

"""simple docstring"""






# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest

from transformers.testing_utils import HfDoctestModule, HfDocTestParser


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
snake_case_   :   Union[str, Any]        =       abspath(join(dirname(__file__), """src"""))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action="""ignore""", category=FutureWarning)



def   lowercase_	(    _lowercase       :		List[str]	):




					'''simple docstring'''






					config.addinivalue_line(
					    "markers"							,      "is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested"	)
					config.addinivalue_line(
					    "markers"							,      "is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested"	)
					config.addinivalue_line("markers"							,      "is_pipeline_test: mark test to run only when pipelines are tested"	)
					config.addinivalue_line("markers"							,      "is_staging_test: mark test to run only in the staging environment"	)
					config.addinivalue_line("markers"							,      "accelerate_tests: mark test that require accelerate"	)
					config.addinivalue_line("markers"							,      "tool_tests: mark the tool tests that are run on their specific schedule"	)



def   lowercase_	(    _lowercase       :		List[str]	):




					'''simple docstring'''






					from transformers.testing_utils import pytest_addoption_shared

					pytest_addoption_shared(_lowercase	)



def   lowercase_	(    _lowercase       :		Tuple	):




					'''simple docstring'''






					from transformers.testing_utils import pytest_terminal_summary_main

					UpperCAmelCase			:   Optional[int]      =				terminalreporter.config.getoption("--make-reports"	)
					if make_reports:
										pytest_terminal_summary_main(_lowercase							,      id=_lowercase	)



def   lowercase_	(    _lowercase       :		str							,      _lowercase       :		Dict	):




					'''simple docstring'''






					if exitstatus == 5:
										UpperCAmelCase			:   List[str]      =				0


# Doctest custom flag to ignore output.
snake_case_   :   Union[str, Any]        =       doctest.register_optionflag("""IGNORE_RESULT""")

snake_case_   :   Optional[int]        =       doctest.OutputChecker







class       snake_case__  ( lowerCAmelCase_     ):







			def 			__lowerCAmelCase				(			self			: List[Any]			,  lowercase			: Tuple			,  lowercase			: Optional[Any]			,  lowercase			: int  ):





								'''simple docstring'''



								if IGNORE_RESULT & optionflags:
													return True
								return OutputChecker.check_output(self			,  lowercase			,  lowercase			,  lowercase  )

snake_case_   :   List[str]        =       CustomOutputChecker
snake_case_   :   Optional[Any]        =       HfDoctestModule




snake_case_   :   List[str]        =       HfDocTestParser





"""simple docstring"""






import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases



def   lowercase_	(    _lowercase       :		Optional[int]							,      _lowercase       :		int	):




					'''simple docstring'''






					assert isinstance(_lowercase							,      _lowercase	)
					assert dataset.num_rows == 4
					assert dataset.num_columns == 1
					assert dataset.column_names == ["text"]
					for feature, expected_dtype in expected_features.items():
										assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"							,      [False, True]	)
def   lowercase_	(    _lowercase       :		Union[str, Any]							,      _lowercase       :		Optional[int]							,      _lowercase       :		Dict	):




					'''simple docstring'''






					UpperCAmelCase			:   Dict      =				tmp_path / "cache"
					UpperCAmelCase			:   str      =				{"text": "string"}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										UpperCAmelCase			:   Tuple      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase							,      keep_in_memory=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)



@pytest.mark.parametrize(
    "features"							,      [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]							,      )
def   lowercase_	(    _lowercase       :		Dict							,      _lowercase       :		Union[str, Any]							,      _lowercase       :		Optional[int]	):




					'''simple docstring'''






					UpperCAmelCase			:   int      =				tmp_path / "cache"
					UpperCAmelCase			:   Any      =				{"text": "string"}
					UpperCAmelCase			:   List[str]      =				features.copy() if features else default_expected_features
					UpperCAmelCase			:   Union[str, Any]      =				(
					    Features({feature: Value(_lowercase	) for feature, dtype in features.items()}	) if features is not None else None
					)
					UpperCAmelCase			:   str      =				TextDatasetReader(_lowercase							,      features=_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)



