towhee.trainer.modelcard.ModelCard

class towhee.trainer.modelcard.ModelCard(model_name: Optional[str] = None, model_architecture: Optional[str] = None, model_overview: Optional[str] = None, language: Optional[Union[str, List[str]]] = None, tags: Optional[Union[str, List[str]]] = None, tasks: Optional[Union[str, List[str]]] = None, datasets: Optional[Union[str, List[str]]] = None, datasets_tags: Optional[Union[str, List[str]]] = None, dataset_args: Optional[Union[str, List[str]]] = None, eval_results: Optional[Dict[str, float]] = None, eval_lines: Optional[List[str]] = None, training_summary: Optional[Dict[str, Any]] = None, training_config: Optional[TrainingConfig] = None, source: Optional[str] = 'trainer')

Bases: object

Utilities to generate and save model card. Recommended attributes from https://arxiv.org/abs/1810.03993 (see papers) https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tao/models/actionrecognitionnet

Parameters:

• model_name (Optional[str]) – model name

• model_architecture (Optional[str]) – model structure

• model_overview (Optional[str] = None) –

• language (Optional[Union[str, List[str]]]) – language

• tags (Optional[Union[str, List[str]]]) – tags

• tasks (Optional[Union[str, List[str]]]) – model tasks (eg. classification, prediction, etc.)

• datasets (Optional[Union[str, List[str]]]) – datasets used to train/test the model

• datasets_tags (Optional[Union[str, List[str]]]) – tags of datasets

• dataset_args (Optional[Union[str, List[str]]]) – arguments of dataset

• eval_results (Optional[Dict[str, float]]) – evaluation results recorded

• eval_lines (Optional[List[str]]) – evaluation baselines

• training_summary (Optional[Dict[str, Any]]) – training summary include training information

• training_config (Optional[TrainingConfig]) – training configurations

• source (Optional[str]) – source of model card (default = “trainer”)

Example

>>> from towhee.trainer.modelcard import ModelCard
>>> model_card = ModelCard(model_name='test')
>>> # Print out model name stored in model card
>>> model_card.model_name
'test'
>>> # Save model card to "path/to/my_dir" as README.md
>>> model_card.save_model_card('/path/to/my_dir')
>>> # Save model card as "/path/to/my_dir/model_card.md"
>>> model_card.save_model_card('/path/to/my_dir/model_card.md')

Methods

load_from_file
save_model_card	Write model card to the given filepath or directory
to_dict	Serializes this instance to a Python dictionary.

Attributes

dataset_args
datasets
datasets_tags
eval_lines
eval_results
language
model_architecture
model_name
model_overview
source
tags
tasks
training_config
training_summary

__init__(model_name: Optional[str] = None, model_architecture: Optional[str] = None, model_overview: Optional[str] = None, language: Optional[Union[str, List[str]]] = None, tags: Optional[Union[str, List[str]]] = None, tasks: Optional[Union[str, List[str]]] = None, datasets: Optional[Union[str, List[str]]] = None, datasets_tags: Optional[Union[str, List[str]]] = None, dataset_args: Optional[Union[str, List[str]]] = None, eval_results: Optional[Dict[str, float]] = None, eval_lines: Optional[List[str]] = None, training_summary: Optional[Dict[str, Any]] = None, training_config: Optional[TrainingConfig] = None, source: Optional[str] = 'trainer') → None

__repr__()

Return repr(self).

save_model_card(save_directory_or_file)

Write model card to the given filepath or directory

Parameters:

save_directory_or_file (str) – file path or directory to write and save model card.

to_dict()

Serializes this instance to a Python dictionary.