



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


__snake_case     :List[Any]			       =logging.get_logger(__name__)

__snake_case     :Tuple			       ={
    '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__					(  _lowerCamelCase       ):
				A_   :     Optional[int]								=     'longformer'


				def __init__(							self      :  int						, __UpperCamelCase      :  Union[List[int], int] = 512						, __UpperCamelCase      :  int = 2						, __UpperCamelCase      :  int = 1						, __UpperCamelCase      :  int = 0						, __UpperCamelCase      :  int = 2						, __UpperCamelCase      :  int = 30_522						, __UpperCamelCase      :  int = 768						, __UpperCamelCase      :  int = 12						, __UpperCamelCase      :  int = 12						, __UpperCamelCase      :  int = 3_072						, __UpperCamelCase      :  str = "gelu"						, __UpperCamelCase      :  float = 0.1						, __UpperCamelCase      :  float = 0.1						, __UpperCamelCase      :  int = 512						, __UpperCamelCase      :  int = 2						, __UpperCamelCase      :  float = 0.0_2						, __UpperCamelCase      :  float = 1e-12						, __UpperCamelCase      :  bool = False						, **__UpperCamelCase      :  int						, )		->     Optional[int]:
											super().__init__(pad_token_id=__UpperCamelCase						, **__UpperCamelCase       )

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





class        lowerCAmelCase__					(  _lowerCamelCase       ):


				def __init__(							self      :  Union[str, Any]						, __UpperCamelCase      :  "PretrainedConfig"						, __UpperCamelCase      :  str = "default"						, __UpperCamelCase      :  "List[PatchingSpec]" = None       )		->     Any:
											super().__init__(__UpperCamelCase						, __UpperCamelCase						, __UpperCamelCase       )
											A      						=    True


				@property
				def __UpperCamelCase						(							self      :  int       )		->     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),
											        ('global_attention_mask', dynamic_axis),
											    ]       )


				@property
				def __UpperCamelCase						(							self      :  Dict       )		->     Mapping[str, Mapping[int, str]]:
											A      						=    super().outputs
											if self.task == "default":
																		A      						=    {0: 'batch'}
											return outputs


				@property
				def __UpperCamelCase						(							self      :  Optional[Any]       )		->     float:
											return 1e-4


				@property
				def __UpperCamelCase						(							self      :  List[Any]       )		->     int:
											# needs to be >= 14 to support tril operator
											return max(super().default_onnx_opset						, 14       )


				def __UpperCamelCase						(							self      :  Optional[int]						, __UpperCamelCase      :  "PreTrainedTokenizerBase"						, __UpperCamelCase      :  int = -1						, __UpperCamelCase      :  int = -1						, __UpperCamelCase      :  bool = False						, __UpperCamelCase      :  Optional[TensorType] = None						, )		->     Mapping[str, Any]:
											A      						=    super().generate_dummy_inputs(
											    preprocessor=__UpperCamelCase						, batch_size=__UpperCamelCase						, seq_length=__UpperCamelCase						, is_pair=__UpperCamelCase						, framework=__UpperCamelCase       )
											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
											A      						=    torch.zeros_like(inputs['input_ids']       )
											# make every second token global
											A      						=    1

											return inputs




import math
import sys






def  lowerCamelCase_	(      lowerCAmelCase__	:	str				)       ->							str:

							'''simple docstring'''






							A      						=    ''
							try:
														with open(lowerCAmelCase__			,	'rb'				) as binary_file:
																					A      						=    binary_file.read()
														for dat in data:
																					A      						=    F'''{dat:08b}'''
																					result += curr_byte
														return result
							except OSError:
														print('File not accessible'				)
														sys.exit()






def  lowerCamelCase_	(      lowerCAmelCase__	:	str				)       ->							str:

							'''simple docstring'''






							A      						=    {'0': '0', '1': '1'}
							A						,   A      						=    '', ''
							A      						=    len(lowerCAmelCase__				)

							for i in range(len(lowerCAmelCase__				)				):
														curr_string += data_bits[i]
														if curr_string not in lexicon:
																					continue

														A      						=    lexicon[curr_string]
														result += last_match_id
														A      						=    last_match_id + '0'

														if math.loga(lowerCAmelCase__				).is_integer():
																					A      						=    {}
																					for curr_key in list(lowerCAmelCase__				):
																												A      						=    lexicon.pop(lowerCAmelCase__				)
																					A      						=    new_lex

														A      						=    last_match_id + '1'
														index += 1
														A      						=    ''
							return result






def  lowerCamelCase_	(      lowerCAmelCase__	:	str			,	lowerCAmelCase__	:	str				)       ->							None:

							'''simple docstring'''






							A      						=    8
							try:
														with open(lowerCAmelCase__			,	'wb'				) as opened_file:
																					A      						=    [
																					    to_write[i : i + byte_length]
																					    for i in range(0			,	len(lowerCAmelCase__				)			,	lowerCAmelCase__				)
																					]

																					if len(result_byte_array[-1]				) % byte_length == 0:
																												result_byte_array.append('10000000'				)
																					else:
																												result_byte_array[-1] += "1" + "0" * (
																												    byte_length - len(result_byte_array[-1]				) - 1
																												)

																					for elem in result_byte_array[:-1]:
																												opened_file.write(int(lowerCAmelCase__			,	2				).to_bytes(1			,	byteorder='big'				)				)
							except OSError:
														print('File not accessible'				)
														sys.exit()






def  lowerCamelCase_	(      lowerCAmelCase__	:	str				)       ->							str:

							'''simple docstring'''






							A      						=    0
							for letter in data_bits:
														if letter == "1":
																					break
														counter += 1

							A      						=    data_bits[counter:]
							A      						=    data_bits[counter + 1 :]
							return data_bits






def  lowerCamelCase_	(      lowerCAmelCase__	:	str			,	lowerCAmelCase__	:	str				)       ->							None:

							'''simple docstring'''






							A      						=    read_file_binary(lowerCAmelCase__				)
							A      						=    remove_prefix(lowerCAmelCase__				)
							A      						=    decompress_data(lowerCAmelCase__				)
							write_file_binary(lowerCAmelCase__			,	lowerCAmelCase__				)


if __name__ == "__main__":
				compress(sys.argv[1], sys.argv[2])