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@ -26,8 +26,7 @@ from .shardheader import ShardHeader
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from .shardindexgenerator import ShardIndexGenerator
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from .shardutils import MIN_SHARD_COUNT, MAX_SHARD_COUNT, VALID_ATTRIBUTES, VALID_ARRAY_ATTRIBUTES, \
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check_filename, VALUE_TYPE_MAP
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from .common.exceptions import ParamValueError, ParamTypeError, MRMInvalidSchemaError, MRMDefineIndexError, \
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MRMValidateDataError
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from .common.exceptions import ParamValueError, ParamTypeError, MRMInvalidSchemaError, MRMDefineIndexError
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__all__ = ['FileWriter']
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@ -201,52 +200,13 @@ class FileWriter:
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raw_data.pop(i)
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logger.warning(v)
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def _verify_based_on_blob_fields(self, raw_data):
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def write_raw_data(self, raw_data):
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"""
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Verify data according to blob fields which is sub set of schema's fields.
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Raise exception if validation failed.
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1) allowed data type contains: "int32", "int64", "float32", "float64", "string", "bytes".
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Args:
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raw_data (list[dict]): List of raw data.
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Raises:
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MRMValidateDataError: If data does not match blob fields.
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"""
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schema_content = self._header.schema
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for field in schema_content:
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for i, v in enumerate(raw_data):
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if field not in v:
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raise MRMValidateDataError("for schema, {} th data is wrong: "\
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"there is not '{}' object in the raw data.".format(i, field))
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if field in self._header.blob_fields:
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field_type = type(v[field]).__name__
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if field_type not in VALUE_TYPE_MAP:
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raise MRMValidateDataError("for schema, {} th data is wrong: "\
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"data type for '{}' is not matched.".format(i, field))
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if schema_content[field]["type"] not in VALUE_TYPE_MAP[field_type]:
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raise MRMValidateDataError("for schema, {} th data is wrong: "\
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"data type for '{}' is not matched.".format(i, field))
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if field_type == 'ndarray':
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if 'shape' not in schema_content[field]:
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raise MRMValidateDataError("for schema, {} th data is wrong: " \
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"data type for '{}' is not matched.".format(i, field))
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try:
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# tuple or list
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np.reshape(v[field], schema_content[field]['shape'])
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except ValueError:
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raise MRMValidateDataError("for schema, {} th data is wrong: " \
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"data type for '{}' is not matched.".format(i, field))
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def write_raw_data(self, raw_data, validate=True):
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"""
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Write raw data and generate sequential pair of MindRecord File.
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Write raw data and generate sequential pair of MindRecord File and \
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validate data based on predefined schema by default.
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Args:
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raw_data (list[dict]): List of raw data.
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validate (bool, optional): Validate data according schema if it equals to True,
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or validate data according to blob fields (default=True).
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Raises:
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ParamTypeError: If index field is invalid.
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@ -264,11 +224,8 @@ class FileWriter:
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for each_raw in raw_data:
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if not isinstance(each_raw, dict):
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raise ParamTypeError('raw_data item', 'dict')
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if validate is True:
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self._verify_based_on_schema(raw_data)
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elif validate is False:
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self._verify_based_on_blob_fields(raw_data)
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return self._writer.write_raw_data(raw_data, validate)
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self._verify_based_on_schema(raw_data)
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return self._writer.write_raw_data(raw_data, True)
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def set_header_size(self, header_size):
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"""
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