lightning/tests/tests_pytorch/deprecated_api/test_remove_2-0.py

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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 Callback, Trainer
from pytorch_lightning.demos.boring_classes import BoringModel
from tests_pytorch.callbacks.test_callbacks import OldStatefulCallback
from tests_pytorch.helpers.runif import RunIf
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)
def test_v2_0_0_deprecated_gpus(cuda_count_4):
with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
_ = Trainer(gpus=0)
@RunIf(skip_windows=True)
def test_v2_0_0_deprecated_tpu_cores(tpu_available):
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_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")
def test_v2_0_0_callback_on_load_checkpoint_hook(tmpdir):
class TestCallbackLoadHook(Callback):
def on_load_checkpoint(self, trainer, pl_module, callback_state):
print("overriding on_load_checkpoint")
model = BoringModel()
trainer = Trainer(
callbacks=[TestCallbackLoadHook()],
max_epochs=1,
fast_dev_run=True,
enable_progress_bar=False,
logger=False,
default_root_dir=tmpdir,
)
with pytest.raises(
RuntimeError, match="`TestCallbackLoadHook.on_load_checkpoint` has changed its signature and behavior in v1.8."
):
trainer.fit(model)
def test_v2_0_0_callback_on_save_checkpoint_hook(tmpdir):
class TestCallbackSaveHookReturn(Callback):
def on_save_checkpoint(self, trainer, pl_module, checkpoint):
return {"returning": "on_save_checkpoint"}
class TestCallbackSaveHookOverride(Callback):
def on_save_checkpoint(self, trainer, pl_module, checkpoint):
print("overriding without returning")
model = BoringModel()
trainer = Trainer(
callbacks=[TestCallbackSaveHookReturn()],
max_epochs=1,
fast_dev_run=True,
enable_progress_bar=False,
logger=False,
default_root_dir=tmpdir,
)
trainer.fit(model)
with pytest.raises(
ValueError,
match=(
"Returning a value from `TestCallbackSaveHookReturn.on_save_checkpoint` was deprecated in v1.6 and is"
" no longer supported as of v1.8"
),
):
trainer.save_checkpoint(tmpdir + "/path.ckpt")
trainer.callbacks = [TestCallbackSaveHookOverride()]
trainer.save_checkpoint(tmpdir + "/pathok.ckpt")
def test_v2_0_0_remove_on_batch_start_end(tmpdir):
class TestCallback(Callback):
def on_batch_start(self, *args, **kwargs):
print("on_batch_start")
model = BoringModel()
trainer = Trainer(
callbacks=[TestCallback()],
fast_dev_run=True,
default_root_dir=tmpdir,
)
with pytest.raises(RuntimeError, match="The `Callback.on_batch_start` hook was removed in v1.8"):
trainer.fit(model)
class TestCallback(Callback):
def on_batch_end(self, *args, **kwargs):
print("on_batch_end")
trainer = Trainer(
callbacks=[TestCallback()],
fast_dev_run=True,
default_root_dir=tmpdir,
)
with pytest.raises(RuntimeError, match="The `Callback.on_batch_end` hook was removed in v1.8"):
trainer.fit(model)
def test_v2_0_0_on_configure_sharded_model(tmpdir):
class TestCallback(Callback):
def on_configure_sharded_model(self, trainer, model):
print("Configuring sharded model")
model = BoringModel()
trainer = Trainer(
callbacks=[TestCallback()],
max_epochs=1,
fast_dev_run=True,
enable_progress_bar=False,
logger=False,
default_root_dir=tmpdir,
)
with pytest.raises(RuntimeError, match="The `on_configure_sharded_model` callback hook was removed in v1.8."):
trainer.fit(model)
def test_v2_0_0_remove_on_epoch_start_end_lightning_module(tmpdir):
class CustomModel(BoringModel):
def on_epoch_start(self, *args, **kwargs):
