
import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


_A													=				"\\n    Text data.\n    Second line of data."

_A													=				"file"



@pytest.fixture(scope="session"	)
def 		lowercase_    (     A__	)							->							int:
    """simple docstring"""

    snake_case				  =      tmp_path_factory.mktemp("data"	) / (FILE_PATH + ".zstd")
    snake_case				  =      bytes(lowercase__				,	"utf-8"	)
    with zstd.open(lowercase__				,	"wb"	) as f:
        f.write(lowercase__	)
    return path



@pytest.fixture
def 		lowercase_    (     A__	)							->							List[str]:
    """simple docstring"""

    with open(os.path.join(tmpfs.local_root_dir				,	lowercase__	)				,	"w"	) as f:
        f.write(lowercase__	)
    return FILE_PATH



@pytest.mark.parametrize("compression_format"				,	["gzip", "xz", "zstd"]	)
def 		lowercase_    (     A__				,	A__				,	A__				,	A__				,	A__				,	A__	)							->							int:
    """simple docstring"""

    snake_case				  =      {"gzip": gz_file, "xz": xz_file, "zstd": zstd_path}
    snake_case				  =      input_paths[compression_format]
    snake_case				  =      tmp_path / "cache"
    snake_case				  =      DownloadConfig(cache_dir=lowercase__				,	extract_compressed_file=lowercase__	)
    snake_case				  =      cached_path(lowercase__				,	download_config=lowercase__	)
    with open(lowercase__	) as f:
        snake_case				  =      f.read()
    with open(lowercase__	) as f:
        snake_case				  =      f.read()
    assert extracted_file_content == expected_file_content



@pytest.mark.parametrize("default_extracted"				,	[True, False]	)
@pytest.mark.parametrize("default_cache_dir"				,	[True, False]	)
def 		lowercase_    (     A__				,	A__				,	A__				,	A__				,	A__	)							->							Any:
    """simple docstring"""

    snake_case				  =      "custom_cache"
    snake_case				  =      "custom_extracted_dir"
    snake_case				  =      tmp_path / "custom_extracted_path"
    if default_extracted:
        snake_case				  =      ("downloads" if default_cache_dir else custom_cache_dir, "extracted")
    else:
        monkeypatch.setattr("datasets.config.EXTRACTED_DATASETS_DIR"				,	lowercase__	)
        monkeypatch.setattr("datasets.config.EXTRACTED_DATASETS_PATH"				,	str(lowercase__	)	)
        snake_case				  =      custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

    snake_case				  =      xz_file
    snake_case				  =      (
        DownloadConfig(extract_compressed_file=lowercase__	)
        if default_cache_dir
        else DownloadConfig(cache_dir=tmp_path / custom_cache_dir				,	extract_compressed_file=lowercase__	)
    )
    snake_case				  =      cached_path(lowercase__				,	download_config=lowercase__	)
    assert Path(lowercase__	).parent.parts[-2:] == expected



def 		lowercase_    (     A__	)							->							Dict:
    """simple docstring"""

    snake_case				  =      str(Path(lowercase__	).resolve()	)
    assert cached_path(lowercase__	) == text_file
    # relative path
    snake_case				  =      str(Path(lowercase__	).resolve().relative_to(Path(os.getcwd()	)	)	)
    assert cached_path(lowercase__	) == text_file



def 		lowercase_    (     A__	)							->							Optional[Any]:
    """simple docstring"""

    snake_case				  =      str(tmp_path.resolve() / "__missing_file__.txt"	)
    with pytest.raises(lowercase__	):
        cached_path(lowercase__	)
    # relative path
    snake_case				  =      "./__missing_file__.txt"
    with pytest.raises(lowercase__	):
        cached_path(lowercase__	)



def 		lowercase_    (     A__	)							->							Dict:
    """simple docstring"""

    snake_case				  =      get_from_cache(F'tmp://{tmpfs_file}'	)
    with open(lowercase__	) as f:
        snake_case				  =      f.read()
    assert output_file_content == FILE_CONTENT



@patch("datasets.config.HF_DATASETS_OFFLINE"				,	lowercase__	)
def 		lowercase_    (     )							->							Any:
    """simple docstring"""

    with pytest.raises(lowercase__	):
        cached_path("https://huggingface.co"	)



@patch("datasets.config.HF_DATASETS_OFFLINE"				,	lowercase__	)
def 		lowercase_    (     A__	)							->							str:
    """simple docstring"""

    snake_case				  =      tmp_path_factory.mktemp("data"	) / "file.html"
    with pytest.raises(lowercase__	):
        http_get("https://huggingface.co"				,	temp_file=lowercase__	)
    with pytest.raises(lowercase__	):
        http_head("https://huggingface.co"	)



