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[Tune][Fix]Remove the clear_checkpoint function during Trial restoration error handling. #48532

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merged 7 commits into from
Nov 6, 2024
Merged

[Tune][Fix]Remove the clear_checkpoint function during Trial restoration error handling. #48532

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312406b
remove clear checkpoint
hongpeng-guo Nov 4, 2024
a40b92f
fix faulty unit test of test_tune_restore
hongpeng-guo Nov 5, 2024
8688364
change the unit test back
hongpeng-guo Nov 5, 2024
72e83c9
remove pdb, making num_failures 2
hongpeng-guo Nov 5, 2024
0a376ff
adding documents of the unit test
hongpeng-guo Nov 5, 2024
fe661bb
Merge remote-tracking branch 'origin' into hpguo/v2/tune_restore_fix
hongpeng-guo Nov 5, 2024
0dbb310
Merge remote-tracking branch 'origin' into hpguo/v2/tune_restore_fix
hongpeng-guo Nov 6, 2024
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10 changes: 2 additions & 8 deletions python/ray/tune/experiment/trial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -793,11 +793,11 @@ def get_error(self) -> Optional[TuneError]:
return None

def _handle_restore_error(self, exc: Exception):
# For Restoration errors, we only increment the restore failure count
# if the number of failures exceeds the restore retry limit.
if self.temporary_state.num_restore_failures >= int(
os.environ.get("TUNE_RESTORE_RETRY_NUM", 0)
):
# Restore was unsuccessful, try again without checkpoint.
self.clear_checkpoint()
self.run_metadata.num_failures += 1
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what are diff between self.run_metadata.num_failures and self.temporary_state.num_restore_failures?

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num_restore_failures is the number of failed restoration.
num_failures is the number of failures that caused by user/ application code.

because restoration is not a user defined behavior, but some feature we provided. We don't treat restoration failure same as normal application failure. The behavior is, when the program failed due to application, we increment the num_failures and trying to restore the application. If the restoration is successful, the program just goes on. If the restoration fail, we will keep on trying to restore but increments the number of num_restore_failures by 1. When the TUNE_RESTORE_RETRY_NUM restore reaches, we stop restoration, and increment the num_failures by another 1.

else:
self.temporary_state.num_restore_failures += 1
Expand Down Expand Up @@ -883,12 +883,6 @@ def should_checkpoint(self):
def has_checkpoint(self) -> bool:
return self.checkpoint is not None

def clear_checkpoint(self):
if self.latest_checkpoint_result:
self.latest_checkpoint_result.checkpoint = None
self.temporary_state.restoring_from = None
self.run_metadata.invalidate_cache()

def on_checkpoint(self, checkpoint_result: _TrainingResult):
"""Hook for handling checkpoints taken by the Trainable.

Expand Down
20 changes: 17 additions & 3 deletions python/ray/tune/tests/test_tuner_restore.py
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Expand Up @@ -537,7 +537,21 @@ def test_tuner_restore_latest_available_checkpoint(

@pytest.mark.parametrize("retry_num", [0, 2])
def test_restore_retry(ray_start_2_cpus, tmpdir, retry_num):
"""Test retrying restore on a trial level by setting `TUNE_RESTORE_RETRY_NUM`."""
"""
Test retrying restore on a trial level by setting `TUNE_RESTORE_RETRY_NUM`.

This unit test holds the following hyperparameters:
- `retry_num`: Maximum number of retry attempts for restoring a trial.
This value is assigned to the environment variable `TUNE_RESTORE_RETRY_NUM`.
If the restoration fails after retry_num attempts, the trial increments its
counter of total number of failures by 1.

- `retry_num_to_fail`: Number of restore attempts to fail. In this test,
retry_num_to_fail is set to 2, causing the first two restore attempts to fail.

- `max_failures`: Maximum allowable failures during training. Here, max_failures is
set to 2, meaning the training process will terminate after two total failures.
"""

class MockTrainable(Trainable):
"""A trainable that can generate one failure during training and
Expand All @@ -546,7 +560,7 @@ class MockTrainable(Trainable):
def setup(self, config):
self.idx = 0
self.tag_file_path = config["tag_file_path"]
self.retry_num_to_fail = config.get("retry_num_to_fail", 2)
self.retry_num_to_fail = 2
self._is_restored = False

def step(self):
Expand Down Expand Up @@ -592,7 +606,7 @@ def load_checkpoint(self, checkpoint_dir):
name="tryout_restore",
stop={"training_iteration": 5},
storage_path=str(tmpdir),
failure_config=FailureConfig(max_failures=1),
failure_config=FailureConfig(max_failures=2),
checkpoint_config=CheckpointConfig(checkpoint_frequency=1),
),
param_space={"tag_file_path": tag_file},
Expand Down
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