Source code for pytorch_lightning.plugins.precision.tpu

# Copyright The Lightning AI 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
from functools import partial
from typing import Any, Callable

import pytorch_lightning as pl
from lightning_fabric.accelerators.tpu import _XLA_AVAILABLE
from lightning_fabric.utilities.types import Optimizable
from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin
from pytorch_lightning.utilities.exceptions import MisconfigurationException

[docs]class TPUPrecisionPlugin(PrecisionPlugin): """Precision plugin for TPU integration.""" def __init__(self, *args: Any, **kwargs: Any) -> None: if not _XLA_AVAILABLE: raise ModuleNotFoundError(str(_XLA_AVAILABLE)) super().__init__(*args, **kwargs) def _tpu_wrap_closure(self, optimizer: Optimizable, closure: Callable[[], Any]) -> Any: import torch_xla.core.xla_model as xm closure_result = closure() xm.reduce_gradients(optimizer) return closure_result
[docs] def optimizer_step( # type: ignore[override] self, optimizer: Optimizable, model: "pl.LightningModule", optimizer_idx: int, closure: Callable[[], Any], **kwargs: Any, ) -> Any: import torch_xla.core.xla_model as xm closure = partial(self._tpu_wrap_closure, optimizer, closure) closure = partial(self._wrap_closure, model, optimizer, optimizer_idx, closure) closure_result = optimizer.step(closure=closure, **kwargs) xm.mark_step() skipped_backward = closure_result is None # in manual optimization, the closure does not return a value if model.automatic_optimization and skipped_backward: # we lack coverage here so disable this - something to explore if there's demand raise MisconfigurationException( "Skipping backward by returning `None` from your `training_step` is not implemented for TPUs." " Please, open an issue in ``" " requesting this feature." ) return closure_result

© Copyright Copyright (c) 2018-2023, Lightning AI et al...

Built with Sphinx using a theme provided by Read the Docs.