





"""simple docstring"""






import unittest

import torch
from torch import nn

from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory

def       __lowerCamelCase    (       )		->       str:






       """simple docstring"""




       raise RuntimeError('CUDA out of memory.'							)



class 	lowerCAmelCase					(      nn.Module							):






       def __init__(   self     ):
              super().__init__()
              _UpperCAmelCase     =     nn.Linear(3    ,  4     )
              _UpperCAmelCase     =     nn.BatchNormad(4     )
              _UpperCAmelCase     =     nn.Linear(4    ,  5     )






       def 							__A (   self    ,  a__     ):
              return self.lineara(self.batchnorm(self.lineara(a__     )     )     )



class 	lowerCAmelCase					(      unittest.TestCase							):






       def 							__A (   self     ):
              _UpperCAmelCase     =     []

              @find_executable_batch_size(starting_batch_size=1_28     )
              def mock_training_loop_function(a__     ):
                     nonlocal batch_sizes
                     batch_sizes.append(a__     )
                     if batch_size != 8:
                            raise_fake_out_of_memory()

              mock_training_loop_function()
              self.assertListEqual(a__    ,  [1_28, 64, 32, 16, 8]     )






       def 							__A (   self     ):
              _UpperCAmelCase     =     []

              @find_executable_batch_size(starting_batch_size=1_28     )
              def mock_training_loop_function(a__    ,  a__     ):
                     nonlocal batch_sizes
                     batch_sizes.append(a__     )
                     if batch_size != 8:
                            raise_fake_out_of_memory()
                     return batch_size, arga

              _UpperCAmelCase    ,							_UpperCAmelCase     =     mock_training_loop_function('hello'     )
              self.assertListEqual(a__    ,  [1_28, 64, 32, 16, 8]     )
              self.assertListEqual([bs, arga]    ,  [8, 'hello']     )






       def 							__A (   self     ):
              @find_executable_batch_size(starting_batch_size=0     )
              def mock_training_loop_function(a__     ):
                     pass

              with self.assertRaises(a__     ) as cm:
                     mock_training_loop_function()
                     self.assertIn('No executable batch size found, reached zero.'    ,  cm.exception.args[0]     )






       def 							__A (   self     ):
              @find_executable_batch_size(starting_batch_size=16     )
              def mock_training_loop_function(a__     ):
                     if batch_size > 0:
                            raise_fake_out_of_memory()
                     pass

              with self.assertRaises(a__     ) as cm:
                     mock_training_loop_function()
                     self.assertIn('No executable batch size found, reached zero.'    ,  cm.exception.args[0]     )






       def 							__A (   self     ):
              @find_executable_batch_size(starting_batch_size=1_28     )
              def mock_training_loop_function(a__    ,  a__    ,  a__     ):
                     if batch_size != 8:
                            raise raise_fake_out_of_memory()

              with self.assertRaises(a__     ) as cm:
                     mock_training_loop_function(1_28    ,  'hello'    ,  'world'     )
                     self.assertIn('Batch size was passed into `f`'    ,  cm.exception.args[0]     )
                     self.assertIn('`f(arg1=\'hello\', arg2=\'world\')'    ,  cm.exception.args[0]     )






       def 							__A (   self     ):
              @find_executable_batch_size(starting_batch_size=16     )
              def mock_training_loop_function(a__     ):
                     raise ValueError('Oops, we had an error!'     )

              with self.assertRaises(a__     ) as cm:
                     mock_training_loop_function()
                     self.assertIn('Oops, we had an error!'    ,  cm.exception.args[0]     )






       @require_cuda
       def 							__A (   self     ):
              _UpperCAmelCase     =     torch.cuda.memory_allocated()
              _UpperCAmelCase     =     ModelForTest()
              model.cuda()
              self.assertGreater(torch.cuda.memory_allocated()    ,  a__     )
              _UpperCAmelCase     =     release_memory(a__     )
              self.assertEqual(torch.cuda.memory_allocated()    ,  a__     )













"""simple docstring"""






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 	lowerCAmelCase					(      snake_case			,	unittest.TestCase							):
       lowerCAmelCase__						 =  RoFormerTokenizer
       lowerCAmelCase__						 =  RoFormerTokenizerFast
       lowerCAmelCase__						 =  True
       lowerCAmelCase__						 =  True






       def 							__A (   self     ):
              super().setUp()






       def 							__A (   self    ,  **a__     ):
              return self.tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'    ,  **a__     )






       def 							__A (   self    ,  **a__     ):
              return self.rust_tokenizer_class.from_pretrained('junnyu/roformer_chinese_base'    ,  **a__     )






       def 							__A (   self     ):
              _UpperCAmelCase     =     '永和服装饰品有限公司,今天天气非常好'
              _UpperCAmelCase     =     '永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'
              return input_text, output_text






       def 							__A (   self     ):
              _UpperCAmelCase     =     self.get_tokenizer()
              _UpperCAmelCase    ,							_UpperCAmelCase     =     self.get_chinese_input_output_texts()
              _UpperCAmelCase     =     tokenizer.tokenize(a__     )

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

              _UpperCAmelCase     =     tokens + [tokenizer.unk_token]
              _UpperCAmelCase     =     [2_29_43, 2_13_32, 3_44_31, 4_59_04, 1_17, 3_06, 12_31, 12_31, 26_53, 3_39_94, 12_66, 1_00]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(a__     )    ,  a__     )






       def 							__A (   self     ):
              _UpperCAmelCase     =     self.get_rust_tokenizer()
              _UpperCAmelCase    ,							_UpperCAmelCase     =     self.get_chinese_input_output_texts()
              _UpperCAmelCase     =     tokenizer.tokenize(a__     )
              self.assertListEqual(a__    ,  output_text.split()     )
              _UpperCAmelCase     =     tokens + [tokenizer.unk_token]
              _UpperCAmelCase     =     [2_29_43, 2_13_32, 3_44_31, 4_59_04, 1_17, 3_06, 12_31, 12_31, 26_53, 3_39_94, 12_66, 1_00]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(a__     )    ,  a__     )






       def 							__A (   self     ):
              pass






       def 							__A (   self     ):
              pass






       def 							__A (   self     ):
              pass






