



'''simple docstring'''






import pytest


lowerCAmelCase:      Tuple		 =		"""__dummy_dataset1__"""

lowerCAmelCase:      List[Any]		 =		"""
import json
import os

import datasets


REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": REPO_URL + \"wikiann-bn-validation.jsonl\"}


class __DummyDataset1__(datasets.GeneratorBasedBuilder):

    def _info(self):
        features = datasets.Features(
            {
                \"tokens\": datasets.Sequence(datasets.Value(\"string\")),
                \"ner_tags\": datasets.Sequence(
                    datasets.features.ClassLabel(
                        names=[
                            \"O\",
                            \"B-PER\",
                            \"I-PER\",
                            \"B-ORG\",
                            \"I-ORG\",
                            \"B-LOC\",
                            \"I-LOC\",
                        ]
                    )
                ),
                \"langs\": datasets.Sequence(datasets.Value(\"string\")),
                \"spans\": datasets.Sequence(datasets.Value(\"string\")),
            }
        )
        return datasets.DatasetInfo(features=features)

    def _split_generators(self, dl_manager):
        dl_path = dl_manager.download(URLS)
        return [
            datasets.SplitGenerator(datasets.Split.TRAIN, gen_kwargs={\"filepath\": dl_path[\"train\"]}),
            datasets.SplitGenerator(datasets.Split.VALIDATION, gen_kwargs={\"filepath\": dl_path[\"validation\"]}),
        ]

    def _generate_examples(self, filepath):
        with open(filepath, \"r\", encoding=\"utf-8\") as f:
            for i, line in enumerate(f):
                yield i, json.loads(line)
"""
@pytest.fixture
def    lowerCamelCase__ (		):
  return DATASET_LOADING_SCRIPT_NAME
@pytest.fixture
def    lowerCamelCase__ (		):
  return DATASET_LOADING_SCRIPT_CODE

@pytest.fixture
def    lowerCamelCase__ (		_A				,    _A				,    _A       ):
  a		:      Any       =  dataset_loading_script_name
  a		:      Dict       =  tmp_path / "datasets" / script_name
  script_dir.mkdir(parents=snake_case_       )
  a		:      Dict       =  script_dir / f"""{script_name}.py"""
  with open(snake_case_				,    'w'       ) as f:
    f.write(snake_case_       )
  return str(snake_case_       )




'''simple docstring'''






import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def    lowerCamelCase__ (		_A       ):
  return (data["data"], data["target"])
def    lowerCamelCase__ (		_A				,    _A				,    _A       ):
  a		:      Any       =  XGBRegressor(verbosity=0				,    random_state=42       )
  xgb.fit(_A				,    _A       )
  # Predict target for test data
  a		:      Any       =  xgb.predict(_A       )
  a		:      Any       =  predictions.reshape(len(_A       )				,    1       )
  return predictions
def    lowerCamelCase__ (		):
  a		:      Optional[int]       =  fetch_california_housing()
  a     ,			a		:      Optional[Any]       =  data_handling(_A       )
  a     ,			a     ,			a     ,			a		:      Dict       =  train_test_split(
      _A				,    _A				,    test_size=0.25				,    random_state=1       )
  a		:      List[str]       =  xgboost(_A				,    _A				,    _A       )
  # Error printing
  print(f"""Mean Absolute Error : {mean_absolute_error(_A				,    _A       )}"""       )
  print(f"""Mean Square Error  : {mean_squared_error(_A				,    _A       )}"""       )


if __name__ == "__main__":
     import doctest

     doctest.testmod(verbose=True)
     main()