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In TorchSnapshotSaver save checkpoint in on_train_end #390

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In TorchSnapshotSaver save checkpoint in on_train_end #390

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26 changes: 26 additions & 0 deletions tests/framework/callbacks/test_torchsnapshot_saver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -91,6 +91,32 @@ def test_save_every_n_train_epochs(self) -> None:
os.path.exists(expected_path) and os.path.isdir(expected_path)
)

def test_save_on_train_end(self) -> None:
input_dim = 2
dataset_len = 10
batch_size = 2
max_epochs = 3
expected_steps_per_epoch = math.ceil(dataset_len / batch_size)
save_every_n_train_epochs = 2

my_unit = DummyTrainUnit(input_dim=input_dim)
dataloader = generate_random_dataloader(dataset_len, input_dim, batch_size)
state = init_train_state(dataloader=dataloader, max_epochs=max_epochs)
with tempfile.TemporaryDirectory() as temp_dir:
expected_path = os.path.join(
temp_dir,
f"epoch_{max_epochs}_step_{expected_steps_per_epoch * (max_epochs)}",
)
snapshot = TorchSnapshotSaver(
temp_dir,
save_every_n_epochs=save_every_n_train_epochs,
replicated=["**"],
)
train(state, my_unit, callbacks=[snapshot])
self.assertTrue(
os.path.exists(expected_path) and os.path.isdir(expected_path)
)

def test_save_restore(self) -> None:
input_dim = 2
dataset_len = 10
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10 changes: 10 additions & 0 deletions torchtnt/framework/callbacks/torchsnapshot_saver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -148,6 +148,16 @@ def on_train_epoch_end(self, state: State, unit: TTrainUnit) -> None:
self._async_snapshot(snapshot_path, app_state, wait=True)

def on_train_end(self, state: State, unit: TTrainUnit) -> None:
app_state = _get_app_state(state, unit, self._replicated, intra_epoch=False)

train_state = none_throws(state.train_state)
epoch = train_state.progress.num_epochs_completed
global_step = train_state.progress.num_steps_completed

# save snapshot to predetermined path
# TODO: discuss whether this path should be customized
snapshot_path = _get_snapshot_save_path(self._dirpath, epoch, global_step)
self._async_snapshot(snapshot_path, app_state, wait=False)
self._wait()

def on_exception(
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