




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__A     =    logging.get_logger(__name__)

__A     =    {
    "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json",
    "google/bigbird-roberta-large": "https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json",
    "google/bigbird-base-trivia-itc": "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json",
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''
 lowercase_		=      "big_bird"

 def __init__(self    :       List[str]	,			UpperCAmelCase_    :       Optional[Any]=50_358	,			UpperCAmelCase_    :       Union[str, Any]=768	,			UpperCAmelCase_    :       str=12	,			UpperCAmelCase_    :       Tuple=12	,			UpperCAmelCase_    :       List[str]=3_072	,			UpperCAmelCase_    :       int="gelu_new"	,			UpperCAmelCase_    :       List[str]=0.1	,			UpperCAmelCase_    :       Optional[Any]=0.1	,			UpperCAmelCase_    :       Optional[Any]=4_096	,			UpperCAmelCase_    :       Union[str, Any]=2	,			UpperCAmelCase_    :       Optional[Any]=0.02	,			UpperCAmelCase_    :       Optional[Any]=1E-1_2	,			UpperCAmelCase_    :       int=True	,			UpperCAmelCase_    :       Optional[int]=0	,			UpperCAmelCase_    :       str=1	,			UpperCAmelCase_    :       int=2	,			UpperCAmelCase_    :       Union[str, Any]=66	,			UpperCAmelCase_    :       Union[str, Any]="block_sparse"	,			UpperCAmelCase_    :       Optional[int]=True	,			UpperCAmelCase_    :       int=False	,			UpperCAmelCase_    :       int=64	,			UpperCAmelCase_    :       Dict=3	,			UpperCAmelCase_    :       List[str]=None	,			**UpperCAmelCase_    :       List[str]	,			)	->int:



   '''simple docstring'''



   super().__init__(
       pad_token_id=UpperCAmelCase_	,			bos_token_id=UpperCAmelCase_	,			eos_token_id=UpperCAmelCase_	,			sep_token_id=UpperCAmelCase_	,			**UpperCAmelCase_	,			)

   lowerCamelCase__:				Union[str, Any]        =vocab_size
   lowerCamelCase__:				List[str]        =max_position_embeddings
   lowerCamelCase__:				Union[str, Any]        =hidden_size
   lowerCamelCase__:				List[Any]        =num_hidden_layers
   lowerCamelCase__:				List[str]        =num_attention_heads
   lowerCamelCase__:				Union[str, Any]        =intermediate_size
   lowerCamelCase__:				Tuple        =hidden_act
   lowerCamelCase__:				Dict        =hidden_dropout_prob
   lowerCamelCase__:				Any        =attention_probs_dropout_prob
   lowerCamelCase__:				Any        =initializer_range
   lowerCamelCase__:				Optional[Any]        =type_vocab_size
   lowerCamelCase__:				List[str]        =layer_norm_eps
   lowerCamelCase__:				Optional[int]        =use_cache

   lowerCamelCase__:				int        =rescale_embeddings
   lowerCamelCase__:				int        =attention_type
   lowerCamelCase__:				str        =use_bias
   lowerCamelCase__:				List[Any]        =block_size
   lowerCamelCase__:				List[Any]        =num_random_blocks
   lowerCamelCase__:				List[Any]        =classifier_dropout



class        _SCREAMING_SNAKE_CASE						(     __SCREAMING_SNAKE_CASE   ):







 '''simple docstring'''

 @property
 def 							SCREAMING_SNAKE_CASE_ (self    :       List[Any])	->Mapping[str, Mapping[int, str]]:



   '''simple docstring'''



   if self.task == "multiple-choice":
     lowerCamelCase__:				List[Any]        ={0: "batch", 1: "choice", 2: "sequence"}
   else:
     lowerCamelCase__:				int        ={0: "batch", 1: "sequence"}
   return OrderedDict(
       [
           ("input_ids", dynamic_axis),
           ("attention_mask", dynamic_axis),
       ])








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_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment



@require_huggingface_suite
class        _SCREAMING_SNAKE_CASE						(     unittest.TestCase   ):







 '''simple docstring'''

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



   '''simple docstring'''



   lowerCamelCase__:				List[str]        =inspect.getfile(accelerate.test_utils)
   lowerCamelCase__:				str        =os.path.sep.join(
       mod_file.split(os.path.sep)[:-1] + ["scripts", "external_deps", "test_metrics.py"])

   from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

   lowerCamelCase__:				str        =test_metrics

 @require_cpu
 def 							SCREAMING_SNAKE_CASE_ (self    :       int)	->Any:



   '''simple docstring'''



   debug_launcher(self.test_metrics.main	,			num_processes=1)

 @require_cpu
 def 							SCREAMING_SNAKE_CASE_ (self    :       int)	->int:



   '''simple docstring'''



   debug_launcher(self.test_metrics.main)

 @require_single_gpu
 def 							SCREAMING_SNAKE_CASE_ (self    :       Any)	->int:



   '''simple docstring'''



   self.test_metrics.main()







 @require_multi_gpu
 def 							SCREAMING_SNAKE_CASE_ (self    :       Tuple)	->Dict:



   '''simple docstring'''



   print(F"""Found {torch.cuda.device_count()} devices.""")
   lowerCamelCase__:				Optional[Any]        =["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())

