From 3ff70a92f90e377e9c31e8d62f737bfa8935d74c Mon Sep 17 00:00:00 2001 From: Jineet Desai Date: Thu, 28 Sep 2023 00:30:18 -0400 Subject: [PATCH] Starting the change for XGBoost integration into EVADb. --- evadb/binder/statement_binder.py | 4 +- evadb/executor/create_function_executor.py | 61 +++++++++++++++++++ evadb/functions/xgboost.py | 47 ++++++++++++++ evadb/utils/generic_utils.py | 10 +++ .../long/test_model_train.py | 16 +++++ 5 files changed, 137 insertions(+), 1 deletion(-) create mode 100644 evadb/functions/xgboost.py diff --git a/evadb/binder/statement_binder.py b/evadb/binder/statement_binder.py index 199c535181..41ecd32935 100644 --- a/evadb/binder/statement_binder.py +++ b/evadb/binder/statement_binder.py @@ -101,7 +101,9 @@ def _bind_create_function_statement(self, node: CreateFunctionStatement): outputs.append(column) else: inputs.append(column) - elif string_comparison_case_insensitive(node.function_type, "sklearn"): + elif string_comparison_case_insensitive( + node.function_type, "sklearn" + ) or string_comparison_case_insensitive(node.function_type, "XGBoost"): assert ( "predict" in arg_map ), f"Creating {node.function_type} functions expects 'predict' metadata." diff --git a/evadb/executor/create_function_executor.py b/evadb/executor/create_function_executor.py index 8f4b5ad274..13b3df215d 100644 --- a/evadb/executor/create_function_executor.py +++ b/evadb/executor/create_function_executor.py @@ -38,6 +38,8 @@ from evadb.utils.generic_utils import ( load_function_class_from_file, string_comparison_case_insensitive, + try_to_import_automl, + try_to_import_forecast, try_to_import_ludwig, try_to_import_neuralforecast, try_to_import_sklearn, @@ -163,6 +165,57 @@ def handle_sklearn_function(self): self.node.metadata, ) + def handle_xgboost_function(self): + """Handle xgboost functions + + We use the Flaml AutoML model for training xgboost models. + """ + try_to_import_automl() + + assert ( + len(self.children) == 1 + ), "Create sklearn function expects 1 child, finds {}.".format( + len(self.children) + ) + + aggregated_batch_list = [] + child = self.children[0] + for batch in child.exec(): + aggregated_batch_list.append(batch) + aggregated_batch = Batch.concat(aggregated_batch_list, copy=False) + aggregated_batch.drop_column_alias() + + arg_map = {arg.key: arg.value for arg in self.node.metadata} + from flaml import AutoML + + model = AutoML() + settings = { + "time_budget": 120, + "metric": "r2", + "estimator_list": ["xgboost"], + "task": "regression", + } + model.fit( + dataframe=aggregated_batch.frames, label=arg_map["predict"], **settings + ) + model_path = os.path.join( + self.db.config.get_value("storage", "model_dir"), self.node.name + ) + pickle.dump(model, open(model_path, "wb")) + self.node.metadata.append( + FunctionMetadataCatalogEntry("model_path", model_path) + ) + + impl_path = Path(f"{self.function_dir}/xgboost.py").absolute().as_posix() + io_list = self._resolve_function_io(None) + return ( + self.node.name, + impl_path, + self.node.function_type, + io_list, + self.node.metadata, + ) + def handle_ultralytics_function(self): """Handle Ultralytics functions""" try_to_import_ultralytics() @@ -516,6 +569,14 @@ def exec(self, *args, **kwargs): io_list, metadata, ) = self.handle_sklearn_function() + elif string_comparison_case_insensitive(self.node.function_type, "XGBoost"): + ( + name, + impl_path, + function_type, + io_list, + metadata, + ) = self.handle_xgboost_function() elif string_comparison_case_insensitive(self.node.function_type, "Forecasting"): ( name, diff --git a/evadb/functions/xgboost.py b/evadb/functions/xgboost.py new file mode 100644 index 0000000000..f09045a502 --- /dev/null +++ b/evadb/functions/xgboost.py @@ -0,0 +1,47 @@ +# coding=utf-8 +# Copyright 2018-2023 EvaDB +# +# 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. +import pickle + +import pandas as pd + +from evadb.functions.abstract.abstract_function import AbstractFunction +from evadb.utils.generic_utils import try_to_import_automl + + +class GenericXGBoostModel(AbstractFunction): + @property + def name(self) -> str: + return "GenericXGBoostModel" + + def setup(self, model_path: str, **kwargs): + try_to_import_automl() + + self.model = pickle.load(open(model_path, "rb")) + + def forward(self, frames: pd.DataFrame) -> pd.DataFrame: + # Last column is the value to predict, hence don't pass that to the + # predict method. + predictions = self.model.predict(frames.iloc[:, :-1]) + predict_df = pd.DataFrame(predictions) + # We need to rename the column of the output dataframe. For this we + # shall rename it to the column name same as that of the last column of + # frames. This is because the last column of frames corresponds to the + # variable we want to predict. + predict_df.rename(columns={0: frames.columns[-1]}, inplace=True) + return predict_df + + def to_device(self, device: str): + # TODO figure out how to control the GPU for ludwig models + return self diff --git a/evadb/utils/generic_utils.py b/evadb/utils/generic_utils.py index 04b6add1f9..5355830231 100644 --- a/evadb/utils/generic_utils.py +++ b/evadb/utils/generic_utils.py @@ -376,6 +376,16 @@ def is_sklearn_available() -> bool: except ValueError: # noqa: E722 return False +def try_to_import_automl(): + try: + import flaml # noqa: F401 + from flaml import AutoML # noqa: F401 + except ImportError: + raise ValueError( + """Could not import Flaml AutoML. + Please install it with `pip install "flaml[automl]"`.""" + ) + ############################## ## VISION diff --git a/test/integration_tests/long/test_model_train.py b/test/integration_tests/long/test_model_train.py index 7424ba424e..08c00213dc 100644 --- a/test/integration_tests/long/test_model_train.py +++ b/test/integration_tests/long/test_model_train.py @@ -95,6 +95,22 @@ def test_sklearn_regression(self): self.assertEqual(len(result.columns), 1) self.assertEqual(len(result), 10) + def test_xgboost_regression(self): + create_predict_function = """ + CREATE FUNCTION IF NOT EXISTS PredictRent FROM + ( SELECT number_of_rooms, number_of_bathrooms, days_on_market, rental_price FROM HomeRentals ) + TYPE XGBoost + PREDICT 'rental_price'; + """ + execute_query_fetch_all(self.evadb, create_predict_function) + + predict_query = """ + SELECT PredictRent(number_of_rooms, number_of_bathrooms, days_on_market, rental_price) FROM HomeRentals LIMIT 10; + """ + result = execute_query_fetch_all(self.evadb, predict_query) + self.assertEqual(len(result.columns), 1) + self.assertEqual(len(result), 10) + if __name__ == "__main__": unittest.main()