Adapter Utilities¶
A collection of utility methods mainly related to searching and loading adapter modules from Adapter-Hub.
- class adapters.utils.AdapterInfo(source: str, adapter_id: str, model_name: Optional[str] = None, task: Optional[str] = None, subtask: Optional[str] = None, username: Optional[str] = None, adapter_config: Optional[dict] = None, sha1_checksum: Optional[str] = None)¶
Holds information about an adapter publicly available on the Hub. Returned by
list_adapters()
.- Parameters
source (str) – The source repository of this adapter. Always ‘hf’ for adapters available on HF Model Hub.
adapter_id (str) – The unique identifier of this adapter.
model_name (str, optional) – The identifier of the model this adapter was trained for.
task (str, optional) – The task this adapter was trained for.
subtask (str, optional) – The subtask or dataset this adapter was trained on.
username (str, optional) – The username of author(s) of this adapter.
adapter_config (dict, optional) – The configuration dictionary of this adapter.
- class adapters.utils.AdapterType(value)¶
Models all currently available model adapter types.
- adapters.utils.get_adapter_config_hash(config, length=16, ignore_params=[])¶
Calculates the hash of a given adapter configuration which is used to identify this configuration.
- Returns
The resulting hash of the given config dict.
- Return type
str
- adapters.utils.get_adapter_info(adapter_id: str) Optional[AdapterInfo] ¶
Retrieves information about a specific adapter.
- Parameters
adapter_id (str) – The identifier of the adapter to retrieve.
- Returns
The adapter information or None if the adapter was not found.
- Return type
- adapters.utils.get_from_cache(url: str, cache_dir=None, force_download=False, proxies=None, etag_timeout=10, resume_download=False, user_agent: Optional[Union[Dict, str]] = None, use_auth_token: Optional[Union[bool, str]] = None, local_files_only=False) Optional[str] ¶
Given a URL, look for the corresponding file in the local cache. If it’s not there, download it. Then return the path to the cached file.
- Returns
Local path (string) of file or if networking is off, last version of file cached on disk.
- Raises
In case of non-recoverable file (non-existent or inaccessible url + no cache on disk). –
- adapters.utils.list_adapters(model_name: Optional[str] = None) List[AdapterInfo] ¶
Retrieves a list of all publicly available adapters on AdapterHub.ml or on huggingface.co.
- Parameters
model_name (str, optional) – If specified, only returns adapters trained for the model with this identifier.
- adapters.utils.parse_adapter_config_string(config_string: str) List[Tuple[str, dict]] ¶
Parses an adapter configuration string into a list of tuples. Each tuple constists of an adapter config identifier and dictionary.
- adapters.utils.prefix_attention_mask(attention_mask, dim: Union[int, List[int]] = 3, prefix_value: int = 0)¶
Adds a prefix to an attention mask. The length of the prefix is determined by the prefix_attention_mask_length attribute in the ForwardContext.
- Parameters
attention_mask – The attention mask to add the prefix to.
dim (int) – The dimension along which to concatenate the prefix_attention_mask. Defaults to 3.
prefix_value (int) – The value to use for the prefix_attention_mask. Defaults to 0, however some models, e.g. DistilBert, use different values. BERT like models invert their extended_attention_mask, hence they use 0 as value for not masked tokens. This inversion is usually done in the forward method of the model in 2 different ways: 1) by calling self.invert_attention_mask, as BERT does 2) by doing the inversion manually, e.g. ALBERT does: extended_attention_mask = (1.0 - extended_attention_mask) * torch.finfo(self.dtype).min
- adapters.utils.pull_from_hub(specifier: str, model_name: str, adapter_config: Optional[Union[dict, str]] = None, version: Optional[str] = None, strict: bool = False, **kwargs) str ¶
Redirects loading from the archived Hub repository to HuggingFace Model Hub.
- Parameters
specifier (str) – A string specifying the adapter to be loaded.
model_name (str) – The identifier of the pre-trained model for which to load an adapter.
adapter_config (Union[dict, str], optional) – The configuration of the adapter to be loaded.
version (str, optional) – The version of the adapter to be loaded. Defaults to None.
strict (bool, optional) – If set to True, only allow adapters exactly matching the given config to be loaded. Defaults to False.
- Returns
The local path to which the adapter has been downloaded.
- Return type
str
- adapters.utils.resolve_adapter_config(config: Union[dict, str], local_map=None, **kwargs) dict ¶
Resolves a given adapter configuration specifier to a full configuration dictionary.
- Parameters
config (Union[dict, str]) –
The configuration to resolve. Can be either:
a dictionary: returned without further action
an identifier string available in local_map
the path to a file containing a full adapter configuration
- Returns
The resolved adapter configuration dictionary.
- Return type
dict
- adapters.utils.resolve_adapter_path(adapter_name_or_path, model_name: Optional[str] = None, adapter_config: Optional[Union[dict, str]] = None, version: Optional[str] = None, **kwargs) str ¶
Resolves the path to a pre-trained adapter module. Note: If attempting to resolve an adapter from the Hub, adapter_config and model_name must be present.
- Parameters
adapter_name_or_path (str) –
Can be either:
the path to a folder in the file system containing the adapter configuration and weights
an url pointing to a zip folder containing the adapter configuration and weights
a specifier matching a pre-trained adapter uploaded to Adapter-Hub
model_name (str, optional) – The identifier of the pre-trained model for which to load an adapter.
adapter_config (Union[dict, str], optional) – The configuration of the adapter to be loaded.
version (str, optional) – The version of the adapter to be loaded. Defaults to None.
- Returns
The local path from where the adapter module can be loaded.
- Return type
str