mindformers.pipeline.pipeline

mindformers.pipeline.pipeline(task: Optional[str] = None, model: Optional[Union[str, BaseModel, Model, Tuple[str, str]]] = None, tokenizer: Optional[BaseTokenizer] = None, image_processor: Optional[BaseImageProcessor] = None, audio_processor: Optional[BaseAudioProcessor] = None, backend: str = 'ms', **kwargs)

Pipeline for downstream tasks

Args:

task (str): The supported task could be selected from

MindFormerBook.show_pipeline_support_task_list().

model (Optional[Union[str, BaseModel]]): The model used for task. tokenizer (Optional[BaseTokenizer]): The tokenizer of the model. image_processor (Optional[BaseImageProcessor]): The image processor of the model. audio_processor (Optional[BaseAudioProcessor]): The audio processor of the model. backend(str): The inference backend. Default “ms”, now support [“ms”, “mslite”].

Return:

A task pipeline.

Raises:

KeyError: If the task or model is not supported.

Examples:

>>> from mindformers import pipeline
>>> from mindformers.tools.image_tools import load_image
>>> classifier = pipeline("zero_shot_image_classification",
    candidate_labels=["sunflower", "tree", "dog", "cat", "toy"])
>>> img = load_image("https://ascend-repo-modelzoo.obs.cn-east-2."
    "myhuaweicloud.com/XFormer_for_mindspore/clip/sunflower.png")
>>> classifier(img)
    [[{'score': 0.99995565, 'label': 'sunflower'},
    {'score': 2.5318595e-05, 'label': 'toy'},
    {'score': 9.903885e-06, 'label': 'dog'},
    {'score': 6.75336e-06, 'label': 'tree'},
    {'score': 2.396818e-06, 'label': 'cat'}]]