import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_rjieba
@require_tokenizers
class 						lowercase    (     a				,       unittest.TestCase     ):
							lowercase__						:       List[str]								=							RoFormerTokenizer
							lowercase__						:       Any								=							RoFormerTokenizerFast
							lowercase__						:       str								=							True
							lowercase__						:       List[str]								=							True




							def 	__snake_case(						self   :					List[Any]      )					->				Optional[int]:



												'''simple docstring'''

												super().setUp()




							def 	__snake_case(						self   :					List[Any]	,							**_UpperCamelCase   :					str      )					->				Tuple:



												'''simple docstring'''

												return self.tokenizer_class.from_pretrained("junnyu/roformer_chinese_base"	,							**_UpperCamelCase      )




							def 	__snake_case(						self   :					Union[str, Any]	,							**_UpperCamelCase   :					Any      )					->				Tuple:



												'''simple docstring'''

												return self.rust_tokenizer_class.from_pretrained("junnyu/roformer_chinese_base"	,							**_UpperCamelCase      )




							def 	__snake_case(						self   :					List[Any]      )					->				Union[str, Any]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       "永和服装饰品有限公司,今天天气非常好"
												SCREAMING_SNAKE_CASE    			=       "永和 服装 饰品 有限公司 , 今 天 天 气 非常 好"
												return input_text, output_text




							def 	__snake_case(						self   :					str      )					->				int:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.get_tokenizer()
												SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       self.get_chinese_input_output_texts()
												SCREAMING_SNAKE_CASE    			=       tokenizer.tokenize(_UpperCamelCase      )

												self.assertListEqual(_UpperCamelCase	,							output_text.split()      )

												SCREAMING_SNAKE_CASE    			=       tokens + [tokenizer.unk_token]
												SCREAMING_SNAKE_CASE    			=       [22_943, 21_332, 34_431, 45_904, 117, 306, 1_231, 1_231, 2_653, 33_994, 1_266, 100]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase      )	,							_UpperCamelCase      )




							def 	__snake_case(						self   :					Dict      )					->				Any:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       self.get_rust_tokenizer()
												SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       self.get_chinese_input_output_texts()
												SCREAMING_SNAKE_CASE    			=       tokenizer.tokenize(_UpperCamelCase      )
												self.assertListEqual(_UpperCamelCase	,							output_text.split()      )
												SCREAMING_SNAKE_CASE    			=       tokens + [tokenizer.unk_token]
												SCREAMING_SNAKE_CASE    			=       [22_943, 21_332, 34_431, 45_904, 117, 306, 1_231, 1_231, 2_653, 33_994, 1_266, 100]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase      )	,							_UpperCamelCase      )




							def 	__snake_case(						self   :					Optional[int]      )					->				Any:



												'''simple docstring'''

												pass




							def 	__snake_case(						self   :					List[Any]      )					->				Optional[Any]:



												'''simple docstring'''

												pass





							def 	__snake_case(						self   :					Tuple      )					->				Optional[int]:



												'''simple docstring'''

												pass





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 						lowercase    (     unittest.TestCase     ):




							def 	__snake_case(						self   :					Union[str, Any]      )					->				List[str]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       inspect.getfile(accelerate.test_utils      )
												SCREAMING_SNAKE_CASE    			=       os.path.sep.join(mod_file.split(os.path.sep      )[:-1] + ["scripts", "test_script.py"]      )
												SCREAMING_SNAKE_CASE    			=       os.path.sep.join(
												    mod_file.split(os.path.sep      )[:-1] + ["scripts", "test_distributed_data_loop.py"]      )
												SCREAMING_SNAKE_CASE    			=       os.path.sep.join(mod_file.split(os.path.sep      )[:-1] + ["scripts", "test_ops.py"]      )




							@require_multi_gpu
							def 	__snake_case(						self   :					Optional[int]      )					->				Any:



												'''simple docstring'''

												print(F"Found {torch.cuda.device_count()} devices."      )
												SCREAMING_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(_UpperCamelCase	,							env=os.environ.copy()      )




							@require_multi_gpu
							def 	__snake_case(						self   :					List[Any]      )					->				int:



												'''simple docstring'''

												print(F"Found {torch.cuda.device_count()} devices."      )
												SCREAMING_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(_UpperCamelCase	,							env=os.environ.copy()      )




							@require_multi_gpu
							def 	__snake_case(						self   :					int      )					->				Optional[int]:



												'''simple docstring'''

												SCREAMING_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(_UpperCamelCase	,							env=os.environ.copy()      )





							@require_multi_gpu
							def 	__snake_case(						self   :					int      )					->				int:



												'''simple docstring'''

												print(F"Found {torch.cuda.device_count()} devices, using 2 devices only"      )
												SCREAMING_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(_UpperCamelCase	,							env=os.environ.copy()      )


if __name__ == "__main__":
							_lowerCamelCase					:   str							=		Accelerator()
							_lowerCamelCase					:   List[str]							=		(accelerator.state.process_index + 2, 10)
							_lowerCamelCase					:   str							=		torch.randint(0, 10, shape).to(accelerator.device)

							_lowerCamelCase					:   Optional[Any]							=		''''''

							_lowerCamelCase					:   str							=		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)."

							_lowerCamelCase					:   Any							=		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."
							_lowerCamelCase					:   int							=		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)




