

'''simple docstring'''





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 		__SCREAMING_SNAKE_CASE							(			lowercase__      ):
				lowerCamelCase_		       =    'longformer'







				def __init__(       self     :		List[str]		,					UpperCAmelCase__     :		Union[List[int], int] = 512		,					UpperCAmelCase__     :		int = 2		,					UpperCAmelCase__     :		int = 1		,					UpperCAmelCase__     :		int = 0		,					UpperCAmelCase__     :		int = 2		,					UpperCAmelCase__     :		int = 30522		,					UpperCAmelCase__     :		int = 768		,					UpperCAmelCase__     :		int = 12		,					UpperCAmelCase__     :		int = 12		,					UpperCAmelCase__     :		int = 3072		,					UpperCAmelCase__     :		str = "gelu"		,					UpperCAmelCase__     :		float = 0.1		,					UpperCAmelCase__     :		float = 0.1		,					UpperCAmelCase__     :		int = 512		,					UpperCAmelCase__     :		int = 2		,					UpperCAmelCase__     :		float = 0.02		,					UpperCAmelCase__     :		float = 1E-12		,					UpperCAmelCase__     :		bool = False		,					**UpperCAmelCase__     :		Optional[int]		,					):
										'''simple docstring'''
										super().__init__(pad_token_id=UpperCAmelCase__		,					**UpperCAmelCase__   )

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





class 		__SCREAMING_SNAKE_CASE							(			lowercase__      ):







				def __init__(       self     :		Any		,					UpperCAmelCase__     :		"PretrainedConfig"		,					UpperCAmelCase__     :		str = "default"		,					UpperCAmelCase__     :		"List[PatchingSpec]" = None   ):
										'''simple docstring'''
										super().__init__(UpperCAmelCase__		,					UpperCAmelCase__		,					UpperCAmelCase__   )
										lowercase :							Tuple    		=True







				@property
				def  lowerCamelCase_	(       self     :		int   ):
										'''simple docstring'''
										if self.task == "multiple-choice":
																lowercase :							Optional[Any]    		={0: '''batch''', 1: '''choice''', 2: '''sequence'''}
										else:
																lowercase :							Union[str, Any]    		={0: '''batch''', 1: '''sequence'''}
										return OrderedDict(
										    [
										        ('''input_ids''', dynamic_axis),
										        ('''attention_mask''', dynamic_axis),
										        ('''global_attention_mask''', dynamic_axis),
										    ]   )







				@property
				def  lowerCamelCase_	(       self     :		Union[str, Any]   ):
										'''simple docstring'''
										lowercase :							Any    		=super().outputs
										if self.task == "default":
																lowercase :							List[Any]    		={0: '''batch'''}
										return outputs







				@property
				def  lowerCamelCase_	(       self     :		Union[str, Any]   ):
										'''simple docstring'''
										return 1E-4







				@property
				def  lowerCamelCase_	(       self     :		Optional[int]   ):
										'''simple docstring'''
										# needs to be >= 14 to support tril operator
										return max(super().default_onnx_opset		,					14   )







				def  lowerCamelCase_	(       self     :		str		,					UpperCAmelCase__     :		"PreTrainedTokenizerBase"		,					UpperCAmelCase__     :		int = -1		,					UpperCAmelCase__     :		int = -1		,					UpperCAmelCase__     :		bool = False		,					UpperCAmelCase__     :		Optional[TensorType] = None		,					):
										'''simple docstring'''
										lowercase :							Optional[int]    		=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
										lowercase :							Any    		=torch.zeros_like(inputs['''input_ids''']   )
										# make every second token global
										lowercase :							List[str]    		=1

										return inputs








'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase_    						=       {"""configuration_mbart""": ["""MBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MBartConfig""", """MBartOnnxConfig"""]}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_    						=       ["""MBartTokenizer"""]

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_    						=       ["""MBartTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_    						=       [
							    """MBART_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """MBartForCausalLM""",
							    """MBartForConditionalGeneration""",
							    """MBartForQuestionAnswering""",
							    """MBartForSequenceClassification""",
							    """MBartModel""",
							    """MBartPreTrainedModel""",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_    						=       [
							    """TFMBartForConditionalGeneration""",
							    """TFMBartModel""",
							    """TFMBartPreTrainedModel""",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_    						=       [
							    """FlaxMBartForConditionalGeneration""",
							    """FlaxMBartForQuestionAnswering""",
							    """FlaxMBartForSequenceClassification""",
							    """FlaxMBartModel""",
							    """FlaxMBartPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_mbart import MBartTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_mbart_fast import MBartTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mbart import (
														    MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MBartForCausalLM,
														    MBartForConditionalGeneration,
														    MBartForQuestionAnswering,
														    MBartForSequenceClassification,
														    MBartModel,
														    MBartPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_mbart import (
														    FlaxMBartForConditionalGeneration,
														    FlaxMBartForQuestionAnswering,
														    FlaxMBartForSequenceClassification,
														    FlaxMBartModel,
														    FlaxMBartPreTrainedModel,
														)

else:
							import sys

							UpperCamelCase_    						=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





