evaluation error

[pradeepkc11]

File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 401, in init self._accelerator_connector = _AcceleratorConnector( File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py", line 155, in init self._set_parallel_devices_and_init_accelerator() File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py", line 395, in _set_parallel_devices_and_init_accelerator self._devices_flag = accelerator_cls.parse_devices(self._devices_flag) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/accelerators/cuda.py", line 82, in parse_devices return _parse_gpu_ids(devices, include_cuda=True) File "/home/pradeep/.local/lib/python3.10/site-packages/lightning_fabric/utilities/device_parser.py", line 77, in _parse_gpu_ids _check_data_type(gpus) File "/home/pradeep/.local/lib/python3.10/site-packages/lightning_fabric/utilities/device_parser.py", line 198, in _check_data_type raise TypeError(f"{msg} None") TypeError: Device IDs (GPU/TPU) must be an int, a string, a sequence of ints, but you passed None

can any explain me how to solve this error

[ControlNet]

Could you please list the python version, lightning version and the args you used for running the scripts?

[pradeepkc11]

absl-py==2.0.0 aicsimageio==4.14.0 aiobotocore==2.5.4 aiohttp==3.8.6 aioitertools==0.11.0 aiosignal==1.3.1 albumentations==1.3.1 annotated-types==0.6.0 asciitree==0.3.3 astunparse==1.6.3 async-timeout==4.0.3 attrs==23.1.0 audioread==3.0.1 av==11.0.0 beautifulsoup4==4.12.2 blinker==1.4 blis==0.7.11 botocore==1.31.17 bottle==0.12.25 bottle-websocket==0.2.9 Brotli==1.1.0 bs4==0.0.1 cachetools==5.3.2 catalogue==2.0.10 certifi==2023.7.22 cffi==1.16.0 charset-normalizer==3.3.2 chromedriver-binary==74.0.3729.6.0 click==8.1.7 cloudpathlib==0.16.0 cloudpickle==3.0.0 cmake==3.27.7 colorama==0.4.6 command-not-found==0.3 confection==0.1.3 contourpy==1.2.0 cryptography==3.4.8 cycler==0.12.1 cymem==2.0.8 dask==2023.10.1 dbus-python==1.2.18 decorator==5.1.1 densenet-pytorch==0.2.0 distributed==2023.10.1 distro==1.7.0 distro-info===1.1build1 dlib==19.24.2 Eel==0.16.0 efficientnet-pytorch==0.7.1 einops==0.7.0 elementpath==4.1.5 et-xmlfile==1.1.0 exceptiongroup==1.1.3 fasteners==0.19 filelock==3.13.1 flatbuffers==23.5.26 fonttools==4.44.0 frozenlist==1.4.0 fsspec==2023.6.0 future==0.18.3 gast==0.5.4 gdown==4.7.1 gevent==23.9.1 gevent-websocket==0.10.1 google==3.0.0 google-auth==2.23.4 google-auth-oauthlib==1.0.0 google-pasta==0.2.0 greenlet==3.0.1 grpcio==1.59.2 h11==0.14.0 h5py==3.10.0 httplib2==0.20.2 huggingface-hub==0.18.0 idna==3.4 imagecodecs==2023.9.18 imageio==2.31.6 importlib-metadata==6.8.0 imutils==0.5.4 jeepney==0.7.1 Jinja2==3.1.2 jmespath==1.0.1 joblib==1.3.2 keras==2.14.0 keyring==23.5.0 kiwisolver==1.4.5 langcodes==3.3.0 launchpadlib==1.10.16 lazr.restfulclient==0.14.4 lazr.uri==1.0.6 lazy_loader==0.3 libclang==16.0.6 librosa==0.10.1 lightning-utilities==0.10.0 llvmlite==0.41.1 