mindspore.dataset.Schema
- class mindspore.dataset.Schema(schema_file=None)[source]
- Class to represent a schema of a dataset. - Parameters
- schema_file (str, optional) – Path of the schema file. Default: - None.
- Raises
- RuntimeError – If schema file failed to load. 
 - Examples - >>> import mindspore.dataset as ds >>> from mindspore import dtype as mstype >>> >>> # Create schema; specify column name, mindspore.dtype and shape of the column >>> schema = ds.Schema() >>> schema.add_column(name='col1', de_type=mstype.int64, shape=[2]) - add_column(name, de_type, shape=None)[source]
- Add new column to the schema. - Parameters
- Raises
- ValueError – If column type is unknown. 
 - Examples - >>> import mindspore.dataset as ds >>> from mindspore import dtype as mstype >>> >>> schema = ds.Schema() >>> schema.add_column('col_1d', de_type=mstype.int64, shape=[2]) 
 - from_json(json_obj)[source]
- Get schema file from JSON object. - Parameters
- json_obj (dictionary) – Object of JSON parsed. 
- Raises
- RuntimeError – if there is unknown item in the object. 
- RuntimeError – if dataset type is missing in the object. 
- RuntimeError – if columns are missing in the object. 
 
 - Examples - >>> import json >>> from mindspore.dataset import Schema >>> >>> with open("/path/to/schema_file", "r") as file: ... json_obj = json.load(file) ... schema = Schema() ... schema.from_json(json_obj) 
 - parse_columns(columns)[source]
- Parse the columns and add it to self. - Parameters
- columns (Union[dict, list[dict], tuple[dict]]) – - Dataset attribute information, decoded from schema file. - list[dict], name and type must be in keys, shape optional. 
- dict, columns.keys() as name, columns.values() is dict, and type inside, shape optional. 
 
- Raises
- RuntimeError – If failed to parse columns. 
- RuntimeError – If column's name field is missing. 
- RuntimeError – If column's type field is missing. 
 
 - Examples - >>> from mindspore.dataset import Schema >>> schema = Schema() >>> columns1 = [{'name': 'image', 'type': 'int8', 'shape': [3, 3]}, ... {'name': 'label', 'type': 'int8', 'shape': [1]}] >>> schema.parse_columns(columns1) >>> columns2 = {'image': {'shape': [3, 3], 'type': 'int8'}, 'label': {'shape': [1], 'type': 'int8'}} >>> schema.parse_columns(columns2) 
 - to_json()[source]
- Get a JSON string of the schema. - Returns
- str, JSON string of the schema. 
 - Examples - >>> from mindspore.dataset import Schema >>> from mindspore import dtype as mstype >>> >>> schema = Schema() >>> schema.add_column('col_1d', de_type=mstype.int64, shape=[2]) >>> json = schema.to_json()