mindformers.pipeline.FillMaskPipeline

class mindformers.pipeline.FillMaskPipeline(model, tokenizer=None, **kwargs)

Pipeline for mask fill

Args:

model: a pretrained model (str or BaseModel) in _supproted_list. tokenizer : a tokenizer (None or Tokenizer) for text processing

forward(model_inputs, **forward_params)

Forward process

Args:

model_inputs (dict): outputs of preprocess.

Return:

probs dict.

postprocess(model_outputs, **postprocess_params)

Postprocess

Args:

model_outputs (dict): outputs of forward process.

Return:

The generated results

preprocess(inputs, **preprocess_params)

Preprocess of mask fill

Args:

inputs (url, PIL.Image, tensor, numpy): the image to be classified. max_length (int): max length of tokenizer’s output padding (False / “max_length”): padding for max_length return_tensors (“ms”): the type of returned tensors

Return:

processed image.