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Moved transformations code out of column_names_dataset
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107
google/cloud/aiplatform/utils/column_transformations_utils.py
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| # -*- coding: utf-8 -*- | ||
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| # Copyright 2021 Google LLC | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| # | ||
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| from google.cloud.aiplatform import base | ||
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| from google.cloud.aiplatform.datasets.column_names_dataset import _ColumnNamesDataset | ||
| from typing import Dict, List, Optional, Union, Tuple | ||
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| import warnings | ||
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| def get_default_column_transformations( | ||
| dataset: _ColumnNamesDataset, target_column: str, | ||
| ) -> Tuple[Dict, List[str]]: | ||
| """Get default column transformations from the column names, while omitting the target column. | ||
| Args: | ||
| target_column (str): | ||
| Required. The name of the column values of which the Model is to predict. | ||
| Returns: | ||
| Dict | ||
| The default column transformations. | ||
| """ | ||
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| column_names = [ | ||
| column_name | ||
| for column_name in dataset.column_names | ||
| if column_name != target_column | ||
| ] | ||
| column_transformations = [ | ||
| {"auto": {"column_name": column_name}} for column_name in column_names | ||
| ] | ||
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| return (column_transformations, column_names) | ||
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| def validate_and_get_column_transformations( | ||
| column_specs: Optional[Dict[str, str]], | ||
| column_transformations: Optional[Union[Dict, List[Dict]]], | ||
| ) -> Dict: | ||
| """Validates column specs and transformations, then returns processed transformations. | ||
| Args: | ||
| column_specs (Dict[str, str]): | ||
| Optional. Alternative to column_transformations where the keys of the dict | ||
| are column names and their respective values are one of | ||
| AutoMLTabularTrainingJob.column_data_types. | ||
| When creating transformation for BigQuery Struct column, the column | ||
| should be flattened using "." as the delimiter. Only columns with no child | ||
| should have a transformation. | ||
| If an input column has no transformations on it, such a column is | ||
| ignored by the training, except for the targetColumn, which should have | ||
| no transformations defined on. | ||
| Only one of column_transformations or column_specs should be passed. | ||
| column_transformations (Union[Dict, List[Dict]]): | ||
| Optional. Transformations to apply to the input columns (i.e. columns other | ||
| than the targetColumn). Each transformation may produce multiple | ||
| result values from the column's value, and all are used for training. | ||
| When creating transformation for BigQuery Struct column, the column | ||
| should be flattened using "." as the delimiter. Only columns with no child | ||
| should have a transformation. | ||
| If an input column has no transformations on it, such a column is | ||
| ignored by the training, except for the targetColumn, which should have | ||
| no transformations defined on. | ||
| Only one of column_transformations or column_specs should be passed. | ||
| Consider using column_specs as column_transformations will be deprecated eventually. | ||
| Returns: | ||
| Dict | ||
| The column transformations. | ||
| """ | ||
| # user populated transformations | ||
| if column_transformations is not None and column_specs is not None: | ||
| raise ValueError( | ||
| "Both column_transformations and column_specs were passed. Only one is allowed." | ||
| ) | ||
| if column_transformations is not None: | ||
| warnings.simplefilter("always", DeprecationWarning) | ||
| warnings.warn( | ||
| "consider using column_specs instead. column_transformations will be deprecated in the future.", | ||
| DeprecationWarning, | ||
| stacklevel=2, | ||
| ) | ||
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| return column_transformations | ||
| elif column_specs is not None: | ||
| return [ | ||
| {transformation: {"column_name": column_name}} | ||
| for column_name, transformation in column_specs.items() | ||
| ] | ||
| else: | ||
| return None |