locket==1.0.0 lxml==4.9.3 Markdown==3.5.1 MarkupSafe==2.1.3 matplotlib==3.8.1 ml-dtypes==0.2.0 more-itertools==8.10.0 mpmath==1.3.0 msgpack==1.0.7 multidict==6.0.4 munch==4.0.0 murmurhash==1.0.10 mutagen==1.47.0 netifaces==0.11.0 networkx==3.2.1 nltk==3.8.1 numba==0.58.1 numcodecs==0.12.1 numpy==1.26.1 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-nccl-cu12==2.18.1 nvidia-nvjitlink-cu12==12.3.52 nvidia-nvtx-cu12==12.1.105 oauthlib==3.2.0 ome-types==0.4.2 ome-zarr==0.8.2 opencv-python==4.8.1.78 opencv-python-headless==4.8.1.78 openpyxl==3.1.2 opt-einsum==3.3.0 outcome==1.3.0.post0 packaging==23.2 pafy==0.5.5 pandas==2.1.2 partd==1.4.1 piexif==1.1.3 Pillow==10.0.1 platformdirs==3.11.0 pooch==1.8.0 preshed==3.0.9 pretrainedmodels==0.7.4 protobuf==4.23.4 psutil==5.9.6 pyasn1==0.5.0 pyasn1-modules==0.3.0 pycparser==2.21 pycryptodomex==3.19.0 pydantic==2.4.2 pydantic_core==2.10.1 pyDeprecate==0.3.2 pydub==0.25.1 PyGObject==3.42.1 PyJWT==2.3.0 pyparsing==2.4.7 PySocks==1.7.1 pyTelegramBotAPI==4.14.0 python-apt==2.4.0+ubuntu1 python-dateutil==2.8.2 pytorch-lightning @ file:///home/pradeep/pytorch_lightning-1.7.7-py3-none-any.whl#sha256=4438b8284d7f7fdb06cf3566a7b5b6f102ac8971cf7bb6d3f1b1de64628241f3 pytz==2023.3.post1 PyYAML==6.0.1 qudida==0.0.4 regex==2023.10.3 requests==2.31.0 requests-oauthlib==1.3.1 resource-backed-dask-array==0.1.0 rpycolors==0.0.5 rsa==4.9 s3fs==2023.6.0 safetensors==0.4.0 scikit-image==0.22.0 scikit-learn==1.3.2 scipy==1.11.3 searchtweets==1.7.6 SecretStorage==3.3.1 segmentation-models-pytorch==0.3.3 selenium==4.15.2 six==1.16.0 smart-open==6.4.0 sniffio==1.3.0 snscrape==0.7.0.20230622 sortedcontainers==2.4.0 soundfile==0.12.1 soupsieve==2.5 soxr==0.3.7 spacy==3.7.2 spacy-legacy==3.0.12 spacy-loggers==1.0.5 srsly==2.4.8 sympy==1.12 systemd-python==234 tblib==3.0.0 telebot==0.0.5 telegram==0.0.1 tensorboard==2.14.1 tensorboard-data-server==0.7.2 tensorflow==2.14.0 tensorflow-estimator==2.14.0 tensorflow-hub==0.15.0 tensorflow-io-gcs-filesystem==0.34.0 termcolor==2.3.0 textblob==0.17.1 thinc==8.2.1 threadpoolctl==3.2.0 tifffile==2023.2.28 timm==0.9.2 tk==0.1.0 toml==0.10.2 toolz==0.12.0 torch==2.1.1 torchaudio==2.1.1 torchmetrics==0.11.4 torchvision==0.16.0 tornado==6.3.3 tqdm==4.66.1 trio==0.23.1 trio-websocket==0.11.1 triton==2.1.0 tweepy==4.14.0 tweet-parser==1.13.2 tweety==0.1.6 typer==0.9.0 typing_extensions==4.8.0 tzdata==2023.3 ubuntu-advantage-tools==8001 ufw==0.36.1 unattended-upgrades==0.1 UNKNOWN @ git+https://github.com/JustAnotherArchivist/snscrape.git@614d4c2029a62d348ca56598f87c425966aaec66 urllib3==1.26.18 vaderSentiment==3.3.2 wadllib==1.3.6 wasabi==1.1.2 weasel==0.3.4 websockets==12.0 Werkzeug==3.0.1 whichcraft==0.6.1 wrapt==1.14.1 wsproto==1.2.0 xarray==2023.10.1 xmlschema==2.5.0 xsdata==23.8 yarl==1.9.2 youtube-dl==2021.12.17 youtube-extract==1.4.0 yt-dlp==2023.10.13 zarr==2.15.0 zict==3.0.0 zipp==1.0.0 zope.event==5.0 zope.interface==6.1

[pradeepkc11]

python3 evaluate.py --config /home/pradeep/LAV-DF/config/batfd_plus_default.toml --data_root /home/pradeep/LAV-DF/dataset --checkpoint /home/pradeep/LAV-DF/batfd_plus_default.ckpt --batch_size 1 --num_workers 4

[pradeepkc11]

I used above args to check if it works or not

[ControlNet]

Could you please try adding gpus 1

[pradeepkc11]

I set the gpus as 1 then i am getting this error

Traceback (most recent call last): File "/home/pradeep/LAV-DF/evaluate.py", line 131, in evaluate_lavdf(config, args) File "/home/pradeep/LAV-DF/evaluate.py", line 81, in evaluate_lavdf inference_batfd(model_name, model, dm, config["max_duration"], model_type, args.modalities, args.gpus) File "/home/pradeep/LAV-DF/inference.py", line 147, in inference_batfd trainer.predict(model, dm.test_dataloader()) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 949, in predict return self._call_and_handle_interrupt( File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 650, in _call_and_handle_interrupt return trainer_fn(*args, kwargs) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 996, in _predict_impl results = self._run(model, ckpt_path=self.ckpt_path) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1166, in _run results = self._run_stage() File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1251, in _run_stage return self._run_predict() File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1311, in _run_predict return self.predict_loop.run() File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/loops/loop.py", line 200, in run self.advance(*args, *kwargs) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/loops/dataloader/prediction_loop.py", line 102, in advance dl_predictions, dl_batch_indices = self.epoch_loop.run( File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/loops/loop.py", line 200, in run self.advance(args, kwargs) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/loops/epoch/prediction_epoch_loop.py", line 101, in advance self._predict_step(batch, batch_idx, dataloader_idx) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/loops/epoch/prediction_epoch_loop.py", line 137, in _predict_step self.trainer._call_callback_hooks("on_predict_batch_end", predictions, batch, batch_idx, dataloader_idx) File "/home/pradeep/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1597, in _call_callback_hooks fn(self, self.lightning_module, *args, **kwargs) File "/home/pradeep/LAV-DF/inference.py", line 74, in on_predict_batch_end self.gen_df_for_batfd_plus(fusion_bm_map[i], nullable_index(fusion_start, i), nullable_index(fusion_end, i), File "/home/pradeep/LAV-DF/inference.py", line 114, in gen_df_for_batfd_plus df = df[(df.duration > 0) & (df.end <= n_frames)] File "/home/pradeep/.local/lib/python3.10/site-packages/pandas/core/ops/common.py", line 76, in new_method return method(self, other) File "/home/pradeep/.local/lib/python3.10/site-packages/pandas/core/arraylike.py", line 52, in le return self._cmp_method(other, operator.le) File "/home/pradeep/.local/lib/python3.10/site-packages/pandas/core/series.py", line 5799, in _cmp_method res_values = ops.comparison_op(lvalues, rvalues, op) File "/home/pradeep/.local/lib/python3.10/site-packages/pandas/core/ops/array_ops.py", line 349, in comparison_op res_values = _na_arithmetic_op(lvalues, rvalues, op, is_cmp=True) File "/home/pradeep/.local/lib/python3.10/site-packages/pandas/core/ops/array_ops.py", line 220, in _na_arithmetic_op result = func(left, right) File "/home/pradeep/.local/lib/python3.10/site-packages/pandas/core/computation/expressions.py", line 242, in evaluate return _evaluate(op, op_str, a, b) # type: ignore[misc] File "/home/pradeep/.local/lib/python3.10/site-packages/pandas/core/computation/expressions.py", line 73, in _evaluate_standard return op(a, b) TypeError: '<=' not supported between instances of 'numpy.ndarray' and 'Tensor'

[ControlNet]

Thanks. Now I have reproduced the problem, and fixed in https://github.com/ControlNet/LAV-DF/commit/fa0ace9ddcce8351516ca3ec13590f73a6f102f2. Hope this can solve your problem.

[pradeepkc11]

Thanks it's solved the problem.