| FAIRSEQ= # Setup your fairseq directory | |
| config_dir=${FAIRSEQ}/examples/mr_hubert/config | |
| config_name=mr_hubert_base_librispeech | |
| # Prepared Data Directory | |
| data_dir=librispeech | |
| # -- data_dir | |
| # -- test.tsv | |
| # -- test.ltr | |
| # -- dict.ltr.txt | |
| exp_dir=exp # Target experiments directory (where you have your pre-trained model with checkpoint_best.pt) | |
| ratios="[1, 2]" # Default label rate ratios | |
| _opts= | |
| # If use slurm, uncomment this line and modify the job submission at | |
| # _opts="${_opts} hydra/launcher=submitit_slurm +hydra.launcher.partition=${your_slurm_partition} +run=submitit_reg" | |
| # If want to set additional experiment tag, uncomment this line | |
| # _opts="${_opts} hydra.sweep.subdir=${your_experiment_tag}" | |
| # If use un-normalized audio, uncomment this line | |
| # _opts="${_opts} task.normalize=false" | |
| PYTHONPATH=${FAIRSEQ} | |
| python examples/speech_recognition/new/infer.py \ | |
| --config-dir ${config_dir} \ | |
| --config-name infer_multires \ | |
| ${_opts} \ | |
| task.data=${data_dir} \ | |
| task.label_rate_ratios='${ratios}' \ | |
| common_eval.results_path=${exp_dir} \ | |
| common_eval.path=${exp_dir}/checkpoint_best.pt \ | |
| dataset.max_tokens=2000000 \ | |
| dataset.gen_subset=test \ | |
| dataset.skip_invalid_size_inputs_valid_test=true | |