From 76d0995ca68e646493b2b8395fc3c81baf6438a4 Mon Sep 17 00:00:00 2001 From: Konstantin Dobler Date: Mon, 31 Jul 2023 17:36:18 +0200 Subject: [PATCH] Miscellaneous fixes --- conda-lock.yml | 3 +- dlib/frameworks/huggingface.py | 7 + dlib/frameworks/wandb.py | 4 +- ppc64le.conda-lock.yml | 3154 ++++++++++++++++---------------- src/helpers.py | 17 + train.py | 18 +- 6 files changed, 1640 insertions(+), 1563 deletions(-) create mode 100644 dlib/frameworks/huggingface.py diff --git a/conda-lock.yml b/conda-lock.yml index 91e9fee..ef99537 100644 --- a/conda-lock.yml +++ b/conda-lock.yml @@ -9,7 +9,7 @@ # To update a single package to the latest version compatible with the version constraints in the source: # conda-lock lock --lockfile conda-lock.yml --update PACKAGE # To re-solve the entire environment, e.g. after changing a version constraint in the source file: -# conda-lock -f ./environment.yml -f /Users/kjd/prog/nlp-research-template/environment.yml --lockfile conda-lock.yml +# conda-lock -f ./environment.yml --lockfile conda-lock.yml metadata: channels: - url: conda-forge @@ -28,7 +28,6 @@ metadata: - win-64 sources: - ./environment.yml - - /Users/kjd/prog/nlp-research-template/environment.yml package: - category: main dependencies: {} diff --git a/dlib/frameworks/huggingface.py b/dlib/frameworks/huggingface.py new file mode 100644 index 0000000..f552790 --- /dev/null +++ b/dlib/frameworks/huggingface.py @@ -0,0 +1,7 @@ +import transformers + + +class EvaluateFirstStepCallback(transformers.TrainerCallback): + def on_step_end(self, args, state, control, **kwargs): + if state.global_step == 1: + control.should_evaluate = True diff --git a/dlib/frameworks/wandb.py b/dlib/frameworks/wandb.py index c10dffc..1cf86e8 100644 --- a/dlib/frameworks/wandb.py +++ b/dlib/frameworks/wandb.py @@ -13,8 +13,8 @@ from ..frameworks.pytorch import get_rank -WANDB_PROJECT = "test-wandb" -WANDB_ENTITY = "konstantinjdobler" +WANDB_PROJECT = "" +WANDB_ENTITY = "" if WANDB_ENTITY == "" or WANDB_PROJECT == "": logger.warning( diff --git a/ppc64le.conda-lock.yml b/ppc64le.conda-lock.yml index 14615dd..99fa76a 100644 --- a/ppc64le.conda-lock.yml +++ b/ppc64le.conda-lock.yml @@ -1,4 +1,4 @@ -# This lock file was generated by conda-lock (https://github.com/conda-incubator/conda-lock). DO NOT EDIT! +# This lock file was generated by conda-lock (https://github.com/conda/conda-lock). DO NOT EDIT! # # A "lock file" contains a concrete list of package versions (with checksums) to be installed. Unlike # e.g. `conda env create`, the resulting environment will not change as new package versions become @@ -9,8 +9,11 @@ # To update a single package to the latest version compatible with the version constraints in the source: # conda-lock lock --lockfile ppc64le.conda-lock.yml --update PACKAGE # To re-solve the entire environment, e.g. after changing a version constraint in the source file: -# conda-lock -f ./environment-ppc64le.yml -f /Users/kjd/prog/nlp-research-template/ppc64le.environment.yml --lockfile ppc64le.conda-lock.yml +# conda-lock -f ppc64le.environment.yml --lockfile ppc64le.conda-lock.yml +version: 1 metadata: + content_hash: + linux-ppc64le: ea538000fc2b9f1a9b5965e4b13ba78886d0c15d175283df17fcfcfa63086854 channels: - url: conda-forge used_env_vars: [] @@ -18,837 +21,837 @@ metadata: used_env_vars: [] - url: defaults used_env_vars: [] - content_hash: - linux-ppc64le: 198c7a4f20c8c9d1bceea59dd15b7871ebe36c79789694718bda40fe8b1a280c platforms: - linux-ppc64le sources: - 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md5: cde76d49fd12b7f1f13aeb00aa216b8b - sha256: 387742fa861b42f16ceca2a05579187db8e8d80f262c9de5db18f9c0f421f1ce - manager: conda - name: pytorch-lightning + md5: 97138eb8783fa54884216a6562413736 + sha256: d2b5fbd636393c71dfc07ce5a15eb36285b01aaa34453b3fd8b9b26f0fa5b689 + category: main optional: false +- name: lightning + version: 2.0.3 + manager: conda platform: linux-ppc64le - url: https://conda.anaconda.org/conda-forge/noarch/pytorch-lightning-2.0.1.post0-pyhd8ed1ab_0.conda - version: 2.0.1.post0 -- category: main dependencies: arrow: <3.0,>=1.2.0 beautifulsoup4: <6.0,>=4.8.0 @@ -3488,16 +3560,16 @@ package: croniter: <1.4.0,>=1.3.0 dateutils: <2.0 deepdiff: <8.0,>=5.7.0 - fastapi: <0.89.0 + fastapi: <0.89.0,>=0.69.0 fsspec: <2024.0,>=2022.5.0 inquirer: <5.0,>=2.10.0 jinja2: <5.0 - lightning-cloud: '>=0.5.31' + lightning-cloud: '>=0.5.34' lightning-utilities: <2.0,>=0.7.0 numpy: <3.0,>=1.17.2 packaging: '' psutil: <7.0 - pydantic: <3.0 + pydantic: <4.0,>=1.7.4 python: '>=3.8' python-multipart: '' pytorch: <4.0,>=1.11.0 @@ -3505,7 +3577,7 @@ package: pyyaml: <8.0 requests: <4.0 rich: <15.0,>=12.3.0 - starlette: <2.0 + starlette: '' starsessions: <2.0,>=1.2.1 torchmetrics: <2.0,>=0.7.0 tqdm: <6.0,>=4.57.0 @@ -3515,23 +3587,19 @@ package: uvicorn: <2.0 websocket-client: <3.0 websockets: <12.0 + url: https://conda.anaconda.org/conda-forge/noarch/lightning-2.0.3-pyhd8ed1ab_0.conda hash: - md5: 94f92697811903496492f22d2be9261b - sha256: 7f0a5bccd8efb144e124cf5c86656201ea58955c4e9fe54c5717a7bcfb0ae1f2 - manager: conda - name: lightning + md5: 6c66fafaef21c72c05239e54e7decf7d + sha256: 5244d52db4c21261f9679ddc11286edd9e367b02c23c4c9e68ed131555827289 + category: main optional: false +- name: warmup-scheduler + version: '0.3' + manager: pip platform: linux-ppc64le - url: https://conda.anaconda.org/conda-forge/noarch/lightning-2.0.1.post0-pyhd8ed1ab_0.conda - version: 2.0.1.post0 -- category: main dependencies: {} + url: https://files.pythonhosted.org/packages/00/39/f77fb5a7a572891c1f4df1d8e1373a1380cb6d861933886334553244d002/warmup_scheduler-0.3.tar.gz hash: sha256: 63624cf5010772252c530ceb1a64e3fd60e3ee54264054da389f1b421089b714 - manager: pip - name: warmup-scheduler + category: main optional: false - platform: linux-ppc64le - url: https://files.pythonhosted.org/packages/00/39/f77fb5a7a572891c1f4df1d8e1373a1380cb6d861933886334553244d002/warmup_scheduler-0.3.tar.gz - version: '0.3' -version: 1 diff --git a/src/helpers.py b/src/helpers.py index c3aaccf..f3cb19d 100644 --- a/src/helpers.py +++ b/src/helpers.py @@ -88,3 +88,20 @@ def handle_batch_size_logic_(args: "TrainingArgs"): f"{args.gradient_accumulation_steps} gradient accumulation steps." ) return effective_batch_size_per_step + + +def log_slurm_info(): + # The info doesn't always seem to be in the same environment variable, so we just check all of them + gpu_identifiers = ( + os.environ.get("SLURM_GPUS") + or os.environ.get("SLURM_GPUS_PER_TASK") + or os.environ.get("SLURM_JOB_GPUS") + or os.environ.get("SLURM_STEP_GPUS") + or len(os.environ.get("CUDA_VISIBLE_DEVICES", [])) + ) + logger.info( + f"Detected SLURM environment. SLURM Job ID: {os.environ.get('SLURM_JOB_ID')}, " + f"SLURM Host Name: {os.environ.get('SLURM_JOB_NODELIST')}, " + f"SLURM Job Name: {os.environ.get('SLURM_JOB_NAME')}, " + f"SLURM GPUS: {gpu_identifiers}" + ) diff --git a/train.py b/train.py index c920b3a..1e51dcf 100644 --- a/train.py +++ b/train.py @@ -33,6 +33,7 @@ choose_auto_accelerator, choose_auto_devices, handle_batch_size_logic_, + log_slurm_info, ) from src.model import BasicLM @@ -299,21 +300,7 @@ def main(parsed_arg_groups: tuple[TrainingArgs, MiscArgs]): IS_ON_SLURM = SLURMEnvironment.detect() if IS_ON_SLURM and current_process_rank == 0: - # The info doesn't always seem to be in the same environment variable, so we just check all of them - gpu_identifiers = ( - os.environ.get("SLURM_GPUS") - or os.environ.get("SLURM_GPUS_PER_TASK") - or os.environ.get("SLURM_JOB_GPUS") - or os.environ.get("SLURM_STEP_GPUS") - or len(os.environ.get("CUDA_VISIBLE_DEVICES", [])) - ) - logger.info( - f"Detected SLURM environment. SLURM Job ID: {os.environ.get('SLURM_JOB_ID')}, " - f"SLURM Host Name: {os.environ.get('SLURM_JOB_NODELIST')}, " - f"SLURM Job Name: {os.environ.get('SLURM_JOB_NAME')}, " - f"SLURM GPUS: {gpu_identifiers}" - ) - + log_slurm_info() ########### Calulate training constants ########### if args.training_goal_unit == "samples": @@ -441,7 +428,6 @@ def main(parsed_arg_groups: tuple[TrainingArgs, MiscArgs]): deterministic=misc_args.force_deterministic, callbacks=callbacks, plugins=plugins, - enable_checkpointing=True, precision=args.precision, gradient_clip_val=args.gradient_clipping, accumulate_grad_batches=args.gradient_accumulation_steps,