




'''simple docstring'''


import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
UpperCAmelCase_ 		=      [
    "kernels/rwkv/wkv_cuda.cu",
    "kernels/rwkv/wkv_op.cpp",
    "kernels/deformable_detr/ms_deform_attn.h",
    "kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh",
    "models/graphormer/algos_graphormer.pyx",
]


def 						SCREAMING_SNAKE_CASE       (      a_	:							Union[str, Any]			):
  # Test all the extensions added in the setup
  for file in FILES_TO_FIND:
    if not (transformers_path / file).exists():
      return False
  return True


if __name__ == "__main__":
  UpperCAmelCase_ 		=      argparse.ArgumentParser()
  parser.add_argument("--check_lib", action="store_true", help="Whether to check the build or the actual package.")
  UpperCAmelCase_ 		=      parser.parse_args()
  if args.check_lib:
    UpperCAmelCase_ 		=      importlib.import_module("transformers")
    UpperCAmelCase_ 		=      Path(transformers_module.__file__).parent
  else:
    UpperCAmelCase_ 		=      Path.cwd() / "build/lib/transformers"
  if not test_custom_files_are_present(transformers_path):
    raise ValueError("The built release does not contain the custom files. Fix this before going further!")









'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase_ 		=      logging.get_logger(__name__)

UpperCAmelCase_ 		=      {
    "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/config.json",
    "distilbert-base-uncased-distilled-squad": (
        "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/config.json",
    "distilbert-base-cased-distilled-squad": (
        "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json",
    "distilbert-base-multilingual-cased": (
        "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json"
    ),
    "distilbert-base-uncased-finetuned-sst-2-english": (
        "https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json"
    ),
}





class    __lowercase						(  __magic_name__ ):
   _a							=      """distilbert"""
   _a							=      {
       """hidden_size""": """dim""",
       """num_attention_heads""": """n_heads""",
       """num_hidden_layers""": """n_layers""",
   }







   def __init__(	self      ,							UpperCamelCase=3_0522      ,							UpperCamelCase=512      ,							UpperCamelCase=False      ,							UpperCamelCase=6      ,							UpperCamelCase=12      ,							UpperCamelCase=768      ,							UpperCamelCase=4 * 768      ,							UpperCamelCase=0.1      ,							UpperCamelCase=0.1      ,							UpperCamelCase="gelu"      ,							UpperCamelCase=0.02      ,							UpperCamelCase=0.1      ,							UpperCamelCase=0.2      ,							UpperCamelCase=0      ,							**UpperCamelCase      ,							)				->    int:
     __a			=					vocab_size
     __a			=					max_position_embeddings
     __a			=					sinusoidal_pos_embds
     __a			=					n_layers
     __a			=					n_heads
     __a			=					dim
     __a			=					hidden_dim
     __a			=					dropout
     __a			=					attention_dropout
     __a			=					activation
     __a			=					initializer_range
     __a			=					qa_dropout
     __a			=					seq_classif_dropout
     super().__init__(**UpperCamelCase      ,							pad_token_id=UpperCamelCase      )





class    __lowercase						(  __magic_name__ ):







   @property
   def 		UpperCamelCase__			(	self      )				->    Mapping[str, Mapping[int, str]]:
     if self.task == "multiple-choice":
       __a			=					{0: 'batch', 1: 'choice', 2: 'sequence'}
     else:
       __a			=					{0: 'batch', 1: 'sequence'}
     return OrderedDict(
         [
             ('input_ids', dynamic_axis),
             ('attention_mask', dynamic_axis),
         ]      )