print("on_epoch_start")
model = CustomModel()
trainer = Trainer(
fast_dev_run=True,
default_root_dir=tmpdir,
)
with pytest.raises(RuntimeError, match="The `LightningModule.on_epoch_start` hook was removed in v1.8"):
trainer.fit(model)
class CustomModel(BoringModel):
def on_epoch_end(self, *args, **kwargs):
print("on_epoch_end")
trainer = Trainer(
fast_dev_run=True,
default_root_dir=tmpdir,
)
model = CustomModel()
with pytest.raises(RuntimeError, match="The `LightningModule.on_epoch_end` hook was removed in v1.8"):
trainer.fit(model)
def test_v2_0_0_remove_on_pretrain_routine_start_end_lightning_module(tmpdir):
class CustomModel(BoringModel):
def on_pretrain_routine_start(self, *args, **kwargs):
print("foo")
model = CustomModel()
trainer = Trainer(
fast_dev_run=True,
default_root_dir=tmpdir,
)
with pytest.raises(RuntimeError, match="The `LightningModule.on_pretrain_routine_start` hook was removed in v1.8"):
trainer.fit(model)
class CustomModel(BoringModel):
def on_pretrain_routine_end(self, *args, **kwargs):
print("foo")
trainer = Trainer(
fast_dev_run=True,
default_root_dir=tmpdir,
)
model = CustomModel()
with pytest.raises(RuntimeError, match="The `LightningModule.on_pretrain_routine_end` hook was removed in v1.8"):
trainer.fit(model)
def test_v2_0_0_on_before_accelerator_backend_setup(tmpdir):
class TestCallback(Callback):
def on_before_accelerator_backend_setup(self, *args, **kwargs):
print("on_before_accelerator_backend called.")
model = BoringModel()
trainer = Trainer(
callbacks=[TestCallback()],
max_epochs=1,
fast_dev_run=True,
enable_progress_bar=False,
logger=False,
default_root_dir=tmpdir,
)
with pytest.raises(
RuntimeError, match="The `on_before_accelerator_backend_setup` callback hook was removed in v1.8"
):
trainer.fit(model)
def test_v2_0_0_callback_on_pretrain_routine_start_end(tmpdir):
class TestCallback(Callback):
def on_pretrain_routine_start(self, trainer, pl_module):
print("on_pretrain_routine_start called.")
model = BoringModel()
trainer = Trainer(
callbacks=[TestCallback()],
fast_dev_run=True,
enable_progress_bar=False,
default_root_dir=tmpdir,
)
with pytest.raises(RuntimeError, match="The `Callback.on_pretrain_routine_start` hook was removed in v1.8"):
trainer.fit(model)
class TestCallback(Callback):
def on_pretrain_routine_end(self, trainer, pl_module):
print("on_pretrain_routine_end called.")
model = BoringModel()
trainer = Trainer(
callbacks=[TestCallback()],
fast_dev_run=True,
enable_progress_bar=False,
default_root_dir=tmpdir,
)
with pytest.raises(RuntimeError, match="The `Callback.on_pretrain_routine_end` hook was removed in v1.8."):
trainer.fit(model)
class OnInitStartCallback(Callback):
def on_init_start(self, trainer):
print("Starting to init trainer!")
class OnInitEndCallback(Callback):
def on_init_end(self, trainer):
print("Trainer is init now")
@pytest.mark.parametrize("callback_class", [OnInitStartCallback, OnInitEndCallback])
def test_v2_0_0_unsupported_on_init_start_end(callback_class, tmpdir):
model = BoringModel()
trainer = Trainer(
callbacks=[callback_class()],
max_epochs=1,
fast_dev_run=True,
enable_progress_bar=False,
logger=False,
default_root_dir=tmpdir,
)
with pytest.raises(
RuntimeError, match="callback hook was deprecated in v1.6 and is no longer supported as of v1.8"
):
trainer.fit(model)
with pytest.raises(
RuntimeError, match="callback hook was deprecated in v1.6 and is no longer supported as of v1.8"
):
trainer.validate(model)