Web12. dec 2024. · Train a new model on one or across multiple GPUs. # We need to setup root logger before importing any fairseq libraries. if isinstance ( cfg, argparse. Namespace ): handler = logging. FileHandler ( filename=cfg. common. log_file) quantizer = quantization_utils. Quantizer (. train_meter = meters. Webfrom omegaconf import OmegaConf, open_dict: from fairseq import distributed_utils, metrics: from fairseq.dataclass.configs import FairseqConfig: from fairseq.dataclass.initialize import add_defaults, hydra_init: from fairseq.dataclass.utils import omegaconf_no_object_check: from fairseq.utils import reset_logging: from …
RobustNMT-ISDST/hydra_train.py at master - Github
WebOmegaConf is a hierarchical configuration system, with support for merging configurations from multiple sources (YAML config files, dataclasses/objects and CLI arguments) … Web23. dec 2024. · 1 Answer. Sorted by: 1. This is not supported, and is not planned to be supported in the form you are requesting. A practical solution is to split your list into two variables and concatenate them in the code. base_list: - a - b extra_list: [] train.py: ... combined_list = cfg.base_list + cfg.extra_list ... internet service for my home
omegaconf 2.2.3 on conda - Libraries.io
Web08. feb 2024. · I managed to solve this using the implementation below. It would be better to avoid importing the private interface omegaconf._impl, but I haven't yet found a way to do that. import yaml from omegaconf import OmegaConf def _subfield (key, field, _parent_): from omegaconf._impl import select_value obj = select_value (cfg=_parent_, key=key ... Web31. avg 2010. · I just discovered you can do this with argparse.ArgumentParser.parse_known_args().Start by using parse_known_args() to parse a configuration file from the commandline, then read it with ConfigParser and set the defaults, and then parse the rest of the options with parse_args().This will allow you to … Webfrom fairseq.dataclass.utils import convert_namespace_to_omegaconf: from fairseq.distributed import fsdp_enable_wrap, fsdp_wrap, utils as distributed_utils: from fairseq.file_io import PathManager: from fairseq.logging import meters, metrics, progress_bar: from fairseq.model_parallel.megatron_trainer import MegatronTrainer: … internet service for church