogBase(object): |
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"""Base class for training log. |
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A training log stores the training timeline, statistics and other |
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auxiliary information. Training logs can use different backends e.g. |
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in-memory Python objects or an SQLite database. |
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Information is stored similar to a nested dictionary, so use |
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``log[time][key]`` to read data. An entry without stored data will |
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return an empty dictionary-like object that can be written to, |
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``log[time][key] = value``. |
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Depending on the backend, ``log[time] = {'key': 'value'}`` could fail. |
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Use ``log[time].update({'key': 'value'})`` for compatibility across |
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backends. |
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In addition to the set of records displaying training dynamics, a |
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training log has a :attr:`status` attribute, which is a dictionary with |
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data that is not bound to a particular time. |
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.. warning:: |
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Changes to mutable objects might not be reflected in the log, |
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depending on the backend. So don't use |
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``log.status['key'].append(...)``, use ``log.status['key'] = ...`` |
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instead. |
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Parameters |
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---------- |
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uuid : :class:`uuid.UUID`, optional |
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The UUID of this log. For persistent log backends, passing the UUID |
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will result in an old log being loaded. Otherwise a new, random |
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UUID will be created. |
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Attributes |
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---------- |
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status : dict |
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A dictionary with data representing the current state of training. |
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By default it contains ``iterations_done``, ``epochs_done`` and |
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``_epoch_ends`` (a list of time stamps when epochs ended). |
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""" |
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def __init__(self, uuid=None): |
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if uuid is None: |
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self.uuid = uuid4() |
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else: |
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self.uuid = uuid |
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if uuid is None: |
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self.status.update({ |
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'iterations_done': 0, |
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'epochs_done': 0, |
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'_epoch_ends': [], |
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'resumed_from': None |
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}) |
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@property |
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def h_uuid(self): |
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"""Return a hexadecimal version of the UUID bytes. |
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This is necessary to store ids in an SQLite database. |
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""" |
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return self.uuid.hex |
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def resume(self): |
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"""Resume a log by setting a new random UUID. |
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Keeps a record of the old log that this is a continuation of. It |
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copies the status of the old log into the new log. |
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""" |
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old_uuid = self.h_uuid |
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old_status = dict(self.status) |
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self.uuid = uuid4() |
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self.status.update(old_status) |
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self.status['resumed_from'] = old_uuid |
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def _check_time(self, time): |
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if not isinstance(time, Integral) or time < 0: |
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raise ValueError("time must be a non-negative integer") |
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@property |
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def current_row(self): |
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return self[self.status['iterations_done']] |
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@property |
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def previous_row(self): |
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return self[self.status['iterations_done'] - 1] |
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@property |
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def last_epoch_row(self): |
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return self[self.status['_epoch_ends'][-1]] |
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class TrainingLog(defaultdict, TrainingLogBase): |
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"""Training log using a `defaultdict` as backend. |
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Notes |
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----- |
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For analysis of the logs, it can be useful to convert the log to a |
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Pandas_ data frame: |
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.. code:: python |
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df = DataFrame.from_dict(log, orient='index') |
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.. _Pandas: http://pandas.pydata.org |
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""" |
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def __init__(self): |
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defaultdict.__init__(self, dict) |
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self.status = {} |
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TrainingLogBase.__init__(self) |
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def __reduce__(self): |
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constructor, args, _, _, items = super(TrainingLog, self).__reduce__() |
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return constructor, (), self.__dict__, _, items |
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def __getitem__(self, time): |
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self._check_time(time) |
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return super(TrainingLog, self).__getitem__(time) |
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def __setitem__(self, time, value): |
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self._check_time(time) |
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return super(TrainingLog, self).__setitem__(time, value) |
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mila-udem /
blocks
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