PiRddlZddlZddlZddlmZmZmZmZddlm Z m Z ddl m Z ddl mZmZdedefdeedfd eeefd efd Zd eeefded efd Zde ded ed efdZdS)N)AnyCallableDictTuple) DictConfig OmegaConf)InstantiationError)_get_component_from_path_has_component _component_.argskwargsreturnc||i|S)N)r r rs q/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/torchtune/config/_instantiate.py_create_componentrs ; ' ' ''nodect|rQt|d}d|D}t |||St d)z Creates the object specified in _component_ field with provided positional args and kwargs already merged. Raises an InstantiationError if _component_ is not specified. r c&i|]\}}|dk ||S)r r).0kvs r z%_instantiate_node.. s(FFF41a1 3E3E!Q3E3E3ErziCannot instantiate specified object. Make sure you've specified a _component_ field with a valid dotpath.)r r getitemsrr )rr r rs r_instantiate_nodersr d .txx /F/FGG FF4::<<FFF dF;;;  W   rconfigcR|dStj|stdt|t jt jvr0t jt jtj |}| gdgd| | |}|rtj||}tj|t!tj|g|RS)aT Given a DictConfig with a _component_ field specifying the object to instantiate and additional fields for keyword arguments, create an instance of the specified object. You can use this function to create the exact instance of a torchtune object you want to use in your recipe using the specification from the config. This function also supports passing in positional args and keyword args within the function call. These are automatically merged with the provided config, with keyword args taking precedence. Based on Hydra's `instantiate` utility from Facebook Research: https://github.com/facebookresearch/hydra/blob/main/hydra/_internal/instantiate/_instantiate2.py#L148 Args: config (DictConfig): a single field in the OmegaConf object parsed from the yaml file. This is expected to have a _component_ field specifying the path of the object to instantiate. *args (Any): positional arguments to pass to the object to instantiate. **kwargs (Any): keyword arguments to pass to the object to instantiate. Examples: >>> config.yaml: >>> model: >>> _component_: torchtune.models.llama2 >>> num_layers: 32 >>> num_heads: 32 >>> num_kv_heads: 32 >>> from torchtune import config >>> vocab_size = 32000 >>> # Pass in vocab size as positional argument. Since it is positioned first >>> # in llama2(), it must be specified first. Pass in other arguments as kwargs. >>> # This will return an nn.Module directly for llama2 with specified args. >>> model = config.instantiate(parsed_yaml.model, vocab_size, max_seq_len=4096, embed_dim=4096) Returns: Any: the instantiated object. Raises: ValueError: if config is not a DictConfig. Nz+instantiate only supports DictConfigs, got ) allow_objectsstructreadonly)TFF)flagsvalues)ris_dict ValueErrortypeosgetcwdsyspathappendcopydeepcopy _set_flag _set_parent _get_parentmergeresolver to_object)rr r config_copys r instantiater7)s!`~t  V $ $WUtF||UUVVV y{{#(""  $$$-''K555>R>R>RF..00111 F 100f Y088 @4 @ @ @@r)r.r)r+typingrrrr omegaconfrrtorchtune.config._errorsr torchtune.config._utilsr r strrrr7rrrr=s` ------------++++++++777777LLLLLLLL(#s(#( S/( cN( ((((  DcN  3  3     GA GA GAGA GAGAGAGAGAGAr