mindformers.trainer.ContrastiveLanguageImagePretrainTrainer

class mindformers.trainer.ContrastiveLanguageImagePretrainTrainer(model_name: Optional[str] = None)

Contrastive Language Image Pretrain Trainer.

Args:

model_name (str): The model name of Task-Trainer. Default: None

Raises:

NotImplementedError: If train method or evaluate method or predict method not implemented.

Examples:

>>> from mindformers import ContrastiveLanguageImagePretrainTrainer
>>> trainer = ContrastiveLanguageImagePretrainTrainer(model_name="clip_vit_b_b32")
>>> trainer.train()

train(config: Optional[Union[dict, MindFormerConfig, ConfigArguments, TrainingArguments]] = None, network: Optional[Union[Cell, BaseModel]] = None, dataset: Optional[Union[BaseDataset, GeneratorDataset]] = None, optimizer: Optional[Optimizer] = None, wrapper: Optional[TrainOneStepCell] = None, callbacks: Optional[Union[Callback, List[Callback]]] = None, **kwargs)

Train For Trainer.

Args:

config (Optional[Union[dict, MindFormerConfig, ConfigArguments, TrainingArguments]]):

The task config which is used to configure the dataset, the hyper-parameter, optimizer, etc. It supports config dict or MindFormerConfig or TrainingArguments or ConfigArguments class. Default: None.

network (Optional[Union[Cell, BaseModel]]): The network for trainer.

It supports model name or BaseModel or MindSpore Cell class. Default: None.

dataset (Optional[Union[BaseDataset, GeneratorDataset]]): The training dataset.

It supports real dataset path or BaseDateset class or MindSpore Dataset class. Default: None.

optimizer (Optional[Optimizer]): The optimizer used for training .Default: None. wrapper (Optional[TrainOneStepCell]): Wraps the network with the optimizer.

It support TrainOneStepCell class of MindSpore. Default: None.

callbacks (Optional[Union[Callback, List[Callback]]]): The training callback function.

It supports CallBack or CallBack List of MindSpore. Default: None.