lightning/tests/deprecated_api/test_remove_2-0.py

89 lines
4.4 KiB
Python

# Copyright The PyTorch Lightning team.
#
# 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.
"""Test deprecated functionality which will be removed in v2.0.0."""
from unittest import mock
import pytest
import pytorch_lightning
from pytorch_lightning import Trainer
from tests.callbacks.test_callbacks import OldStatefulCallback
from tests.helpers import BoringModel
def test_v2_0_0_deprecated_num_processes():
with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
_ = Trainer(num_processes=2)
@mock.patch("torch.cuda.is_available", return_value=True)
@mock.patch("torch.cuda.device_count", return_value=2)
def test_v2_0_0_deprecated_gpus(*_):
with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
_ = Trainer(gpus=0)
@mock.patch("pytorch_lightning.accelerators.tpu.TPUAccelerator.is_available", return_value=True)
@mock.patch("pytorch_lightning.accelerators.tpu.TPUAccelerator.parse_devices", return_value=8)
def test_v2_0_0_deprecated_tpu_cores(*_):
with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
_ = Trainer(tpu_cores=8)
@mock.patch("pytorch_lightning.accelerators.ipu.IPUAccelerator.is_available", return_value=True)
def test_v2_0_0_deprecated_ipus(_, monkeypatch):
monkeypatch.setattr(pytorch_lightning.strategies.ipu, "_IPU_AVAILABLE", True)
with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
_ = Trainer(ipus=4)
def test_v2_0_resume_from_checkpoint_trainer_constructor(tmpdir):
# test resume_from_checkpoint still works until v2.0 deprecation
model = BoringModel()
callback = OldStatefulCallback(state=111)
trainer = Trainer(default_root_dir=tmpdir, max_steps=1, callbacks=[callback])
trainer.fit(model)
ckpt_path = trainer.checkpoint_callback.best_model_path
callback = OldStatefulCallback(state=222)
with pytest.deprecated_call(match=r"Setting `Trainer\(resume_from_checkpoint=\)` is deprecated in v1.5"):
trainer = Trainer(default_root_dir=tmpdir, max_steps=2, callbacks=[callback], resume_from_checkpoint=ckpt_path)
with pytest.deprecated_call(match=r"trainer.resume_from_checkpoint` is deprecated in v1.5"):
_ = trainer.resume_from_checkpoint
assert trainer._checkpoint_connector.resume_checkpoint_path is None
assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path == ckpt_path
trainer.validate(model=model, ckpt_path=ckpt_path)
assert callback.state == 222
assert trainer._checkpoint_connector.resume_checkpoint_path is None
assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path == ckpt_path
with pytest.deprecated_call(match=r"trainer.resume_from_checkpoint` is deprecated in v1.5"):
trainer.fit(model)
ckpt_path = trainer.checkpoint_callback.best_model_path # last `fit` replaced the `best_model_path`
assert callback.state == 111
assert trainer._checkpoint_connector.resume_checkpoint_path is None
assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path is None
trainer.predict(model=model, ckpt_path=ckpt_path)
assert trainer._checkpoint_connector.resume_checkpoint_path is None
assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path is None
trainer.fit(model)
assert trainer._checkpoint_connector.resume_checkpoint_path is None
assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path is None
# test fit(ckpt_path=) precedence over Trainer(resume_from_checkpoint=) path
model = BoringModel()
with pytest.deprecated_call(match=r"Setting `Trainer\(resume_from_checkpoint=\)` is deprecated in v1.5"):
trainer = Trainer(resume_from_checkpoint="trainer_arg_path")
with pytest.raises(FileNotFoundError, match="Checkpoint at fit_arg_ckpt_path not found. Aborting training."):
trainer.fit(model, ckpt_path="fit_arg_ckpt_path")