Is "Prepare a config file for the CLI" out of date?

[zengchang233]

Bug description

I would like to generate a config file for my project. However, when I followed the example described in Prepare a config file for the CLI, the error was raised. Is the content in the document out of date?

• error

python prepare_config.py fit --model DemoModel --print_config   
usage: prepare_config.py [options] fit [-h] [-c CONFIG] [--print_config[=flags]] [--seed_everything SEED_EVERYTHING] [--trainer CONFIG] [--trainer.accelerator.help CLASS_PATH_OR_NAME] [--trainer.accelerator ACCELERATOR] [--trainer.strategy.help CLASS_PATH_OR_NAME] [--trainer.strategy STRATEGY] [--trainer.devices DEVICES] [--trainer.num_nodes NUM_NODES]
                                       [--trainer.precision PRECISION] [--trainer.logger.help CLASS_PATH_OR_NAME] [--trainer.logger LOGGER] [--trainer.callbacks.help CLASS_PATH_OR_NAME] [--trainer.callbacks CALLBACKS] [--trainer.fast_dev_run FAST_DEV_RUN] [--trainer.max_epochs MAX_EPOCHS] [--trainer.min_epochs MIN_EPOCHS] [--trainer.max_steps MAX_STEPS]
                                       [--trainer.min_steps MIN_STEPS] [--trainer.max_time MAX_TIME] [--trainer.limit_train_batches LIMIT_TRAIN_BATCHES] [--trainer.limit_val_batches LIMIT_VAL_BATCHES] [--trainer.limit_test_batches LIMIT_TEST_BATCHES] [--trainer.limit_predict_batches LIMIT_PREDICT_BATCHES] [--trainer.overfit_batches OVERFIT_BATCHES]
                                       [--trainer.val_check_interval VAL_CHECK_INTERVAL] [--trainer.check_val_every_n_epoch CHECK_VAL_EVERY_N_EPOCH] [--trainer.num_sanity_val_steps NUM_SANITY_VAL_STEPS] [--trainer.log_every_n_steps LOG_EVERY_N_STEPS] [--trainer.enable_checkpointing {true,false,null}] [--trainer.enable_progress_bar {true,false,null}]
                                       [--trainer.enable_model_summary {true,false,null}] [--trainer.accumulate_grad_batches ACCUMULATE_GRAD_BATCHES] [--trainer.gradient_clip_val GRADIENT_CLIP_VAL] [--trainer.gradient_clip_algorithm GRADIENT_CLIP_ALGORITHM] [--trainer.deterministic DETERMINISTIC] [--trainer.benchmark {true,false,null}] [--trainer.inference_mode {true,false}]
                                       [--trainer.use_distributed_sampler {true,false}] [--trainer.profiler.help CLASS_PATH_OR_NAME] [--trainer.profiler PROFILER] [--trainer.detect_anomaly {true,false}] [--trainer.barebones {true,false}] [--trainer.plugins.help CLASS_PATH_OR_NAME] [--trainer.plugins PLUGINS] [--trainer.sync_batchnorm {true,false}]
                                       [--trainer.reload_dataloaders_every_n_epochs RELOAD_DATALOADERS_EVERY_N_EPOCHS] [--trainer.default_root_dir DEFAULT_ROOT_DIR] [--model CONFIG] [--model.out_dim OUT_DIM] [--model.learning_rate LEARNING_RATE] [--optimizer.help CLASS_PATH_OR_NAME] [--optimizer CONFIG | CLASS_PATH_OR_NAME | .INIT_ARG_NAME VALUE]
                                       [--lr_scheduler.help CLASS_PATH_OR_NAME] [--lr_scheduler CONFIG | CLASS_PATH_OR_NAME | .INIT_ARG_NAME VALUE] [--ckpt_path CKPT_PATH]
error: Parser key "model":
Unable to load config 'DemoModel'
  - Parser key "model": Unable to load config "DemoModel"

What version are you seeing the problem on?

