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73 行
2.6 KiB
Python
73 行
2.6 KiB
Python
# Copyright (c) 2022 Predibase, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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from ludwig.api_annotations import PublicAPI
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@PublicAPI
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class LudwigError(Exception):
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"""Base class for all custom exceptions raised by the Ludwig framework."""
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def __reduce__(self):
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"""Docs: https://docs.python.org/3/library/pickle.html#object.__reduce__."""
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raise NotImplementedError(
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"Implement __reduce__ for all subclasses of LudwigError as it's necessary for "
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"serialization by Ray. See https://github.com/ludwig-ai/ludwig/pull/2695."
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)
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@PublicAPI
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class InputDataError(LudwigError, ValueError):
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"""Exception raised for errors in the input data.
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Appropriate for data which is not convertible to the input feature type, columns with all missing values,
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categorical columns with only one category, etc...
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Attributes:
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column - The name of the input column which caused the error
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feature_type - The Ludwig feature type which caused the error (number, binary, category...).
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message - An error message describing the situation.
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"""
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def __init__(self, column_name: str, feature_type: str, message: str):
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self.column_name = column_name
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self.feature_type = feature_type
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self.message = message
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super().__init__(message)
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def __str__(self):
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return f'Column "{self.column_name}" as {self.feature_type} feature: {self.message}'
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def __reduce__(self):
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return type(self), (self.column_name, self.feature_type, self.message)
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@PublicAPI
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class ConfigValidationError(LudwigError, ValueError):
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"""Exception raised for errors in the Ludwig configuration.
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Appropriate for bad configuration values, missing required configuration values, etc...
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Attributes:
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message - An error message describing the situation.
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"""
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def __init__(self, message: str):
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self.message = message
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super().__init__(message)
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def __reduce__(self):
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return type(self), (self.message,)
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