98 lines
3.9 KiB
Python
98 lines
3.9 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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from typing import Union, Optional
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from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping, ProgressBarBase, ProgressBar
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from pytorch_lightning.utilities import rank_zero_warn
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from pytorch_lightning.utilities.exceptions import MisconfigurationException
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class CallbackConnector:
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def __init__(self, trainer):
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self.trainer = trainer
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def on_trainer_init(
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self,
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callbacks,
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checkpoint_callback,
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progress_bar_refresh_rate,
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process_position,
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default_root_dir,
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weights_save_path,
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resume_from_checkpoint
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):
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self.trainer.resume_from_checkpoint = resume_from_checkpoint
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# init folder paths for checkpoint + weights save callbacks
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self.trainer._default_root_dir = default_root_dir or os.getcwd()
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self.trainer._weights_save_path = weights_save_path or self.trainer._default_root_dir
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# init callbacks
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self.trainer.callbacks = callbacks or []
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# configure checkpoint callback
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# it is important that this is the last callback to run
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# pass through the required args to figure out defaults
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self.configure_checkpoint_callbacks(checkpoint_callback)
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# init progress bar
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self.trainer._progress_bar_callback = self.configure_progress_bar(
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progress_bar_refresh_rate, process_position
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)
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def configure_checkpoint_callbacks(self, checkpoint_callback: Union[ModelCheckpoint, bool]):
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if isinstance(checkpoint_callback, ModelCheckpoint):
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# TODO: deprecated, remove this block in v1.3.0
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rank_zero_warn(
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"Passing a ModelCheckpoint instance to Trainer(checkpoint_callbacks=...)"
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" is deprecated since v1.1 and will no longer be supported in v1.3.",
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DeprecationWarning
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)
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self.trainer.callbacks.append(checkpoint_callback)
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if self._trainer_has_checkpoint_callbacks() and checkpoint_callback is False:
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raise MisconfigurationException(
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"Trainer was configured with checkpoint_callback=False but found ModelCheckpoint"
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" in callbacks list."
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)
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if not self._trainer_has_checkpoint_callbacks() and checkpoint_callback is True:
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self.trainer.callbacks.append(ModelCheckpoint(dirpath=None, filename=None))
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def configure_progress_bar(self, refresh_rate=1, process_position=0):
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progress_bars = [c for c in self.trainer.callbacks if isinstance(c, ProgressBarBase)]
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if len(progress_bars) > 1:
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raise MisconfigurationException(
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'You added multiple progress bar callbacks to the Trainer, but currently only one'
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' progress bar is supported.'
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)
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elif len(progress_bars) == 1:
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progress_bar_callback = progress_bars[0]
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elif refresh_rate > 0:
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progress_bar_callback = ProgressBar(
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refresh_rate=refresh_rate,
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process_position=process_position,
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)
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self.trainer.callbacks.append(progress_bar_callback)
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else:
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progress_bar_callback = None
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return progress_bar_callback
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def _trainer_has_checkpoint_callbacks(self):
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return len(self.trainer.checkpoint_callbacks) > 0
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