
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

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


if TYPE_CHECKING:
     from ...onnx.config import PatchingSpec
     from ...tokenization_utils_base import PreTrainedTokenizerBase


_UpperCAmelCase        =				logging.get_logger(__name__)

_UpperCAmelCase        =				{
    '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096''': '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096-finetuned-triviaqa''': (
        '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json'''
    ),
    '''allenai/longformer-base-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
    '''allenai/longformer-large-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
}



class 							_UpperCamelCase					(	a__     ):
       _UpperCamelCase				:					Union[str, Any]         =   """longformer"""

       def __init__(		self: str					,   _SCREAMING_SNAKE_CASE: List[Any] = 512					,   _SCREAMING_SNAKE_CASE: List[str] = 2					,   _SCREAMING_SNAKE_CASE: List[Any] = 1					,   _SCREAMING_SNAKE_CASE: Optional[int] = 0					,   _SCREAMING_SNAKE_CASE: int = 2					,   _SCREAMING_SNAKE_CASE: List[str] = 30522					,   _SCREAMING_SNAKE_CASE: Union[str, Any] = 768					,   _SCREAMING_SNAKE_CASE: Optional[Any] = 12					,   _SCREAMING_SNAKE_CASE: List[str] = 12					,   _SCREAMING_SNAKE_CASE: int = 3072					,   _SCREAMING_SNAKE_CASE: Dict = "gelu"					,   _SCREAMING_SNAKE_CASE: List[str] = 0.1					,   _SCREAMING_SNAKE_CASE: List[str] = 0.1					,   _SCREAMING_SNAKE_CASE: Dict = 512					,   _SCREAMING_SNAKE_CASE: Union[str, Any] = 2					,   _SCREAMING_SNAKE_CASE: Dict = 0.02					,   _SCREAMING_SNAKE_CASE: Optional[int] = 1e-12					,   _SCREAMING_SNAKE_CASE: List[Any] = False					,   **_SCREAMING_SNAKE_CASE: Any					,   )       -> int:




              """simple docstring"""


              super().__init__(pad_token_id=lowerCAmelCase__					,   **lowerCAmelCase__		)

              UpperCamelCase_          =  attention_window
              UpperCamelCase_          =  sep_token_id
              UpperCamelCase_          =  bos_token_id
              UpperCamelCase_          =  eos_token_id
              UpperCamelCase_          =  vocab_size
              UpperCamelCase_          =  hidden_size
              UpperCamelCase_          =  num_hidden_layers
              UpperCamelCase_          =  num_attention_heads
              UpperCamelCase_          =  hidden_act
              UpperCamelCase_          =  intermediate_size
              UpperCamelCase_          =  hidden_dropout_prob
              UpperCamelCase_          =  attention_probs_dropout_prob
              UpperCamelCase_          =  max_position_embeddings
              UpperCamelCase_          =  type_vocab_size
              UpperCamelCase_          =  initializer_range
              UpperCamelCase_          =  layer_norm_eps
              UpperCamelCase_          =  onnx_export



class 							_UpperCamelCase					(	a__     ):

       def __init__(		self: Dict					,   _SCREAMING_SNAKE_CASE: Dict					,   _SCREAMING_SNAKE_CASE: int = "default"					,   _SCREAMING_SNAKE_CASE: Optional[Any] = None		)       -> Dict:




              """simple docstring"""


              super().__init__(lowerCAmelCase__					,   lowerCAmelCase__					,   lowerCAmelCase__		)
              UpperCamelCase_          =  True

       @property
       def lowercase (		self: int		)       -> Mapping[str, Mapping[int, str]]:




              """simple docstring"""


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

       @property
       def lowercase (		self: Tuple		)       -> Mapping[str, Mapping[int, str]]:




              """simple docstring"""


              UpperCamelCase_          =  super().outputs
              if self.task == "default":
                     UpperCamelCase_          =  {0: "batch"}
              return outputs

       @property
       def lowercase (		self: List[str]		)       -> float:




              """simple docstring"""


              return 1e-4

       @property
       def lowercase (		self: Optional[Any]		)       -> int:




