mindformers.AutoProcessor

class mindformers.AutoProcessor

helps instantiates a processor by yaml model name or path. If using a model name, the config yaml will be downloaded from obs to ./checkpoint_download dir

Examples:

>>> from mindformers.auto_class import AutoProcessor
>>>
>>> # 1)  instantiates a processor by yaml model name
>>> pro_a = AutoProcessor.from_pretrained('clip_vit_b_32')
>>> # 2)  instantiates a processor by yaml model path
>>> from mindformers.mindformer_book import MindFormerBook
>>> config_path = os.path.join(MindFormerBook.get_project_path(),
...                            'configs', 'clip', 'run_clip_vit_b_32_pretrain_flickr8k.yaml')
>>> pro_b = AutoProcessor.from_pretrained(config_path)

classmethod from_pretrained(yaml_name_or_path, **kwargs)

From pretrain method, which instantiated a processor by yaml name or path.

Args:

yaml_name_or_path (str): A supported yaml name or a path to .yaml file,

the supported model name could be selected from .show_support_list(). If yaml_name_or_path is model name, it supports model names beginning with mindspore or the model name itself, such as “mindspore/vit_base_p16” or “vit_base_p16”.

pretrained_model_name_or_path (Optional[str]): Equal to “yaml_name_or_path”,

if “pretrained_model_name_or_path” is set, “yaml_name_or_path” is useless.

Returns:

A processor which inherited from BaseProcessor.

classmethod get_support_list()

get support list method

classmethod invalid_yaml_name(yaml_name_or_path)

Check whether it is a valid yaml name

classmethod show_support_list()

show support list method