v2.2

How to reproduce the bug

from lightning.pytorch.cli import LightningCLI
from lightning.pytorch.demos.boring_classes import DemoModel, BoringDataModule

def main():
    cli = LightningCLI(DemoModel, BoringDataModule)

if __name__ == "__main__":
    main()

python prepare_config.py fit --model DemoModel --print_config 

Error messages and logs

python prepare_config.py fit --model DemoModel --print_config   
usage: prepare_config.py [options] fit [-h] [-c CONFIG] [--print_config[=flags]] [--seed_everything SEED_EVERYTHING] [--trainer CONFIG] [--trainer.accelerator.help CLASS_PATH_OR_NAME] [--trainer.accelerator ACCELERATOR] [--trainer.strategy.help CLASS_PATH_OR_NAME] [--trainer.strategy STRATEGY] [--trainer.devices DEVICES] [--trainer.num_nodes NUM_NODES]
                                       [--trainer.precision PRECISION] [--trainer.logger.help CLASS_PATH_OR_NAME] [--trainer.logger LOGGER] [--trainer.callbacks.help CLASS_PATH_OR_NAME] [--trainer.callbacks CALLBACKS] [--trainer.fast_dev_run FAST_DEV_RUN] [--trainer.max_epochs MAX_EPOCHS] [--trainer.min_epochs MIN_EPOCHS] [--trainer.max_steps MAX_STEPS]
                                       [--trainer.min_steps MIN_STEPS] [--trainer.max_time MAX_TIME] [--trainer.limit_train_batches LIMIT_TRAIN_BATCHES] [--trainer.limit_val_batches LIMIT_VAL_BATCHES] [--trainer.limit_test_batches LIMIT_TEST_BATCHES] [--trainer.limit_predict_batches LIMIT_PREDICT_BATCHES] [--trainer.overfit_batches OVERFIT_BATCHES]
                                       [--trainer.val_check_interval VAL_CHECK_INTERVAL] [--trainer.check_val_every_n_epoch CHECK_VAL_EVERY_N_EPOCH] [--trainer.num_sanity_val_steps NUM_SANITY_VAL_STEPS] [--trainer.log_every_n_steps LOG_EVERY_N_STEPS] [--trainer.enable_checkpointing {true,false,null}] [--trainer.enable_progress_bar {true,false,null}]
                                       [--trainer.enable_model_summary {true,false,null}] [--trainer.accumulate_grad_batches ACCUMULATE_GRAD_BATCHES] [--trainer.gradient_clip_val GRADIENT_CLIP_VAL] [--trainer.gradient_clip_algorithm GRADIENT_CLIP_ALGORITHM] [--trainer.deterministic DETERMINISTIC] [--trainer.benchmark {true,false,null}] [--trainer.inference_mode {true,false}]
                                       [--trainer.use_distributed_sampler {true,false}] [--trainer.profiler.help CLASS_PATH_OR_NAME] [--trainer.profiler PROFILER] [--trainer.detect_anomaly {true,false}] [--trainer.barebones {true,false}] [--trainer.plugins.help CLASS_PATH_OR_NAME] [--trainer.plugins PLUGINS] [--trainer.sync_batchnorm {true,false}]
                                       [--trainer.reload_dataloaders_every_n_epochs RELOAD_DATALOADERS_EVERY_N_EPOCHS] [--trainer.default_root_dir DEFAULT_ROOT_DIR] [--model CONFIG] [--model.out_dim OUT_DIM] [--model.learning_rate LEARNING_RATE] [--optimizer.help CLASS_PATH_OR_NAME] [--optimizer CONFIG | CLASS_PATH_OR_NAME | .INIT_ARG_NAME VALUE]
                                       [--lr_scheduler.help CLASS_PATH_OR_NAME] [--lr_scheduler CONFIG | CLASS_PATH_OR_NAME | .INIT_ARG_NAME VALUE] [--ckpt_path CKPT_PATH]
error: Parser key "model":
Unable to load config 'DemoModel'
  - Parser key "model": Unable to load config "DemoModel"

