

import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class __SCREAMING_SNAKE_CASE     (	_snake_case			,						unittest.TestCase		):
    SCREAMING_SNAKE_CASE__      =FunnelTokenizer
    SCREAMING_SNAKE_CASE__      =FunnelTokenizerFast
    SCREAMING_SNAKE_CASE__      =True
    SCREAMING_SNAKE_CASE__      =True






    def 						__lowerCAmelCase    (       self )   ->					Optional[int]:
       super().setUp()

       __SCREAMING_SNAKE_CASE       =				[
           '''<unk>''',
           '''<cls>''',
           '''<sep>''',
           '''want''',
           '''##want''',
           '''##ed''',
           '''wa''',
           '''un''',
           '''runn''',
           '''##ing''',
           ''',''',
           '''low''',
           '''lowest''',
       ]
       __SCREAMING_SNAKE_CASE       =				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] ) )






    def 						__lowerCAmelCase    (       self,		**_a )   ->					Optional[Any]:
       return FunnelTokenizer.from_pretrained(self.tmpdirname,		**__lowerCamelCase )






    def 						__lowerCAmelCase    (       self,		**_a )   ->					Tuple:
       return FunnelTokenizerFast.from_pretrained(self.tmpdirname,		**__lowerCamelCase )






    def 						__lowerCAmelCase    (       self,		_a )   ->					int:
       __SCREAMING_SNAKE_CASE       =				'''UNwant\u00E9d,running'''
       __SCREAMING_SNAKE_CASE       =				'''unwanted, running'''
       return input_text, output_text






    def 						__lowerCAmelCase    (       self )   ->					str:
       __SCREAMING_SNAKE_CASE       =				self.tokenizer_class(self.vocab_file )

       __SCREAMING_SNAKE_CASE       =				tokenizer.tokenize("UNwant\u00E9d,running" )
       self.assertListEqual(__lowerCamelCase,		["un", "##want", "##ed", ",", "runn", "##ing"] )
       self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase ),		[7, 4, 5, 10, 8, 9] )






    def 						__lowerCAmelCase    (       self )   ->					Any:
       __SCREAMING_SNAKE_CASE       =				self.get_tokenizers(do_lower_case=__lowerCamelCase )
       for tokenizer in tokenizers:
          __SCREAMING_SNAKE_CASE       =				tokenizer("UNwant\u00E9d,running" )
          __SCREAMING_SNAKE_CASE       =				len(inputs["input_ids"] ) - 1
          self.assertListEqual(inputs["token_type_ids"],		[2] + [0] * sentence_len )

          __SCREAMING_SNAKE_CASE       =				tokenizer("UNwant\u00E9d,running",		"UNwant\u00E9d,running" )
          self.assertListEqual(inputs["token_type_ids"],		[2] + [0] * sentence_len + [1] * sentence_len )





'''simple docstring'''





import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

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


__lowerCamelCase												=						logging.get_logger(__name__)

__lowerCamelCase												=						{
    '''nvidia/segformer-b0-finetuned-ade-512-512''': (
        '''https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json'''
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}




class 				UpperCAmelCase			(			_snake_case						):
 UpperCAmelCase				=					"segformer"


 def __init__(      self							:	Dict			,       __lowerCamelCase							:	Dict=3			,       __lowerCamelCase							:	List[str]=4			,       __lowerCamelCase							:	List[Any]=[2, 2, 2, 2]			,       __lowerCamelCase							:	List[str]=[8, 4, 2, 1]			,       __lowerCamelCase							:	Optional[Any]=[3_2, 6_4, 1_6_0, 2_5_6]			,       __lowerCamelCase							:	Tuple=[7, 3, 3, 3]			,       __lowerCamelCase							:	Tuple=[4, 2, 2, 2]			,       __lowerCamelCase							:	Any=[1, 2, 5, 8]			,       __lowerCamelCase							:	Optional[Any]=[4, 4, 4, 4]			,       __lowerCamelCase							:	Union[str, Any]="gelu"			,       __lowerCamelCase							:	Dict=0.0			,       __lowerCamelCase							:	Union[str, Any]=0.0			,       __lowerCamelCase							:	Tuple=0.1			,       __lowerCamelCase							:	Optional[Any]=0.02			,       __lowerCamelCase							:	Optional[int]=0.1			,       __lowerCamelCase							:	str=1e-6			,       __lowerCamelCase							:	List[Any]=2_5_6			,       __lowerCamelCase							:	int=2_5_5			,       **__lowerCamelCase							:	str			,       ):
    super().__init__(**__lowerCamelCase )

    if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
       warnings.warn(
           '''Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'''
           ''' removed, as the behaviour will default to that of reshape_last_stage = True.'''			,       __lowerCamelCase			,       )

    UpperCAmelCase__	:Dict      =      num_channels
    UpperCAmelCase__	:List[Any]      =      num_encoder_blocks
    UpperCAmelCase__	:List[str]      =      depths
    UpperCAmelCase__	:str      =      sr_ratios
    UpperCAmelCase__	:Optional[Any]      =      hidden_sizes
    UpperCAmelCase__	:List[str]      =      patch_sizes
    UpperCAmelCase__	:List[str]      =      strides
    UpperCAmelCase__	:List[str]      =      mlp_ratios
    UpperCAmelCase__	:Dict      =      num_attention_heads
    UpperCAmelCase__	:Tuple      =      hidden_act
    UpperCAmelCase__	:List[str]      =      hidden_dropout_prob
    UpperCAmelCase__	:List[Any]      =      attention_probs_dropout_prob
    UpperCAmelCase__	:int      =      classifier_dropout_prob
    UpperCAmelCase__	:str      =      initializer_range
    UpperCAmelCase__	:List[str]      =      drop_path_rate
    UpperCAmelCase__	:Dict      =      layer_norm_eps
    UpperCAmelCase__	:List[str]      =      decoder_hidden_size
    UpperCAmelCase__	:Optional[int]      =      kwargs.get('''reshape_last_stage'''			,       __lowerCamelCase )
    UpperCAmelCase__	:str      =      semantic_loss_ignore_index




class 				UpperCAmelCase			(			_snake_case						):
 UpperCAmelCase				=					version.parse("1.11"						)


 @property
 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[Any] ):
    return OrderedDict(
        [
            ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
        ] )


 @property
 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[int] ):
    return 1e-4





 @property
 def        __SCREAMING_SNAKE_CASE					(      self							:	List[str] ):
    return 1_2



