Spaces:
Runtime error
Runtime error
# Copyright 2023 The Orbit Authors. All Rights Reserved. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""Provides a utility class for training in epochs.""" | |
import tensorflow as tf, tf_keras | |
class EpochHelper: | |
"""A helper class handle bookkeeping of epochs in custom training loops.""" | |
def __init__(self, epoch_steps: int, global_step: tf.Variable): | |
"""Initializes the `EpochHelper` instance. | |
Args: | |
epoch_steps: An integer indicating how many steps are in an epoch. | |
global_step: A `tf.Variable` providing the current global step. | |
""" | |
self._epoch_steps = epoch_steps | |
self._global_step = global_step | |
self._current_epoch = None | |
self._epoch_start_step = None | |
self._in_epoch = False | |
def epoch_begin(self): | |
"""Returns whether a new epoch should begin.""" | |
if self._in_epoch: | |
return False | |
current_step = self._global_step.numpy() | |
self._epoch_start_step = current_step | |
self._current_epoch = current_step // self._epoch_steps | |
self._in_epoch = True | |
return True | |
def epoch_end(self): | |
"""Returns whether the current epoch should end.""" | |
if not self._in_epoch: | |
raise ValueError("`epoch_end` can only be called inside an epoch.") | |
current_step = self._global_step.numpy() | |
epoch = current_step // self._epoch_steps | |
if epoch > self._current_epoch: | |
self._in_epoch = False | |
return True | |
return False | |
def batch_index(self): | |
"""Index of the next batch within the current epoch.""" | |
return self._global_step.numpy() - self._epoch_start_step | |
def current_epoch(self): | |
return self._current_epoch | |