





'''simple docstring'''







import textwrap

import pyarrow as pa
import pytest

from datasets import Features, Image
from datasets.packaged_modules.text.text import Text

from ..utils import require_pil





@pytest.fixture
def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      List[Any] )			->						str:
						UpperCAmelCase_      :   Tuple      =	tmp_path / '''text.txt'''
						UpperCAmelCase_      :   Optional[int]      =	textwrap.dedent(
						    '''\
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

        Second paragraph:
        Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
        Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
        ''' )
						with open(SCREAMING_SNAKE_CASE__,      '''w''',      encoding='''utf-8''' ) as f:
												f.write(SCREAMING_SNAKE_CASE__ )
						return str(SCREAMING_SNAKE_CASE__ )





@pytest.fixture
def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      Tuple,      SCREAMING_SNAKE_CASE__   :      List[str] )			->						Any:
						UpperCAmelCase_      :   Tuple      =	tmp_path / '''text_with_image.txt'''
						with open(SCREAMING_SNAKE_CASE__,      '''w''',      encoding='''utf-8''' ) as f:
												f.write(SCREAMING_SNAKE_CASE__ )
						return str(SCREAMING_SNAKE_CASE__ )





@pytest.mark.parametrize('''keep_linebreaks''',      [True, False] )
def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      Dict,      SCREAMING_SNAKE_CASE__   :      str )			->						int:
						with open(SCREAMING_SNAKE_CASE__,      encoding='''utf-8''' ) as f:
												UpperCAmelCase_      :   Tuple      =	f.read().splitlines(keepends=SCREAMING_SNAKE_CASE__ )
						UpperCAmelCase_      :   str      =	Text(keep_linebreaks=SCREAMING_SNAKE_CASE__,      encoding='''utf-8''' )
						UpperCAmelCase_      :   Optional[Any]      =	text._generate_tables([[text_file]] )
						UpperCAmelCase_      :   Optional[Any]      =	pa.concat_tables([table for _, table in generator] ).to_pydict()['''text''']
						assert generated_content == expected_content





@require_pil
def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      List[Any] )			->						str:
						with open(SCREAMING_SNAKE_CASE__,      encoding='''utf-8''' ) as f:
												UpperCAmelCase_      :   Tuple      =	f.read().splitlines()[0]
						UpperCAmelCase_      :   Optional[int]      =	Text(encoding='''utf-8''',      features=Features({'''image''': Image()} ) )
						UpperCAmelCase_      :   Optional[int]      =	text._generate_tables([[text_file_with_image]] )
						UpperCAmelCase_      :   List[Any]      =	pa.concat_tables([table for _, table in generator] )
						assert pa_table.schema.field('''image''' ).type == Image()()
						UpperCAmelCase_      :   Tuple      =	pa_table.to_pydict()['''image''']
						assert generated_content == [{"path": image_file, "bytes": None}]





@pytest.mark.parametrize('''sample_by''',      ['''line''', '''paragraph''', '''document'''] )
def 							lowerCamelCase_   (	SCREAMING_SNAKE_CASE__   :      Optional[int],      SCREAMING_SNAKE_CASE__   :      Optional[int] )			->						Optional[int]:
						with open(SCREAMING_SNAKE_CASE__,      encoding='''utf-8''' ) as f:
												UpperCAmelCase_      :   List[Any]      =	f.read()
						if sample_by == "line":
												UpperCAmelCase_      :   Union[str, Any]      =	expected_content.splitlines()
						elif sample_by == "paragraph":
												UpperCAmelCase_      :   Optional[int]      =	expected_content.split('''\n\n''' )
						elif sample_by == "document":
												UpperCAmelCase_      :   List[str]      =	[expected_content]
						UpperCAmelCase_      :   Optional[int]      =	Text(sample_by=SCREAMING_SNAKE_CASE__,      encoding='''utf-8''',      chunksize=100 )
						UpperCAmelCase_      :   Dict      =	text._generate_tables([[text_file]] )
						UpperCAmelCase_      :   Union[str, Any]      =	pa.concat_tables([table for _, table in generator] ).to_pydict()['''text''']
						assert generated_content == expected_content







"""simple docstring"""




import argparse
import os


A__   :						Any 							=     {
    """pytorch""": {
        """1.13""": {
            """torch""": """1.13.1""",
            """torchvision""": """0.14.1""",
            """torchaudio""": """0.13.1""",
            """python""": 3.9,
            """cuda""": """cu116""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu116"""
            ),
            """base_image""": """nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.12""": {
            """torch""": """1.12.1""",
            """torchvision""": """0.13.1""",
            """torchaudio""": """0.12.1""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.11""": {
            """torch""": """1.11.0""",
            """torchvision""": """0.12.0""",
            """torchaudio""": """0.11.0""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.10""": {
            """torch""": """1.10.2""",
            """torchvision""": """0.11.3""",
            """torchaudio""": """0.10.2""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        """1.9""": {
            """torch""": """1.9.1""",
            """torchvision""": """0.10.1""",
            """torchaudio""": """0.9.1""",
            """python""": 3.9,
            """cuda""": """cu111""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu111"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
    },
    """tensorflow""": {
        """2.11""": {
            """tensorflow""": """2.11.1""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.11.1""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.10""": {
            """tensorflow""": """2.10.1""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.10.1""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.9""": {
            """tensorflow""": """2.9.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.9.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.8""": {
            """tensorflow""": """2.8.2""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.8.2""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.7""": {
            """tensorflow""": """2.7.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.7.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.6""": {
            """tensorflow""": """2.6.5""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.6.5""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.5""": {
            """tensorflow""": """2.5.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.5.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
    },
}


if __name__ == "__main__":
    A__   :						str 							=     argparse.ArgumentParser("""Choose the framework and version to install""")
    parser.add_argument(
        """--framework""", help="""The framework to install. Should be `torch` or `tensorflow`""", type=str, required=True
    )
    parser.add_argument("""--version""", help="""The version of the framework to install.""", type=str, required=True)
    A__   :						Any 							=     parser.parse_args()

    A__   :						List[Any] 							=     past_versions_testing[args.framework][args.version]

    os.system(f"""echo \"export INSTALL_CMD=\'{info["install"]}\'\" >> ~/.profile""")
    print(f"""echo \"export INSTALL_CMD=\'{info["install"]}\'\" >> ~/.profile""")

    A__   :						Any 							=     """"""
    if args.framework == "pytorch":
        A__   :						str 							=     info["""cuda"""]
    os.system(f"""echo \"export CUDA='{cuda}'\" >> ~/.profile""")
    print(f"""echo \"export CUDA='{cuda}'\" >> ~/.profile""")



