



import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Value
from datasets.packaged_modules.json.json import Json

@pytest.fixture
def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Optional[int]      ):
				"""simple docstring"""







				__a					       =						tmp_path / """file.jsonl"""
				__a					       =						textwrap.dedent(
				    """\
        {\"col_1\": -1}
        {\"col_1\": 1, \"col_2\": 2}
        {\"col_1\": 10, \"col_2\": 20}
        """      )
				with open(_SCREAMING_SNAKE_CASE			,       """w"""      ) as f:
								f.write(_SCREAMING_SNAKE_CASE      )
				return str(_SCREAMING_SNAKE_CASE      )

@pytest.fixture
def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     int      ):
				"""simple docstring"""







				__a					       =						tmp_path / """file_utf16_encoded.jsonl"""
				__a					       =						textwrap.dedent(
				    """\
        {\"col_1\": -1}
        {\"col_1\": 1, \"col_2\": 2}
        {\"col_1\": 10, \"col_2\": 20}
        """      )
				with open(_SCREAMING_SNAKE_CASE			,       """w"""			,       encoding="""utf-16"""      ) as f:
								f.write(_SCREAMING_SNAKE_CASE      )
				return str(_SCREAMING_SNAKE_CASE      )

@pytest.fixture
def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Union[str, Any]      ):
				"""simple docstring"""







				__a					       =						tmp_path / """file_with_list_of_dicts.json"""
				__a					       =						textwrap.dedent(
				    """\
        [
            {\"col_1\": -1},
            {\"col_1\": 1, \"col_2\": 2},
            {\"col_1\": 10, \"col_2\": 20}
        ]
        """      )
				with open(_SCREAMING_SNAKE_CASE			,       """w"""      ) as f:
								f.write(_SCREAMING_SNAKE_CASE      )
				return str(_SCREAMING_SNAKE_CASE      )

@pytest.fixture
def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Tuple      ):
				"""simple docstring"""







				__a					       =						tmp_path / """file_with_list_of_dicts_field.json"""
				__a					       =						textwrap.dedent(
				    """\
        {
            \"field1\": 1,
            \"field2\": \"aabb\",
            \"field3\": [
                {\"col_1\": -1},
                {\"col_1\": 1, \"col_2\": 2},
                {\"col_1\": 10, \"col_2\": 20}
            ]
        }
        """      )
				with open(_SCREAMING_SNAKE_CASE			,       """w"""      ) as f:
								f.write(_SCREAMING_SNAKE_CASE      )
				return str(_SCREAMING_SNAKE_CASE      )

@pytest.mark.parametrize(
    """file_fixture, config_kwargs"""			,       [
        ("""jsonl_file""", {}),
        ("""jsonl_file_utf16_encoded""", {"""encoding""": """utf-16"""}),
        ("""json_file_with_list_of_dicts""", {}),
        ("""json_file_with_list_of_dicts_field""", {"""field""": """field3"""}),
    ]			,       )
def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     Union[str, Any]			,       _SCREAMING_SNAKE_CASE    :     int			,       _SCREAMING_SNAKE_CASE    :     Dict      ):
				"""simple docstring"""







				__a					       =						Json(**_SCREAMING_SNAKE_CASE      )
				__a					       =						json._generate_tables([[request.getfixturevalue(_SCREAMING_SNAKE_CASE      )]]      )
				__a					       =						pa.concat_tables([table for _, table in generator]      )
				assert pa_table.to_pydict() == {"col_1": [-1, 1, 10], "col_2": [None, 2, 20]}

@pytest.mark.parametrize(
    """file_fixture, config_kwargs"""			,       [
        (
            """jsonl_file""",
            {"""features""": Features({"""col_1""": Value("""int64"""      ), """col_2""": Value("""int64"""      ), """missing_col""": Value("""string"""      )}      )},
        ),
        (
            """json_file_with_list_of_dicts""",
            {"""features""": Features({"""col_1""": Value("""int64"""      ), """col_2""": Value("""int64"""      ), """missing_col""": Value("""string"""      )}      )},
        ),
        (
            """json_file_with_list_of_dicts_field""",
            {
                """field""": """field3""",
                """features""": Features(
                    {"""col_1""": Value("""int64"""      ), """col_2""": Value("""int64"""      ), """missing_col""": Value("""string"""      )}      ),
            },
        ),
    ]			,       )
def 					lowerCAmelCase__  (							_SCREAMING_SNAKE_CASE    :     int			,       _SCREAMING_SNAKE_CASE    :     List[str]			,       _SCREAMING_SNAKE_CASE    :     str      ):
				"""simple docstring"""







				__a					       =						Json(**_SCREAMING_SNAKE_CASE      )
				__a					       =						json._generate_tables([[request.getfixturevalue(_SCREAMING_SNAKE_CASE      )]]      )
				__a					       =						pa.concat_tables([table for _, table in generator]      )
				assert pa_table.to_pydict() == {"col_1": [-1, 1, 10], "col_2": [None, 2, 20], "missing_col": [None, None, None]}





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase__     =	{
    """configuration_oneformer""": ["""ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OneFormerConfig"""],
    """processing_oneformer""": ["""OneFormerProcessor"""],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__     =	["""OneFormerImageProcessor"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__     =	[
						    """ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """OneFormerForUniversalSegmentation""",
						    """OneFormerModel""",
						    """OneFormerPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig
						from .processing_oneformer import OneFormerProcessor

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_oneformer import OneFormerImageProcessor
						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_oneformer import (
												    ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    OneFormerForUniversalSegmentation,
												    OneFormerModel,
												    OneFormerPreTrainedModel,
												)


else:
						import sys

						lowerCamelCase__     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)