Environment

Current environment

• CUDA: - GPU: - NVIDIA GeForce RTX 4090 - NVIDIA GeForce RTX 4090 - NVIDIA GeForce RTX 4090 - NVIDIA GeForce RTX 4090 - NVIDIA GeForce RTX 4090 - NVIDIA GeForce RTX 4090 - NVIDIA GeForce RTX 4090 - NVIDIA GeForce RTX 4090 - available: True - version: 12.1
• Lightning: - lightning: 2.2.1 - lightning-utilities: 0.11.2 - pytorch-lightning: 2.2.4 - torch: 2.2.0+cu121 - torch-complex: 0.4.3 - torchaudio: 2.2.0+cu121 - torchdiffeq: 0.2.3 - torchmetrics: 1.4.0 - torchvision: 0.17.0+cu121
• Packages: - absl-py: 2.1.0 - aiohttp: 3.9.5 - aiosignal: 1.3.1 - annotated-types: 0.6.0 - antlr4-python3-runtime: 4.9.3 - anyio: 4.3.0 - appdirs: 1.4.4 - argon2-cffi: 23.1.0 - argon2-cffi-bindings: 21.2.0 - arrow: 1.3.0 - asteroid-filterbanks: 0.4.0 - asttokens: 2.4.1 - async-lru: 2.0.4 - async-timeout: 4.0.3 - attrs: 23.2.0 - audioread: 3.0.1 - babel: 2.15.0 - beautifulsoup4: 4.12.3 - bleach: 6.1.0 - cachetools: 5.3.3 - certifi: 2024.2.2 - cffi: 1.16.0 - charset-normalizer: 3.3.2 - ci-sdr: 0.0.2 - click: 8.1.7 - colorama: 0.4.6 - comm: 0.2.2 - configargparse: 1.7 - contourpy: 1.2.1 - ctc-segmentation: 1.7.4 - cycler: 0.12.1 - cython: 3.0.10 - debugpy: 1.8.1 - decorator: 5.1.1 - defusedxml: 0.7.1 - distance: 0.1.3 - docker-pycreds: 0.4.0 - docstring-parser: 0.16 - editdistance: 0.8.1 - einops: 0.8.0 - encodec: 0.1.1 - espnet: 202402 - espnet-tts-frontend: 0.0.3 - exceptiongroup: 1.2.1 - executing: 2.0.1 - fast-bss-eval: 0.1.3 - fastjsonschema: 2.19.1 - filelock: 3.14.0 - fonttools: 4.51.0 - fqdn: 1.5.1 - frozenlist: 1.4.1 - fsspec: 2024.3.1 - g2p-en: 2.1.0 - gitdb: 4.0.11 - gitpython: 3.1.43 - google-auth: 2.29.0 - google-auth-oauthlib: 0.4.6 - grpcio: 1.63.0 - h11: 0.14.0 - h5py: 3.11.0 - httpcore: 1.0.5 - httpx: 0.27.0 - huggingface-hub: 0.20.1 - humanfriendly: 10.0 - hydra-core: 1.3.2 - idna: 3.7 - importlib-metadata: 4.13.0 - importlib-resources: 6.4.0 - inflect: 7.0.0 - ipdb: 0.13.13 - ipykernel: 6.29.4 - ipython: 8.24.0 - ipywidgets: 8.1.2 - isoduration: 20.11.0 - jaconv: 0.3.4 - jamo: 0.4.1 - jedi: 0.19.1 - jinja2: 3.1.4 - joblib: 1.4.2 - json5: 0.9.25 - jsonargparse: 4.28.0 - jsonpointer: 2.4 - jsonschema: 4.22.0 - jsonschema-specifications: 2023.12.1 - julius: 0.2.7 - jupyter: 1.0.0 - jupyter-client: 8.6.1 - jupyter-console: 6.6.3 - jupyter-core: 5.7.2 - jupyter-events: 0.10.0 - jupyter-lsp: 2.2.5 - jupyter-server: 2.14.0 - jupyter-server-terminals: 0.5.3 - jupyterlab: 4.2.0 - jupyterlab-pygments: 0.3.0 - jupyterlab-server: 2.27.1 - jupyterlab-widgets: 3.0.10 - kaldiio: 2.18.0 - kiwisolver: 1.4.5 - librosa: 0.9.2 - lightning: 2.2.1 - lightning-utilities: 0.11.2 - llvmlite: 0.42.0 - markdown: 3.6 - markupsafe: 2.1.5 - matplotlib: 3.8.4 - matplotlib-inline: 0.1.7 - mistune: 3.0.2 - mpmath: 1.3.0 - multidict: 6.0.5 - nbclient: 0.10.0 - nbconvert: 7.16.4 - nbformat: 