Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

R2.12.1 merge with preemption_watcher fix #11045

Merged
merged 1 commit into from
Jul 7, 2023
Merged

R2.12.1 merge with preemption_watcher fix #11045

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion official/core/config_definitions.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -272,7 +272,7 @@ class TrainerConfig(base_config.Config):
recovery_max_trials: int = 0
validation_summary_subdir: str = "validation"
# Preemption on-demand checkpoint.
preemption_on_demand_checkpoint: bool = True
preemption_on_demand_checkpoint: bool = False


@dataclasses.dataclass
Expand Down
2 changes: 1 addition & 1 deletion official/nlp/train.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@ def _run_experiment_with_preemption_recovery(params, model_dir):
**params.runtime.model_parallelism())
with distribution_strategy.scope():
task = task_factory.get_task(params.task, logging_dir=model_dir)
preemption_watcher = tf.distribute.experimental.PreemptionWatcher()
preemption_watcher = None

train_lib.run_experiment(
distribution_strategy=distribution_strategy,
Expand Down
2 changes: 1 addition & 1 deletion official/vision/train.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,7 @@ def _run_experiment_with_preemption_recovery(params, model_dir):
tpu_address=params.runtime.tpu)
with distribution_strategy.scope():
task = task_factory.get_task(params.task, logging_dir=model_dir)
preemption_watcher = tf.distribute.experimental.PreemptionWatcher()
preemption_watcher = None

train_lib.run_experiment(
distribution_strategy=distribution_strategy,
Expand Down