              """simple docstring"""


              return max(super().default_onnx_opset					,   14		)



       def lowercase (		self: Union[str, Any]					,   _SCREAMING_SNAKE_CASE: Union[str, Any]					,   _SCREAMING_SNAKE_CASE: Dict = -1					,   _SCREAMING_SNAKE_CASE: Dict = -1					,   _SCREAMING_SNAKE_CASE: Optional[Any] = False					,   _SCREAMING_SNAKE_CASE: Dict = None					,   )       -> Mapping[str, Any]:




              """simple docstring"""


              UpperCamelCase_          =  super().generate_dummy_inputs(
                  preprocessor=lowerCAmelCase__					,   batch_size=lowerCAmelCase__					,   seq_length=lowerCAmelCase__					,   is_pair=lowerCAmelCase__					,   framework=lowerCAmelCase__		)
              import torch

              # for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
              # makes the export fail randomly
              UpperCamelCase_          =  torch.zeros_like(inputs["input_ids"]		)
              # make every second token global
              UpperCamelCase_          =  1

              return inputs








import argparse
import os
import re


_UpperCAmelCase        =				'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
_UpperCAmelCase        =				re.compile(r'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
_UpperCAmelCase        =				re.compile(r'\s*\(\s*"(\S[^"]+)"')




def  lowerCAmelCase_ (							UpperCamelCase_					,		UpperCamelCase_ = False  )     ->		Union[str, Any]:
       with open(UpperCamelCase_					,		"r"					,		encoding="utf-8"  ) as f:
              UpperCamelCase_          =  f.read()

       UpperCamelCase_          =  content.split("\n"  )
       UpperCamelCase_          =  []
       UpperCamelCase_          =  0
       while line_idx < len(UpperCamelCase_  ):
              if _re_intro_mapping.search(lines[line_idx]  ) is not None:
                     UpperCamelCase_          =  len(re.search(r"^(\s*)\S"					,		lines[line_idx]  ).groups()[0]  ) + 8
                     # Start of a new mapping!
                     while not lines[line_idx].startswith(" " * indent + "("  ):
                            new_lines.append(lines[line_idx]  )
                            line_idx += 1

                     UpperCamelCase_          =  []
                     while lines[line_idx].strip() != "]":
                            # Blocks either fit in one line or not
                            if lines[line_idx].strip() == "(":
                                   UpperCamelCase_          =  line_idx
                                   while not lines[line_idx].startswith(" " * indent + ")"  ):
                                          line_idx += 1
                                   blocks.append("\n".join(lines[start_idx : line_idx + 1]  )  )
                            else:
                                   blocks.append(lines[line_idx]  )
                            line_idx += 1

                     # Sort blocks by their identifiers
                     UpperCamelCase_          =  sorted(UpperCamelCase_					,		key=lambda UpperCamelCase_  : _re_identifier.search(UpperCamelCase_  ).groups()[0]  )
                     new_lines += blocks
              else:
                     new_lines.append(lines[line_idx]  )
                     line_idx += 1

       if overwrite:
              with open(UpperCamelCase_					,		"w"					,		encoding="utf-8"  ) as f:
                     f.write("\n".join(UpperCamelCase_  )  )
       elif "\n".join(UpperCamelCase_  ) != content:
              return True




def  lowerCAmelCase_ (							UpperCamelCase_ = False  )     ->		List[Any]:
       UpperCamelCase_          =  [os.path.join(UpperCamelCase_					,		UpperCamelCase_  ) for f in os.listdir(UpperCamelCase_  ) if f.endswith(".py"  )]
       UpperCamelCase_          =  [sort_auto_mapping(UpperCamelCase_					,		overwrite=UpperCamelCase_  ) for fname in fnames]

       if not overwrite and any(UpperCamelCase_  ):
              UpperCamelCase_          =  [f for f, d in zip(UpperCamelCase_					,		UpperCamelCase_  ) if d]
              raise ValueError(
                  F'''The following files have auto mappings that need sorting: {", ".join(UpperCamelCase_  )}. Run `make style` to fix'''
                  " this."  )


if __name__ == "__main__":
     _UpperCAmelCase        =				argparse.ArgumentParser()
     parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
     _UpperCAmelCase        =				parser.parse_args()

     sort_all_auto_mappings(not args.check_only)

