# 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.
from typing import Any, Dict, Union
import torch
from pytorch_lightning.accelerators.accelerator import Accelerator
from pytorch_lightning.utilities import _XLA_AVAILABLE
if _XLA_AVAILABLE:
import torch_xla.core.xla_model as xm
class TPUAccelerator(Accelerator):
"""Accelerator for TPU devices."""
def get_device_stats(self, device: Union[str, torch.device]) -> Dict[str, Any]:
"""Gets stats for the given TPU device.
Args:
device: TPU device for which to get stats
Returns:
A dictionary mapping the metrics (free memory and peak memory) to their values.
"""
memory_info = xm.get_memory_info(device)
free_memory = memory_info["kb_free"]
peak_memory = memory_info["kb_total"] - free_memory
device_stats = {
"avg. free memory (MB)": free_memory,
"avg. peak memory (MB)": peak_memory,
}
return device_stats
@staticmethod
def auto_device_count() -> int:
"""Get the devices when set to auto."""
return 8
