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Remove deprecated device attributes from Trainer #14829

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Sep 22, 2022
Merged

Remove deprecated device attributes from Trainer #14829

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f8b3145
Remove deprecated device attributes from Trainer
awaelchli Sep 21, 2022
920b9a5
changelog
awaelchli Sep 21, 2022
56f9ebf
chlog
awaelchli Sep 21, 2022
c89f1f5
Update src/pytorch_lightning/CHANGELOG.md
awaelchli Sep 21, 2022
d6658c2
Merge branch 'master' into feature/remove/device-attrs
Borda Sep 22, 2022
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6 changes: 5 additions & 1 deletion src/pytorch_lightning/CHANGELOG.md
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Expand Up @@ -197,9 +197,13 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

- Removed the deprecated way to set the distributed backend via the environment variable `PL_TORCH_DISTRIBUTED_BACKEND`, in favor of setting the `process_group_backend` in the strategy constructor ([#14693](https://github.com/Lightning-AI/lightning/pull/14693))

- Removed the deprecated device attributes `Trainer.{devices,gpus,num_gpus,ipus,tpu_cores}` in favor of the accelerator-agnostic `Trainer.num_devices` ([#14829](https://github.com/Lightning-AI/lightning/pull/14829))

- Removed the deprecated `Trainer.use_amp` and `LightningModule.use_amp` attributes ([#14832](https://github.com/Lightning-AI/lightning/pull/14832))

- Removed the deprecated `Trainer.root_gpu` attribute in favor of `Trainer.strategy.root_device` ([#14829](https://github.com/Lightning-AI/lightning/pull/14829))


- Removed the deprecated `Trainer.use_amp` and `LightningModule.use_amp` attributes ([#14832](https://github.com/Lightning-AI/lightning/pull/14832))


### Fixed
Expand Down
48 changes: 0 additions & 48 deletions src/pytorch_lightning/trainer/trainer.py
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Expand Up @@ -2052,46 +2052,6 @@ def num_devices(self) -> int:
"""Number of devices the trainer uses per node."""
return len(self.device_ids)

@property
def root_gpu(self) -> Optional[int]:
rank_zero_deprecation(
"`Trainer.root_gpu` is deprecated in v1.6 and will be removed in v1.8. "
"Please use `Trainer.strategy.root_device.index` instead."
)
return self.strategy.root_device.index if isinstance(self.accelerator, CUDAAccelerator) else None

@property
def tpu_cores(self) -> int:
rank_zero_deprecation(
"`Trainer.tpu_cores` is deprecated in v1.6 and will be removed in v1.8. "
"Please use `Trainer.num_devices` instead."
)
return self.num_devices if isinstance(self.accelerator, TPUAccelerator) else 0

@property
def ipus(self) -> int:
rank_zero_deprecation(
"`Trainer.ipus` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` instead."
)
return self.num_devices if isinstance(self.accelerator, IPUAccelerator) else 0

@property
def num_gpus(self) -> int:
rank_zero_deprecation(
"`Trainer.num_gpus` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` instead."
)
return self.num_devices if isinstance(self.accelerator, CUDAAccelerator) else 0

@property
def devices(self) -> int:
rank_zero_deprecation(
"`Trainer.devices` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` or `Trainer.device_ids` to get device information instead."
)
return self.num_devices

@property
def lightning_module(self) -> "pl.LightningModule":
# TODO: this is actually an optional return
Expand Down Expand Up @@ -2140,14 +2100,6 @@ def precision(self) -> Union[str, int]:
def scaler(self) -> Optional[Any]:
return getattr(self.precision_plugin, "scaler", None)

@property
def gpus(self) -> Optional[Union[List[int], str, int]]:
rank_zero_deprecation(
"`Trainer.gpus` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` or `Trainer.device_ids` to get device information instead."
)
return self._accelerator_connector._gpus

@property
def model(self) -> torch.nn.Module:
"""The LightningModule, but possibly wrapped into DataParallel or DistributedDataParallel.
Expand Down
136 changes: 0 additions & 136 deletions tests/tests_pytorch/deprecated_api/test_remove_1-8.py
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Expand Up @@ -19,7 +19,6 @@
import numpy as np
import pytest

import pytorch_lightning
from pytorch_lightning import Callback, Trainer
from pytorch_lightning.callbacks import ModelCheckpoint
from pytorch_lightning.demos.boring_classes import BoringDataModule, BoringModel
Expand All @@ -30,7 +29,6 @@
from pytorch_lightning.trainer.configuration_validator import _check_datamodule_checkpoint_hooks
from pytorch_lightning.trainer.states import RunningStage
from pytorch_lightning.utilities.rank_zero import rank_zero_only
from tests_pytorch.helpers.runif import RunIf


def test_v1_8_0_on_init_start_end(tmpdir):
Expand Down Expand Up @@ -490,104 +488,6 @@ def on_load_checkpoint(self, checkpoint):
_check_datamodule_checkpoint_hooks(trainer)


def test_trainer_config_device_ids():
trainer = Trainer(devices=2)
with pytest.deprecated_call(
match="`Trainer.devices` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` or `Trainer.device_ids` to get device information instead."
):
trainer.devices == 2


