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231f400133
co-contributed with 夕陌&雨泓 * add torch epoch based trainer and dis utils * add hooks including optimizer, lrscheduler, logging, checkpoint, evaluation, time profiling * add torch mdoel base and test * add optimizer and lrscheduler module * add sbert for text classification example * add task_dataset for dataset-level processor Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9338412
maintain docs
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build docs
# in root directory: make docs -
doc string format
We adopt the google style docstring format as the standard, please refer to the following documents.
- Google Python style guide docstring link
- Google docstring example link
- sample：torch.nn.modules.conv link
- load function as an example：
def load(file, file_format=None, **kwargs): """Load data from json/yaml/pickle files. This method provides a unified api for loading data from serialized files. Args: file (str or :obj:`Path` or file-like object): Filename or a file-like object. file_format (str, optional): If not specified, the file format will be inferred from the file extension, otherwise use the specified one. Currently supported formats include "json", "yaml/yml". Examples: >>> load('/path/of/your/file') # file is storaged in disk >>> load('https://path/of/your/file') # file is storaged in Internet >>> load('oss://path/of/your/file') # file is storaged in petrel Returns: The content from the file. """