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# 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
#
# 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 functools
import logging
from typing import Any
from typing_extensions import override
from lightning_fabric.accelerators.xla import _XLA_AVAILABLE, _XLA_GREATER_EQUAL_2_1, XLAAccelerator
from lightning_fabric.plugins.environments.cluster_environment import ClusterEnvironment
log = logging.getLogger(__name__)
class XLAEnvironment(ClusterEnvironment):
"""Cluster environment for training on a TPU Pod with the `PyTorch/XLA <https://pytorch.org/xla>`_ library.
A list of environment variables set by XLA can be found
`here <https://github.com/pytorch/xla/blob/master/torch_xla/core/xla_env_vars.py>`_.
"""
def __init__(self, *args: Any, **kwargs: Any) -> None:
if not _XLA_AVAILABLE:
raise ModuleNotFoundError(str(_XLA_AVAILABLE))
super().__init__(*args, **kwargs)
@property
@override
def creates_processes_externally(self) -> bool:
return False
@property
@override
def main_address(self) -> str:
# unused by lightning
raise NotImplementedError
@property
@override
def main_port(self) -> int:
# unused by lightning
raise NotImplementedError
@staticmethod
@override
def detect() -> bool:
return XLAAccelerator.is_available()
@override
@functools.lru_cache(maxsize=1)
def world_size(self) -> int:
"""The number of processes across all devices and hosts.
The output is cached for performance.
"""
import torch_xla.core.xla_model as xm
return xm.xrt_world_size()
@override
def set_world_size(self, size: int) -> None:
log.debug("XLAEnvironment.set_world_size was called, but setting world size is not allowed. Ignored.")
@override
@functools.lru_cache(maxsize=1)
def global_rank(self) -> int:
"""The rank (index) of the currently running process across all host and devices.
The output is cached for performance.
"""
import torch_xla.core.xla_model as xm
return xm.get_ordinal()
@override
def set_global_rank(self, rank: int) -> None:
log.debug("XLAEnvironment.set_global_rank was called, but setting global rank is not allowed. Ignored.")
@override
@functools.lru_cache(maxsize=1)
def local_rank(self) -> int:
"""The rank (index) of the currently running process inside of the current host.
The output is cached for performance.
"""
import torch_xla.core.xla_model as xm
return xm.get_local_ordinal()
@override
@functools.lru_cache(maxsize=1)
def node_rank(self) -> int:
"""The rank (index) of the host on which the current process runs.
The output is cached for performance.
"""
if _XLA_GREATER_EQUAL_2_1:
from torch_xla import runtime as xr
return xr.host_index()
import torch_xla.core.xla_env_vars as xenv
from torch_xla.utils.utils import getenv_as
return getenv_as(xenv.HOST_ORDINAL, int, 0)
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