<filename>pytorch_lightning/plugins/precision/tpu_bfloat.py
# 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.
import os
from typing import Any, Sequence, Tuple, TYPE_CHECKING

from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin

if TYPE_CHECKING:
    from torch.nn import Module
    from torch.optim import Optimizer


class TPUHalfPrecisionPlugin(PrecisionPlugin):
    """Plugin that enables bfloats on TPUs"""

    precision: int = 16

    def connect(
        self,
        model: 'Module',
        optimizers: Sequence['Optimizer'],
        lr_schedulers: Sequence[Any],
    ) -> Tuple['Module', Sequence['Optimizer'], Sequence[Any]]:
        os.environ["XLA_USE_BF16"] = str(1)
        return super().connect(model=model, optimizers=optimizers, lr_schedulers=lr_schedulers)

<filename>pytorch_lightning/plugins/precision/tpu_bfloat.py
# 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.
import os
from typing import Any, Sequence, Tuple, TYPE_CHECKING

from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin

if TYPE_CHECKING:
    from torch.nn import Module
    from torch.optim import Optimizer


class TPUHalfPrecisionPlugin(PrecisionPlugin):
    """Plugin that enables bfloats on TPUs"""

    precision: int = 16

    def connect(
        self,
        model: 'Module',
        optimizers: Sequence['Optimizer'],
        lr_schedulers: Sequence[Any],
    ) -> Tuple['Module', Sequence['Optimizer'], Sequence[Any]]:
        os.environ["XLA_USE_BF16"] = str(1)
        return super().connect(model=model, optimizers=optimizers, lr_schedulers=lr_schedulers)

# 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. Plugin that enables bfloats on TPUs