@patch("datasets.config.HF_DATASETS_OFFLINE"				,	lowercase__	)
def 		lowercase_    (     A__	)							->							List[Any]:
    """simple docstring"""

    snake_case				  =      tmp_path_factory.mktemp("data"	) / "file.html"
    with pytest.raises(lowercase__	):
        ftp_get("ftp://huggingface.co"				,	temp_file=lowercase__	)
    with pytest.raises(lowercase__	):
        ftp_head("ftp://huggingface.co"	)





@patch("datasets.config.HF_DATASETS_OFFLINE"				,	lowercase__	)
def 		lowercase_    (     A__	)							->							List[str]:
    """simple docstring"""

    snake_case				  =      tmp_path_factory.mktemp("data"	) / "file.html"
    with pytest.raises(lowercase__	):
        fsspec_get("s3://huggingface.co"				,	temp_file=lowercase__	)
    with pytest.raises(lowercase__	):
        fsspec_head("s3://huggingface.co"	)



import inspect
import os
import unittest

import torch

import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment







class   lowerCamelCase	(						unittest.TestCase						):





     def 	UpperCAmelCase(self   :					Dict     )		->		Dict:
         snake_case				  =      inspect.getfile(accelerate.test_utils     )
         snake_case				  =      os.path.sep.join(mod_file.split(os.path.sep     )[:-1] + ["scripts", "test_script.py"]     )
         snake_case				  =      os.path.sep.join(
             mod_file.split(os.path.sep     )[:-1] + ["scripts", "test_distributed_data_loop.py"]     )
         snake_case				  =      os.path.sep.join(mod_file.split(os.path.sep     )[:-1] + ["scripts", "test_ops.py"]     )





     @require_multi_gpu
     def 	UpperCAmelCase(self   :					List[Any]     )		->		int:
         print(f'Found {torch.cuda.device_count()} devices.'     )
         snake_case				  =      ["torchrun", f'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
         with patch_environment(omp_num_threads=1     ):
             execute_subprocess_async(_A       ,					env=os.environ.copy()     )





     @require_multi_gpu
     def 	UpperCAmelCase(self   :					Any     )		->		Optional[Any]:
         print(f'Found {torch.cuda.device_count()} devices.'     )
         snake_case				  =      ["torchrun", f'--nproc_per_node={torch.cuda.device_count()}', self.operation_file_path]
         print(f'Command: {cmd}'     )
         with patch_environment(omp_num_threads=1     ):
             execute_subprocess_async(_A       ,					env=os.environ.copy()     )





     @require_multi_gpu
     def 	UpperCAmelCase(self   :					Union[str, Any]     )		->		Dict:
         snake_case				  =      ["torchrun", f'--nproc_per_node={torch.cuda.device_count()}', inspect.getfile(self.__class__     )]
         with patch_environment(omp_num_threads=1     ):
             execute_subprocess_async(_A       ,					env=os.environ.copy()     )





     @require_multi_gpu
     def 	UpperCAmelCase(self   :					List[str]     )		->		Dict:
         print(f'Found {torch.cuda.device_count()} devices, using 2 devices only'     )
         snake_case				  =      ["torchrun", f'--nproc_per_node={torch.cuda.device_count()}', self.data_loop_file_path]
         with patch_environment(omp_num_threads=1       ,					cuda_visible_devices="0,1"     ):
             execute_subprocess_async(_A       ,					env=os.environ.copy()     )


if __name__ == "__main__":
   _A						      =				Accelerator()
   _A						      =				(accelerator.state.process_index + 2, 10)
   _A						      =				torch.randint(0, 10, shape).to(accelerator.device)

   _A						      =				""

   _A						      =				accelerator.pad_across_processes(tensor)
   if tensora.shape[0] != accelerator.state.num_processes + 1:
      error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
   if not torch.equal(tensora[: accelerator.state.process_index + 2], tensor):
      error_msg += "Tensors have different values."
   if not torch.all(tensora[accelerator.state.process_index + 2 :] == 0):
      error_msg += "Padding was not done with the right value (0)."

   _A						      =				accelerator.pad_across_processes(tensor, pad_first=True)
   if tensora.shape[0] != accelerator.state.num_processes + 1:
      error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
   _A						      =				accelerator.state.num_processes - accelerator.state.process_index - 1
   if not torch.equal(tensora[index:], tensor):
      error_msg += "Tensors have different values."
   if not torch.all(tensora[:index] == 0):
      error_msg += "Padding was not done with the right value (0)."

   # Raise error at the end to make sure we don't stop at the first failure.
   if len(error_msg) > 0:
      raise ValueError(error_msg)

