
import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment





class      UpperCamelCase_			(			unittest.TestCase		):







						'''simple docstring'''



						def 					SCREAMING_SNAKE_CASE( self       :Any    )     ->Any:
										lowercase						    =			inspect.getfile(accelerate.test_utils    )
										lowercase						    =			os.path.sep.join(mod_file.split(os.path.sep    )[:-1] + ["scripts", "test_sync.py"]    )





						@require_cpu
						def 					SCREAMING_SNAKE_CASE( self       :str    )     ->str:
										debug_launcher(test_sync.main		,						num_processes=1    )





						@require_cpu
						def 					SCREAMING_SNAKE_CASE( self       :int    )     ->str:
										debug_launcher(test_sync.main    )





						@require_single_gpu
						def 					SCREAMING_SNAKE_CASE( self       :List[Any]    )     ->Tuple:
										test_sync.main()





						@require_multi_gpu
						def 					SCREAMING_SNAKE_CASE( self       :List[Any]    )     ->str:
										print(F'''Found {torch.cuda.device_count()} devices.'''    )
										lowercase						    =			["torchrun", F'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
										with patch_environment(omp_num_threads=1    ):
														execute_subprocess_async(lowerCAmelCase__		,						env=os.environ.copy()    )


import sys
from collections.abc import Mapping

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter





class      UpperCamelCase_			(			TensorFormatter[Mapping, np.ndarray, Mapping]		):







						'''simple docstring'''



						def __init__( self       :int		,						lowerCAmelCase__       :Any=None		,						**lowerCAmelCase__       :Union[str, Any]    )     ->int:
										super().__init__(features=lowerCAmelCase__    )
										lowercase						    =			np_array_kwargs





						def 					SCREAMING_SNAKE_CASE( self       :Union[str, Any]		,						lowerCAmelCase__       :str    )     ->Optional[Any]:
										if isinstance(lowerCAmelCase__		,						lowerCAmelCase__    ):
														if column and all(
														    isinstance(lowerCAmelCase__		,						np.ndarray    ) and x.shape == column[0].shape and x.dtype == column[0].dtype for x in column    ):
																		return np.stack(lowerCAmelCase__    )
														else:
																		# don't use np.array(column, dtype=object)
																		# since it fails in certain cases
																		# see https://stackoverflow.com/q/51005699
																		lowercase						    =			np.empty(len(lowerCAmelCase__    )		,						dtype=lowerCAmelCase__    )
																		lowercase						    =			column
																		return out
										return column





						def 					SCREAMING_SNAKE_CASE( self       :str		,						lowerCAmelCase__       :List[str]    )     ->Union[str, Any]:
										if isinstance(lowerCAmelCase__		,						(str, bytes, type(lowerCAmelCase__    ))    ):
														return value
										elif isinstance(lowerCAmelCase__		,						(np.character, np.ndarray)    ) and np.issubdtype(value.dtype		,						np.character    ):
														return value
										elif isinstance(lowerCAmelCase__		,						np.number    ):
														return value

										lowercase						    =			{}

										if isinstance(lowerCAmelCase__		,						np.ndarray    ) and np.issubdtype(value.dtype		,						np.integer    ):
														lowercase						    =			{"dtype": np.intaa}
										elif isinstance(lowerCAmelCase__		,						np.ndarray    ) and np.issubdtype(value.dtype		,						np.floating    ):
														lowercase						    =			{"dtype": np.floataa}
										elif config.PIL_AVAILABLE and "PIL" in sys.modules:
														import PIL.Image

														if isinstance(lowerCAmelCase__		,						PIL.Image.Image    ):
																		return np.asarray(lowerCAmelCase__		,						**self.np_array_kwargs    )

										return np.asarray(lowerCAmelCase__		,						**{**default_dtype, **self.np_array_kwargs}    )





						def 					SCREAMING_SNAKE_CASE( self       :int		,						lowerCAmelCase__       :Dict    )     ->int:
										# support for torch, tf, jax etc.
										if config.TORCH_AVAILABLE and "torch" in sys.modules:
														import torch

														if isinstance(lowerCAmelCase__		,						torch.Tensor    ):
																		return self._tensorize(data_struct.detach().cpu().numpy()[()]    )
										if hasattr(lowerCAmelCase__		,						"__array__"    ) and not isinstance(lowerCAmelCase__		,						(np.ndarray, np.character, np.number)    ):
														lowercase						    =			data_struct.__array__()
										# support for nested types like struct of list of struct
										if isinstance(lowerCAmelCase__		,						np.ndarray    ):
														if data_struct.dtype == object:
																		return self._consolidate([self.recursive_tensorize(lowerCAmelCase__    ) for substruct in data_struct]    )
										if isinstance(lowerCAmelCase__		,						(list, tuple)    ):
														return self._consolidate([self.recursive_tensorize(lowerCAmelCase__    ) for substruct in data_struct]    )
										return self._tensorize(lowerCAmelCase__    )





						def 					SCREAMING_SNAKE_CASE( self       :int		,						lowerCAmelCase__       :dict    )     ->str:
										return map_nested(self._recursive_tensorize		,						lowerCAmelCase__		,						map_list=lowerCAmelCase__    )





						def 					SCREAMING_SNAKE_CASE( self       :Tuple		,						lowerCAmelCase__       :pa.Table    )     ->Mapping:
										lowercase						    =			self.numpy_arrow_extractor().extract_row(lowerCAmelCase__    )
										lowercase						    =			self.python_features_decoder.decode_row(lowerCAmelCase__    )
										return self.recursive_tensorize(lowerCAmelCase__    )





						def 					SCREAMING_SNAKE_CASE( self       :str		,						lowerCAmelCase__       :pa.Table    )     ->np.ndarray:
										lowercase						    =			self.numpy_arrow_extractor().extract_column(lowerCAmelCase__    )
										lowercase						    =			self.python_features_decoder.decode_column(lowerCAmelCase__		,						pa_table.column_names[0]    )
										lowercase						    =			self.recursive_tensorize(lowerCAmelCase__    )
										lowercase						    =			self._consolidate(lowerCAmelCase__    )
										return column





						def 					SCREAMING_SNAKE_CASE( self       :List[Any]		,						lowerCAmelCase__       :pa.Table    )     ->Mapping:
										lowercase						    =			self.numpy_arrow_extractor().extract_batch(lowerCAmelCase__    )
										lowercase						    =			self.python_features_decoder.decode_batch(lowerCAmelCase__    )
										lowercase						    =			self.recursive_tensorize(lowerCAmelCase__    )
										for column_name in batch:
														lowercase						    =			self._consolidate(batch[column_name]    )
										return batch
