63 lines
1.5 KiB
Python
63 lines
1.5 KiB
Python
from mlflow.protos.service_pb2 import DatasetSummary
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class _DatasetSummary:
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"""
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DatasetSummary object.
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This is used to return a list of dataset summaries across one or more experiments in the UI.
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"""
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def __init__(self, experiment_id, name, digest, context):
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self._experiment_id = experiment_id
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self._name = name
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self._digest = digest
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self._context = context
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def __eq__(self, other) -> bool:
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if type(other) is type(self):
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return self.__dict__ == other.__dict__
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return False
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@property
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def experiment_id(self):
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return self._experiment_id
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@property
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def name(self):
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return self._name
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@property
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def digest(self):
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return self._digest
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@property
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def context(self):
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return self._context
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def to_dict(self):
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return {
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"experiment_id": self.experiment_id,
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"name": self.name,
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"digest": self.digest,
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"context": self.context,
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}
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def to_proto(self):
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dataset_summary = DatasetSummary()
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dataset_summary.experiment_id = self.experiment_id
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dataset_summary.name = self.name
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dataset_summary.digest = self.digest
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if self.context:
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dataset_summary.context = self.context
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return dataset_summary
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@classmethod
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def from_proto(cls, proto):
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return cls(
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experiment_id=proto.experiment_id,
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name=proto.name,
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digest=proto.digest,
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context=proto.context,
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)
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