@pytest.mark.parametrize("split"							,      [None, NamedSplit("train"	), "train", "test"]	)
def   lowercase_	(    _lowercase       :		int							,      _lowercase       :		Tuple							,      _lowercase       :		List[str]	):




					'''simple docstring'''






					UpperCAmelCase			:   str      =				tmp_path / "cache"
					UpperCAmelCase			:   Any      =				{"text": "string"}
					UpperCAmelCase			:   List[Any]      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase							,      split=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)
					assert dataset.split == split if split else "train"



@pytest.mark.parametrize("path_type"							,      [str, list]	)
def   lowercase_	(    _lowercase       :		Optional[int]							,      _lowercase       :		Any							,      _lowercase       :		Union[str, Any]	):




					'''simple docstring'''






					if issubclass(_lowercase							,      _lowercase	):
										UpperCAmelCase			:   List[str]      =				text_path
					elif issubclass(_lowercase							,      _lowercase	):
										UpperCAmelCase			:   List[Any]      =				[text_path]
					UpperCAmelCase			:   Union[str, Any]      =				tmp_path / "cache"
					UpperCAmelCase			:   List[Any]      =				{"text": "string"}
					UpperCAmelCase			:   Tuple      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_dataset(_lowercase							,      _lowercase	)



def   lowercase_	(    _lowercase       :		Dict							,      _lowercase       :		int							,      _lowercase       :		Optional[Any]=("train",)	):




					'''simple docstring'''






					assert isinstance(_lowercase							,      _lowercase	)
					for split in splits:
										UpperCAmelCase			:   str      =				dataset_dict[split]
										assert dataset.num_rows == 4
										assert dataset.num_columns == 1
										assert dataset.column_names == ["text"]
										for feature, expected_dtype in expected_features.items():
															assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"							,      [False, True]	)
def   lowercase_	(    _lowercase       :		Dict							,      _lowercase       :		str							,      _lowercase       :		Dict	):




					'''simple docstring'''






					UpperCAmelCase			:   str      =				tmp_path / "cache"
					UpperCAmelCase			:   Union[str, Any]      =				{"text": "string"}
					with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
										UpperCAmelCase			:   Tuple      =				TextDatasetReader({"train": text_path}							,      cache_dir=_lowercase							,      keep_in_memory=_lowercase	).read()
					_check_text_datasetdict(_lowercase							,      _lowercase	)



@pytest.mark.parametrize(
    "features"							,      [
        None,
        {"text": "string"},
        {"text": "int32"},
        {"text": "float32"},
    ]							,      )
def   lowercase_	(    _lowercase       :		List[Any]							,      _lowercase       :		Union[str, Any]							,      _lowercase       :		int	):




					'''simple docstring'''






					UpperCAmelCase			:   int      =				tmp_path / "cache"
					# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
					UpperCAmelCase			:   List[str]      =				{"text": "string"}
					UpperCAmelCase			:   str      =				features.copy() if features else default_expected_features
					UpperCAmelCase			:   Optional[int]      =				(
					    Features({feature: Value(_lowercase	) for feature, dtype in features.items()}	) if features is not None else None
					)
					UpperCAmelCase			:   Optional[int]      =				TextDatasetReader({"train": text_path}							,      features=_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_datasetdict(_lowercase							,      _lowercase	)




@pytest.mark.parametrize("split"							,      [None, NamedSplit("train"	), "train", "test"]	)
def   lowercase_	(    _lowercase       :		int							,      _lowercase       :		Tuple							,      _lowercase       :		Optional[Any]	):




					'''simple docstring'''






					if split:
										UpperCAmelCase			:   Optional[Any]      =				{split: text_path}
					else:
										UpperCAmelCase			:   str      =				"train"
										UpperCAmelCase			:   Union[str, Any]      =				{"train": text_path, "test": text_path}
					UpperCAmelCase			:   Any      =				tmp_path / "cache"
					UpperCAmelCase			:   List[Any]      =				{"text": "string"}
					UpperCAmelCase			:   Any      =				TextDatasetReader(_lowercase							,      cache_dir=_lowercase	).read()
					_check_text_datasetdict(_lowercase							,      _lowercase							,      splits=list(path.keys()	)	)
					assert all(dataset[split].split == split for split in path.keys()	)