@pytest.mark.parametrize(
["gpus", "expected_root_gpu", "strategy"],
[
pytest.param(None, None, "ddp", id="None is None"),
pytest.param(0, None, "ddp", id="O gpus, expect gpu root device to be None."),
pytest.param(1, 0, "ddp", id="1 gpu, expect gpu root device to be 0."),
pytest.param(-1, 0, "ddp", id="-1 - use all gpus, expect gpu root device to be 0."),
pytest.param("-1", 0, "ddp", id="'-1' - use all gpus, expect gpu root device to be 0."),
pytest.param(3, 0, "ddp", id="3 gpus, expect gpu root device to be 0.(backend:ddp)"),
],
)
def test_root_gpu_property(cuda_count_4, gpus, expected_root_gpu, strategy):
with pytest.deprecated_call(
match="`Trainer.root_gpu` is deprecated in v1.6 and will be removed in v1.8. "
"Please use `Trainer.strategy.root_device.index` instead."
):
assert Trainer(gpus=gpus, strategy=strategy).root_gpu == expected_root_gpu


@pytest.mark.parametrize(
["gpus", "expected_root_gpu", "strategy"],
[
pytest.param(None, None, None, id="None is None"),
pytest.param(None, None, "ddp", id="None is None"),
pytest.param(0, None, "ddp", id="None is None"),
],
)
def test_root_gpu_property_0_passing(cuda_count_0, gpus, expected_root_gpu, strategy):
with pytest.deprecated_call(
match="`Trainer.root_gpu` is deprecated in v1.6 and will be removed in v1.8. "
"Please use `Trainer.strategy.root_device.index` instead."
):
assert Trainer(gpus=gpus, strategy=strategy).root_gpu == expected_root_gpu


@pytest.mark.parametrize(
["gpus", "expected_num_gpus", "strategy"],
[
pytest.param(None, 0, None, id="None - expect 0 gpu to use."),
pytest.param(0, 0, None, id="Oth gpu, expect 1 gpu to use."),
pytest.param(1, 1, None, id="1st gpu, expect 1 gpu to use."),
pytest.param(-1, 4, "ddp", id="-1 - use all gpus"),
pytest.param("-1", 4, "ddp", id="'-1' - use all gpus"),
pytest.param(3, 3, "ddp", id="3rd gpu - 1 gpu to use (backend:ddp)"),
],
)
def test_trainer_gpu_parse(cuda_count_4, gpus, expected_num_gpus, strategy):
with pytest.deprecated_call(
match="`Trainer.num_gpus` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` instead."
):
assert Trainer(gpus=gpus, strategy=strategy).num_gpus == expected_num_gpus


@pytest.mark.parametrize(
["gpus", "expected_num_gpus", "strategy"],
[
pytest.param(None, 0, None, id="None - expect 0 gpu to use."),
pytest.param(None, 0, "ddp", id="None - expect 0 gpu to use."),
],
)
def test_trainer_num_gpu_0(cuda_count_0, gpus, expected_num_gpus, strategy):
with pytest.deprecated_call(
match="`Trainer.num_gpus` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` instead."
):
assert Trainer(gpus=gpus, strategy=strategy).num_gpus == expected_num_gpus


@pytest.mark.parametrize(
["trainer_kwargs", "expected_ipus"],
[
({}, 0),
({"devices": 1}, 0),
({"accelerator": "ipu", "devices": 1}, 1),
({"accelerator": "ipu", "devices": 8}, 8),
],
)
def test_trainer_config_ipus(monkeypatch, trainer_kwargs, expected_ipus):
monkeypatch.setattr(pytorch_lightning.accelerators.ipu.IPUAccelerator, "is_available", lambda _: True)
monkeypatch.setattr(pytorch_lightning.strategies.ipu, "_IPU_AVAILABLE", lambda: True)
trainer = Trainer(**trainer_kwargs)
with pytest.deprecated_call(
match="`Trainer.ipus` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` instead."
):
trainer.ipus == expected_ipus


def test_v1_8_0_deprecated_lightning_ipu_module():
with pytest.deprecated_call(match=r"has been deprecated in v1.7.0 and will be removed in v1.8."):
_ = LightningIPUModule(BoringModel(), 32)
Expand Down Expand Up @@ -653,39 +553,3 @@ def on_save_checkpoint(self, trainer, pl_module, checkpoint):

trainer.callbacks = [TestCallbackSaveHookOverride()]
trainer.save_checkpoint(tmpdir + "/pathok.ckpt")


@pytest.mark.parametrize(
"trainer_kwargs",
[
pytest.param({"accelerator": "gpu", "devices": 2}, marks=RunIf(mps=False)),
pytest.param({"accelerator": "gpu", "devices": [0, 2]}, marks=RunIf(mps=False)),
pytest.param({"accelerator": "gpu", "devices": "2"}, marks=RunIf(mps=False)),
pytest.param({"accelerator": "gpu", "devices": "0,"}, marks=RunIf(mps=False)),
pytest.param({"accelerator": "gpu", "devices": 1}, marks=RunIf(mps=True)),
pytest.param({"accelerator": "gpu", "devices": [0]}, marks=RunIf(mps=True)),
pytest.param({"accelerator": "gpu", "devices": "0,"}, marks=RunIf(mps=True)),
],
)
def test_trainer_gpus(cuda_count_4, trainer_kwargs):
trainer = Trainer(**trainer_kwargs)
with pytest.deprecated_call(
match=(
"`Trainer.gpus` was deprecated in v1.6 and will be removed in v1.8."
" Please use `Trainer.num_devices` or `Trainer.device_ids` to get device information instead."
)
):
assert trainer.gpus == trainer_kwargs["devices"]


@RunIf(skip_windows=True)
def test_trainer_tpu_cores(monkeypatch):
monkeypatch.setattr(pytorch_lightning.accelerators.tpu.TPUAccelerator, "is_available", lambda _: True)
trainer = Trainer(accelerator="tpu", devices=8)
with pytest.deprecated_call(
match=(
"`Trainer.tpu_cores` is deprecated in v1.6 and will be removed in v1.8. "
"Please use `Trainer.num_devices` instead."
)
):
assert trainer.tpu_cores == 8