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# Copyright (c) 2025, NVIDIA CORPORATION. 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.
import os
import shutil
import time
from pathlib import Path
from unittest.mock import patch
import pytest
from lightning.pytorch.callbacks import ModelCheckpoint as PTLModelCheckpoint
from lightning.pytorch.loggers import WandbLogger
from nemo import lightning as nl
from nemo.constants import NEMO_ENV_VARNAME_VERSION
from nemo.utils.exp_manager import NotFoundError
class TestNeMoLogger:
@pytest.fixture
def trainer(self):
return nl.Trainer(accelerator="cpu")
def test_loggers(self):
trainer = nl.Trainer(accelerator="cpu")
logger = nl.NeMoLogger(
update_logger_directory=True,
wandb=WandbLogger(name="custom", save_dir="wandb_logs", offline=True),
)
logger.setup(trainer)
assert logger.tensorboard is None
assert len(logger.extra_loggers) == 0
assert len(trainer.loggers) == 2
assert isinstance(trainer.loggers[1], WandbLogger)
assert str(trainer.loggers[1].save_dir).endswith("nemo_experiments/wandb_logs")
assert trainer.loggers[1]._name == "custom"
def test_explicit_log_dir(self, trainer):
explicit_dir = "explicit_test_dir"
logger = nl.NeMoLogger(name="test", explicit_log_dir=explicit_dir)
app_state = logger.setup(trainer)
assert str(app_state.log_dir) == "explicit_test_dir"
assert app_state.name == "" ## name should be ignored when explicit_log_dir is passed in
assert app_state.version == ""
def test_default_log_dir(self, trainer):
if os.environ.get(NEMO_ENV_VARNAME_VERSION, None) is not None:
del os.environ[NEMO_ENV_VARNAME_VERSION]
logger = nl.NeMoLogger(use_datetime_version=False)
app_state = logger.setup(trainer)
assert app_state.log_dir == Path(Path.cwd() / "nemo_experiments" / "default")
def test_custom_version(self, trainer):
custom_version = "v1.0"
logger = nl.NeMoLogger(name="test", version=custom_version, use_datetime_version=False)
app_state = logger.setup(trainer)
assert app_state.version == custom_version
def test_file_logging_setup(self, trainer):
logger = nl.NeMoLogger(name="test")
with patch("nemo.lightning.nemo_logger.logging.add_file_handler") as mock_add_handler:
logger.setup(trainer)
mock_add_handler.assert_called_once()
def test_model_checkpoint_setup(self, trainer):
ckpt = PTLModelCheckpoint(dirpath="test_ckpt", filename="test-{epoch:02d}-{val_loss:.2f}")
logger = nl.NeMoLogger(name="test", ckpt=ckpt)
logger.setup(trainer)
assert any(isinstance(cb, PTLModelCheckpoint) for cb in trainer.callbacks)
ptl_ckpt = next(cb for cb in trainer.callbacks if isinstance(cb, PTLModelCheckpoint))
assert str(ptl_ckpt.dirpath).endswith("test_ckpt")
assert ptl_ckpt.filename == "test-{epoch:02d}-{val_loss:.2f}"
def test_resume(self, trainer, tmp_path):
"""Tests the resume capabilities of NeMoLogger + AutoResume"""
if os.environ.get(NEMO_ENV_VARNAME_VERSION, None) is not None:
del os.environ[NEMO_ENV_VARNAME_VERSION]
# Error because explicit_log_dir does not exist
with pytest.raises(NotFoundError):
nl.AutoResume(
resume_from_directory=str(tmp_path / "test_resume"),
resume_if_exists=True,
).setup(trainer)
# Error because checkpoints folder does not exist
with pytest.raises(NotFoundError):
nl.AutoResume(
resume_from_directory=str(tmp_path / "test_resume" / "does_not_exist"),
resume_if_exists=True,
).setup(trainer)
# No error because we tell autoresume to ignore notfounderror
nl.AutoResume(
resume_from_directory=str(tmp_path / "test_resume" / "does_not_exist"),
resume_if_exists=True,
resume_ignore_no_checkpoint=True,
).setup(trainer)
path = Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints")
path.mkdir(parents=True)
# Error because checkpoints do not exist in folder
with pytest.raises(NotFoundError):
nl.AutoResume(
resume_from_directory=path,
resume_if_exists=True,
).setup(trainer)
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--end").mkdir()
# Error because *end.ckpt is in folder indicating that training has already finished
with pytest.raises(ValueError):
nl.AutoResume(
resume_from_directory=Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints"),
resume_if_exists=True,
).setup(trainer)
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--end").rmdir()
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--end").mkdir()
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--end-unfinished").touch()
# Error because *end.ckpt is unfinished, should raise an error despite resume_ignore_no_checkpoint=True
with pytest.raises(ValueError):
nl.AutoResume(
resume_from_directory=Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints"),
resume_if_exists=True,
resume_past_end=True,
resume_ignore_no_checkpoint=True,
).setup(trainer)
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--end").rmdir()
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--end-unfinished").unlink()
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--last").mkdir()
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--last-unfinished").touch()
# Error because *last.ckpt is unfinished, should raise an error despite resume_ignore_no_checkpoint=True
with pytest.raises(ValueError):
nl.AutoResume(
resume_from_directory=Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints"),
resume_if_exists=True,
resume_ignore_no_checkpoint=True,
).setup(trainer)
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--last").rmdir()
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--last-unfinished").unlink()
## if there are multiple "-last" checkpoints, choose the most recent one
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--last").mkdir()
time.sleep(1) ## sleep for a second so the checkpoints are created at different times
## make a "weights" dir within the checkpoint
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel2--last" / "weights").mkdir(
parents=True
)
time.sleep(1)
# unfinished last, that should be ignored
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel3--last").mkdir()
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel3--last-unfinished").touch()
nl.AutoResume(
resume_from_directory=Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints"),
resume_if_exists=True,
).setup(trainer)
## if "weights" exists, we should restore from there
assert str(trainer.ckpt_path) == str(
Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel2--last" / "weights")
)
logger = nl.NeMoLogger(
name="default",
log_dir=str(tmp_path) + "/test_resume",
version="version_0",
use_datetime_version=False,
)
logger.setup(trainer)
shutil.rmtree(Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel2--last"))
nl.AutoResume(
resume_if_exists=True,
).setup(trainer)
checkpoint = Path(tmp_path / "test_resume" / "default" / "version_0" / "checkpoints" / "mymodel--last")
assert Path(trainer.ckpt_path).resolve() == checkpoint.resolve()
trainer = nl.Trainer(accelerator="cpu", logger=False)
# Check that model loads from `dirpath` and not <log_dir>/checkpoints
dirpath_log_dir = Path(tmp_path / "test_resume" / "dirpath_test" / "logs")
dirpath_log_dir.mkdir(parents=True)
dirpath_checkpoint_dir = Path(tmp_path / "test_resume" / "dirpath_test" / "ckpts")
dirpath_checkpoint = Path(dirpath_checkpoint_dir / "mymodel--last")
dirpath_checkpoint.mkdir(parents=True)
logger = nl.NeMoLogger(
name="default",
explicit_log_dir=dirpath_log_dir,
)
logger.setup(trainer)
nl.AutoResume(
resume_if_exists=True,
resume_from_directory=str(dirpath_checkpoint_dir),
).setup(trainer)
assert Path(trainer.ckpt_path).resolve() == dirpath_checkpoint.resolve()
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