Created
August 16, 2024 16:48
-
-
Save kabouzeid/c394b2300e6bd57e0ca1a22478072941 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| # Copyright (c) Karim Abou Zeid | |
| from typing import Any | |
| import lightning.pytorch as pl | |
| import torch | |
| from lightning.pytorch.callbacks.callback import Callback | |
| from lightning.pytorch.utilities.exceptions import MisconfigurationException | |
| from lightning.pytorch.utilities.types import STEP_OUTPUT | |
| from typing_extensions import override | |
| class CudaMemoryMonitor(Callback): | |
| def __init__(self, name="cuda_memory", prog_bar=True) -> None: | |
| super().__init__() | |
| self.name = name | |
| self.prog_bar = prog_bar | |
| @override | |
| def setup( | |
| self, | |
| trainer: "pl.Trainer", | |
| pl_module: "pl.LightningModule", | |
| stage: str, | |
| ) -> None: | |
| if stage != "fit": | |
| return | |
| if not trainer.loggers: | |
| raise MisconfigurationException( | |
| "Cannot use `GpuMemoryMonitor` callback with `Trainer(logger=False)`." | |
| ) | |
| device = trainer.strategy.root_device | |
| if not device.type == "cuda": | |
| raise MisconfigurationException( | |
| f"Cannot use `GpuMemoryMonitor` callback with {device.type} device." | |
| ) | |
| def _get_and_log_device_stats( | |
| self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", key: str | |
| ) -> None: | |
| max_mem_gibi = torch.cuda.max_memory_allocated(trainer.strategy.root_device) / ( | |
| 2**30 | |
| ) | |
| pl_module.log( | |
| f"{key}_{self.name}", | |
| max_mem_gibi, | |
| on_step=True, | |
| on_epoch=False, | |
| reduce_fx=torch.max, | |
| prog_bar=self.prog_bar, | |
| ) | |
| @override | |
| def on_train_batch_start( | |
| self, | |
| trainer: "pl.Trainer", | |
| pl_module: "pl.LightningModule", | |
| batch: Any, | |
| batch_idx: int, | |
| ) -> None: | |
| torch.cuda.reset_peak_memory_stats() | |
| @override | |
| def on_train_batch_end( | |
| self, | |
| trainer: "pl.Trainer", | |
| pl_module: "pl.LightningModule", | |
| outputs: STEP_OUTPUT, | |
| batch: Any, | |
| batch_idx: int, | |
| ) -> None: | |
| self._get_and_log_device_stats(trainer, pl_module, "train") | |
| @override | |
| def on_validation_batch_start( | |
| self, | |
| trainer: "pl.Trainer", | |
| pl_module: "pl.LightningModule", | |
| batch: Any, | |
| batch_idx: int, | |
| dataloader_idx: int = 0, | |
| ) -> None: | |
| torch.cuda.reset_peak_memory_stats() | |
| @override | |
| def on_validation_batch_end( | |
| self, | |
| trainer: "pl.Trainer", | |
| pl_module: "pl.LightningModule", | |
| outputs: STEP_OUTPUT, | |
| batch: Any, | |
| batch_idx: int, | |
| dataloader_idx: int = 0, | |
| ) -> None: | |
| self._get_and_log_device_stats(trainer, pl_module, "validation") | |
| @override | |
| def on_test_batch_start( | |
| self, | |
| trainer: "pl.Trainer", | |
| pl_module: "pl.LightningModule", | |
| batch: Any, | |
| batch_idx: int, | |
| dataloader_idx: int = 0, | |
| ) -> None: | |
| torch.cuda.reset_peak_memory_stats() | |
| @override | |
| def on_test_batch_end( | |
| self, | |
| trainer: "pl.Trainer", | |
| pl_module: "pl.LightningModule", | |
| outputs: STEP_OUTPUT, | |
| batch: Any, | |
| batch_idx: int, | |
| dataloader_idx: int = 0, | |
| ) -> None: | |
| self._get_and_log_device_stats(trainer, pl_module, "test") |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment