Open SarahSalimpour opened 1 year ago
Hi @SarahSalimpour, I share the command line used for testing in my environment.
conda create -y -n autoavsr python=3.8
conda activate autoavsr
pip3 install torch torchvision torchaudio
git clone <https://github.com/pytorch/fairseq>
cd fairseq
pip install --editable ./
conda install -c conda-forge ffmpeg
pip install -r requirements.txt
blessed 1.19.1 requires wcwidth>=0.1.4, which is not installed. fairseq 0.12.2 requires hydra-core<1.1,>=1.0.7, but you have hydra-core 1.3.0 which is incompatible. fairseq 0.12.2 requires omegaconf<2.1, but you have omegaconf 2.3.0 which is incompatible.
I got the above three error messages related to package compatibility issues. I tested for training and inference and both passed. Do you think it might be helpful in your case?
Thanks for your response I used the exact command lines that you mentioned. for inference, I got this error then I checked all the lines and found these related to the inference error message as follows:
`The version_base parameter is not specified. Please specify a compatability version level, or None. Will assume defaults for version 1.1 @hydra.main(config_path="conf", config_name="config") DEBUG:hydra.core.utils:Setting JobRuntime:name=UNKNOWN_NAME DEBUG:hydra.core.utils:Setting JobRuntime:name=main sys:1: UserWarning: 'config' is validated against ConfigStore schema with the same name. This behavior is deprecated in Hydra 1.1 and will be removed in Hydra 1.2. See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/automatic_schema_matching for migration instructions. /usr/local/lib/python3.10/dist-packages/hydra/main.py:90: UserWarning: 'config' is validated against ConfigStore schema with the same name. This behavior is deprecated in Hydra 1.1 and will be removed in Hydra 1.2. See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/automatic_schema_matching for migration instructions. _run_hydra( Error merging 'config' with schema Key 'exp_name' not in 'FairseqConfig' full_key: exp_name object_type=FairseqConfig
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
I found rename ‘config.yaml’ can solve the problem “Key not in FairseqConfig” . However , I happen a new problem:
Omegaconf.errors.ConfigAttributeError: key 'checkpoint' is not in struct.
Then I print the cfg, I find the cfg has key 'save_top_k' ,but no key 'checkpoint'. As the mentioned in main.py, it should be cfg.checkpoint.save_top_k
Hi @SarahSalimpour and @zyjcsf, I've just pushed a commit, can you please let me know whether the issue has been resolved
I was getting this same error, it was because I was using python3.10 instead of 3.8. Thought I'd mentioned it incase this helps anybody else.
I also have this issue, I find that renaming "config.yaml" in folder /configs works for me.
Hi Thank you for sharing the code.
For Installing additional packages in step 3.4 I got this error: ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. ipython 7.34.0 requires jedi>=0.16, which is not installed. arviz 0.15.1 requires setuptools>=60.0.0, but you have setuptools 59.5.0 which is incompatible. cvxpy 1.3.2 requires setuptools>65.5.1, but you have setuptools 59.5.0 which is incompatible. fairseq 0.12.2 requires hydra-core<1.1,>=1.0.7, but you have hydra-core 1.3.0 which is incompatible. fairseq 0.12.2 requires omegaconf<2.1, but you have omegaconf 2.3.0 which is incompatible. Successfully installed GitPython-3.1.32 antlr4-python3-runtime-4.9.3 av-10.0.0 docker-pycreds-0.4.0 gitdb-4.0.10 hydra-core-1.3.0 lightning-utilities-0.9.0 omegaconf-2.3.0 pathtools-0.1.2 pyDeprecate-0.3.1 pytorch-lightning-1.5.10 sentencepiece-0.1.99 sentry-sdk-1.29.2 setproctitle-1.3.2 setuptools-59.5.0 smmap-5.0.0 torchmetrics-1.0.3 wandb-0.15.8
Can you help me about this?