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


__lowercase											=      logging.get_logger(__name__)

__lowercase											=      {
    '''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_  (     UpperCAmelCase_				):






    '''simple docstring'''






    a__			:		List[Any]      			=   """longformer"""







    def __init__(			self				,				__lowercase = 512				,				__lowercase = 2				,				__lowercase = 1				,				__lowercase = 0				,				__lowercase = 2				,				__lowercase = 30_522				,				__lowercase = 768				,				__lowercase = 12				,				__lowercase = 12				,				__lowercase = 3_072				,				__lowercase = "gelu"				,				__lowercase = 0.1				,				__lowercase = 0.1				,				__lowercase = 512				,				__lowercase = 2				,				__lowercase = 0.02				,				__lowercase = 1E-1_2				,				__lowercase = False				,				**__lowercase				,				) ->			List[Any]:
        super().__init__(pad_token_id=__lowercase				,				**__lowercase)

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


class 			lowerCamelCase_  (     UpperCAmelCase_				):






    '''simple docstring'''






    def __init__(			self				,				__lowercase				,				__lowercase = "default"				,				__lowercase = None) ->			Optional[Any]:
        super().__init__(__lowercase				,				__lowercase				,				__lowercase)
        __UpperCamelCase  :Union[str, Any]    						=	True







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







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







    @property
    def     UpperCamelCase__     (			self) ->			float:
        return 1E-4







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







    def     UpperCamelCase__     (			self				,				__lowercase				,				__lowercase = -1				,				__lowercase = -1				,				__lowercase = False				,				__lowercase = None				,				) ->			Mapping[str, Any]:
        __UpperCamelCase  :str    						=	super().generate_dummy_inputs(
            preprocessor=__lowercase				,				batch_size=__lowercase				,				seq_length=__lowercase				,				is_pair=__lowercase				,				framework=__lowercase)
        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  :Any    						=	torch.zeros_like(inputs['''input_ids'''])
        # make every second token global
        __UpperCamelCase  :Dict    						=	1

        return inputs






import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin


@require_jieba
class 			lowerCamelCase_  (     UpperCAmelCase_		,			unittest.TestCase				):






    '''simple docstring'''






    a__			:		Any      			=   CpmAntTokenizer
    a__			:		Optional[Any]      			=   False







    def     UpperCamelCase__     (			self) ->			Any:
        super().setUp()

        __UpperCamelCase  :Optional[int]    						=	[
            '''<d>''',
            '''</d>''',
            '''<s>''',
            '''</s>''',
            '''</_>''',
            '''<unk>''',
            '''<pad>''',
            '''</n>''',
            '''我''',
            '''是''',
            '''C''',
            '''P''',
            '''M''',
            '''A''',
            '''n''',
            '''t''',
        ]
        __UpperCamelCase  :Optional[int]    						=	os.path.join(self.tmpdirname				,				VOCAB_FILES_NAMES['''vocab_file'''])
        with open(self.vocab_file				,				'''w'''				,				encoding='''utf-8''') as vocab_writer:
            vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]))







    @tooslow
    def     UpperCamelCase__     (			self) ->			Dict:
        __UpperCamelCase  :Tuple    						=	CpmAntTokenizer.from_pretrained('''openbmb/cpm-ant-10b''')
        __UpperCamelCase  :Dict    						=	'''今天天气真好！'''
        __UpperCamelCase  :Tuple    						=	['''今天''', '''天气''', '''真''', '''好''', '''！''']
        __UpperCamelCase  :Optional[Any]    						=	tokenizer.tokenize(__lowercase)
        self.assertListEqual(__lowercase				,				__lowercase)
        __UpperCamelCase  :int    						=	'''今天天气真好！'''
        __UpperCamelCase  :List[str]    						=	[tokenizer.bos_token] + tokens

        __UpperCamelCase  :List[str]    						=	[6, 9_802, 14_962, 2_082, 831, 244]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowercase)				,				__lowercase)

        __UpperCamelCase  :Dict    						=	tokenizer.decode(__lowercase)
        self.assertEqual(__lowercase				,				__lowercase)