5.10.4 - nest-asyncio: 1.6.0 - networkx: 3.3 - nltk: 3.8.1 - notebook: 7.2.0 - notebook-shim: 0.2.4 - numba: 0.59.1 - numpy: 1.23.5 - nvidia-cublas-cu12: 12.1.3.1 - nvidia-cuda-cupti-cu12: 12.1.105 - nvidia-cuda-nvrtc-cu12: 12.1.105 - nvidia-cuda-runtime-cu12: 12.1.105 - nvidia-cudnn-cu12: 8.9.2.26 - nvidia-cufft-cu12: 11.0.2.54 - nvidia-curand-cu12: 10.3.2.106 - nvidia-cusolver-cu12: 11.4.5.107 - nvidia-cusparse-cu12: 12.1.0.106 - nvidia-ml-py: 12.535.161 - nvidia-nccl-cu12: 2.19.3 - nvidia-nvjitlink-cu12: 12.4.127 - nvidia-nvtx-cu12: 12.1.105 - nvitop: 1.3.2 - oauthlib: 3.2.2 - omegaconf: 2.3.0 - opt-einsum: 3.3.0 - overrides: 7.7.0 - packaging: 24.0 - pandas: 2.2.2 - pandocfilters: 1.5.1 - parso: 0.8.4 - pathtools: 0.1.2 - pexpect: 4.9.0 - pillow: 10.3.0 - pip: 24.0 - platformdirs: 4.2.1 - pooch: 1.8.1 - pretty-errors: 1.2.25 - prometheus-client: 0.20.0 - prompt-toolkit: 3.0.43 - protobuf: 3.19.6 - psutil: 5.9.8 - ptyprocess: 0.7.0 - pure-eval: 0.2.2 - pyasn1: 0.6.0 - pyasn1-modules: 0.4.0 - pycparser: 2.22 - pydantic: 2.7.1 - pydantic-core: 2.18.2 - pygments: 2.18.0 - pyparsing: 3.1.2 - pypinyin: 0.44.0 - python-dateutil: 2.9.0.post0 - python-json-logger: 2.0.7 - pytorch-lightning: 2.2.4 - pytz: 2024.1 - pyworld: 0.3.4 - pyyaml: 6.0.1 - pyzmq: 26.0.3 - qtconsole: 5.5.2 - qtpy: 2.4.1 - referencing: 0.35.1 - regex: 2024.5.10 - requests: 2.31.0 - requests-oauthlib: 2.0.0 - resampy: 0.4.3 - rfc3339-validator: 0.1.4 - rfc3986-validator: 0.1.1 - rpds-py: 0.18.1 - rsa: 4.9 - safetensors: 0.4.3 - scikit-learn: 1.4.2 - scipy: 1.13.0 - send2trash: 1.8.3 - sentencepiece: 0.1.97 - sentry-sdk: 2.1.1 - setproctitle: 1.3.3 - setuptools: 69.5.1 - six: 1.16.0 - smmap: 5.0.1 - sniffio: 1.3.1 - soundfile: 0.12.1 - soupsieve: 2.5 - stack-data: 0.6.3 - sympy: 1.12 - tensorboard: 2.9.1 - tensorboard-data-server: 0.6.1 - tensorboard-plugin-wit: 1.8.1 - termcolor: 2.4.0 - terminado: 0.18.1 - threadpoolctl: 3.5.0 - tinycss2: 1.3.0 - tokenizers: 0.13.3 - tomli: 2.0.1 - torch: 2.2.0+cu121 - torch-complex: 0.4.3 - torchaudio: 2.2.0+cu121 - torchdiffeq: 0.2.3 - torchmetrics: 1.4.0 - torchvision: 0.17.0+cu121 - tornado: 6.4 - tqdm: 4.66.4 - traitlets: 5.14.3 - transformers: 4.31.0 - triton: 2.2.0 - typeguard: 2.13.3 - types-python-dateutil: 2.9.0.20240316 - typeshed-client: 2.5.1 - typing-extensions: 4.11.0 - tzdata: 2024.1 - unidecode: 1.3.8 - uri-template: 1.3.0 - urllib3: 2.2.1 - wandb: 0.15.8 - wcwidth: 0.2.13 - webcolors: 1.13 - webencodings: 0.5.1 - websocket-client: 1.8.0 - werkzeug: 3.0.3 - wheel: 0.43.0 - widgetsnbextension: 4.0.10 - xformers: 0.0.24 - yarl: 1.9.4 - zipp: 3.18.1
• System: - OS: Linux - architecture: - 64bit - ELF - processor: x86_64 - python: 3.10.14 - release: 5.10.101-1.el8.ssai.x86_64 - version: #1 SMP Mon Apr 25 12:35:34 UTC 2022

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