






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


lowerCamelCase : Dict						   =       logging.get_logger(__name__)

lowerCamelCase : List[Any]						   =       {
    '''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 		lowerCAmelCase     ( __a			):

     '''simple docstring'''

     _A						:			List[str]									=      '''longformer'''



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


            """simple docstring"""

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

            __lowercase      :							Tuple				=     attention_window
            __lowercase      :							str				=     sep_token_id
            __lowercase      :							Tuple				=     bos_token_id
            __lowercase      :							Optional[int]				=     eos_token_id
            __lowercase      :							Any				=     vocab_size
            __lowercase      :							Any				=     hidden_size
            __lowercase      :							Dict				=     num_hidden_layers
            __lowercase      :							List[str]				=     num_attention_heads
            __lowercase      :							Dict				=     hidden_act
            __lowercase      :							Dict				=     intermediate_size
            __lowercase      :							Dict				=     hidden_dropout_prob
            __lowercase      :							Optional[Any]				=     attention_probs_dropout_prob
            __lowercase      :							int				=     max_position_embeddings
            __lowercase      :							List[str]				=     type_vocab_size
            __lowercase      :							List[str]				=     initializer_range
            __lowercase      :							Union[str, Any]				=     layer_norm_eps
            __lowercase      :							List[Any]				=     onnx_export







class 		lowerCAmelCase     ( __a			):

     '''simple docstring'''

     def __init__(  self				:	Optional[Any]		,     __a				:	"PretrainedConfig"		,     __a				:	str = "default"		,     __a				:	"List[PatchingSpec]" = None							)			->  Tuple:


            """simple docstring"""

            super().__init__(__a		,     __a		,     __a							)
            __lowercase      :							Dict				=     True



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


            """simple docstring"""

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



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


            """simple docstring"""

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



     @property
     def       lowerCAmelCase				(  self				:	List[Any]							)			->  float:


            """simple docstring"""

            return 1E-4



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


            """simple docstring"""

            return max(super().default_onnx_opset		,     14							)



     def       lowerCAmelCase				(  self				:	Dict		,     __a				:	"PreTrainedTokenizerBase"		,     __a				:	int = -1		,     __a				:	int = -1		,     __a				:	bool = False		,     __a				:	Optional[TensorType] = None		,     )			->  Mapping[str, Any]:


            """simple docstring"""

            __lowercase      :							Optional[int]				=     super().generate_dummy_inputs(
                preprocessor=__a		,     batch_size=__a		,     seq_length=__a		,     is_pair=__a		,     framework=__a							)
            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
            __lowercase      :							Optional[int]				=     torch.zeros_like(inputs["""input_ids"""]							)
            # make every second token global
            __lowercase      :							str				=     1

            return inputs







from .imports import is_tqdm_available


if is_tqdm_available():
	from tqdm.auto import tqdm as _tqdm

from ..state import PartialState
def       snake_case_		(     lowerCAmelCase_       :						bool = True       ,       *lowerCAmelCase_       :						int       ,       **lowerCAmelCase_       :						List[str]      ):
							if not is_tqdm_available():
														raise ImportError("""Accelerate's `tqdm` module requires `tqdm` to be installed. Please run `pip install tqdm`."""      )
							__lowercase      :							List[str]				=     False
							if main_process_only:
														__lowercase      :							Optional[int]				=     PartialState().local_process_index == 0
							return _tqdm(*lowerCAmelCase_       ,       **lowerCAmelCase_       ,       disable=lowerCAmelCase_      )