





"""simple docstring"""






import inspect
import os
import unittest
from dataclasses import dataclass

import torch

from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from accelerate.utils import KwargsHandler



@dataclass
class 	lowerCAmelCase					(      snake_case							):

       '''simple docstring'''





       lowerCAmelCase__						 =  0
       lowerCAmelCase__						 =  False
       lowerCAmelCase__						 =  3.0



class 	lowerCAmelCase					(      unittest.TestCase							):

       '''simple docstring'''





       def 							__A (   self     ):
              # If no defaults are changed, `to_kwargs` returns an empty dict.
              self.assertDictEqual(MockClass().to_kwargs()    ,  {}     )
              self.assertDictEqual(MockClass(a=2     ).to_kwargs()    ,  {'a': 2}     )
              self.assertDictEqual(MockClass(a=2    ,  b=a__     ).to_kwargs()    ,  {'a': 2, 'b': True}     )
              self.assertDictEqual(MockClass(a=2    ,  c=2.25     ).to_kwargs()    ,  {'a': 2, 'c': 2.25}     )






       @require_cuda
       def 							__A (   self     ):
              # If no defaults are changed, `to_kwargs` returns an empty dict.
              _UpperCAmelCase     =     GradScalerKwargs(init_scale=10_24    ,  growth_factor=2     )
              AcceleratorState._reset_state()
              _UpperCAmelCase     =     Accelerator(mixed_precision='fp16'    ,  kwargs_handlers=[scaler_handler]     )
              print(accelerator.use_fpaa     )
              _UpperCAmelCase     =     accelerator.scaler

              # Check the kwargs have been applied
              self.assertEqual(scaler._init_scale    ,  10_24.0     )
              self.assertEqual(scaler._growth_factor    ,  2.0     )

              # Check the other values are at the default
              self.assertEqual(scaler._backoff_factor    ,  0.5     )
              self.assertEqual(scaler._growth_interval    ,  20_00     )
              self.assertEqual(scaler._enabled    ,  a__     )






       @require_multi_gpu
       def 							__A (   self     ):
              _UpperCAmelCase     =     ['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", inspect.getfile(self.__class__     )]
              execute_subprocess_async(a__    ,  env=os.environ.copy()     )


if __name__ == "__main__":
    lowerCAmelCase_			=							DistributedDataParallelKwargs(bucket_cap_mb=15, find_unused_parameters=True)
    lowerCAmelCase_			=							Accelerator(kwargs_handlers=[ddp_scaler])
    lowerCAmelCase_			=							torch.nn.Linear(100, 200)
    lowerCAmelCase_			=							accelerator.prepare(model)

    # Check the values changed in kwargs
    lowerCAmelCase_			=							''''''
    lowerCAmelCase_			=							model.bucket_bytes_cap // (1_024 * 1_024)
    if observed_bucket_cap_map != 15:
        error_msg += F"Kwargs badly passed, should have `15` but found {observed_bucket_cap_map}.\n"
    if model.find_unused_parameters is not True:
        error_msg += F"Kwargs badly passed, should have `True` but found {model.find_unused_parameters}.\n"

    # Check the values of the defaults
    if model.dim != 0:
        error_msg += F"Default value not respected, should have `0` but found {model.dim}.\n"
    if model.broadcast_buffers is not True:
        error_msg += F"Default value not respected, should have `True` but found {model.broadcast_buffers}.\n"
    if model.gradient_as_bucket_view is not False:
        error_msg += F"Default value not respected, should have `False` but found {model.gradient_as_bucket_view}.\n"

    # 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)













"""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






