




"""simple docstring"""


import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
    import torch

    from transformers.generation import DisjunctiveConstraint






@require_torch
class       lowercase(  unittest.TestCase				):







 '''simple docstring'''





 def 				UpperCamelCase_     (       self:	List[Any]	):




   '''simple docstring'''



   _snake_case							:	Optional[Any]			=						[[1, 2, 4], [1, 2, 3, 4]]
   _snake_case							:	int			=						DisjunctiveConstraint(a_	)
   self.assertTrue(isinstance(dc.token_ids,   a_	)	)

   with self.assertRaises(a_	):
     DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]	)	)

   with self.assertRaises(a_	):
     DisjunctiveConstraint([torch.LongTensor([1, 2, 4]	), torch.LongTensor([1, 2, 3, 4, 5]	)]	)


 def 				UpperCamelCase_     (       self:	Any	):




   '''simple docstring'''



   _snake_case							:	str			=						[[1, 2], [1, 2, 3, 4]]

   with self.assertRaises(a_	):
     DisjunctiveConstraint(a_	)  # fails here


 def 				UpperCamelCase_     (       self:	Optional[Any]	):




   '''simple docstring'''



   _snake_case							:	int			=						[[1, 2, 3], [1, 2, 4]]

   _snake_case							:	Union[str, Any]			=						DisjunctiveConstraint(a_	)

   _snake_case							:	Optional[Any]			=						dc.update(1	)
   _snake_case							:	List[Any]			=						stepped is True and completed is False and reset is False
   self.assertTrue(a_	)
   self.assertTrue(not dc.completed	)
   self.assertTrue(dc.current_seq == [1]	)

   _snake_case							:	Union[str, Any]			=						dc.update(2	)
   _snake_case							:	Union[str, Any]			=						stepped is True and completed is False and reset is False
   self.assertTrue(a_	)
   self.assertTrue(not dc.completed	)
   self.assertTrue(dc.current_seq == [1, 2]	)

   _snake_case							:	Dict			=						dc.update(3	)
   _snake_case							:	Optional[Any]			=						stepped is True and completed is True and reset is False
   self.assertTrue(a_	)
   self.assertTrue(dc.completed	)  # Completed!
   self.assertTrue(dc.current_seq == [1, 2, 3]	)


 def 				UpperCamelCase_     (       self:	Optional[int]	):




   '''simple docstring'''



   _snake_case							:	List[str]			=						[[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

   _snake_case							:	Union[str, Any]			=						DisjunctiveConstraint(a_	)

   _snake_case							:	Any			=						dc.update(1	)
   self.assertTrue(not dc.completed	)
   self.assertTrue(dc.current_seq == [1]	)

   _snake_case							:	List[Any]			=						dc.update(2	)
   self.assertTrue(not dc.completed	)
   self.assertTrue(dc.current_seq == [1, 2]	)

   _snake_case							:	Union[str, Any]			=						dc.update(4	)
   self.assertTrue(not dc.completed	)
   self.assertTrue(dc.current_seq == [1, 2, 4]	)

   _snake_case							:	str			=						dc.update(5	)
   self.assertTrue(dc.completed	)  # Completed!
   self.assertTrue(dc.current_seq == [1, 2, 4, 5]	)

   dc.reset()

   _snake_case							:	Optional[Any]			=						dc.update(1	)
   self.assertTrue(not dc.completed	)
   self.assertTrue(dc.remaining() == 3	)
   self.assertTrue(dc.current_seq == [1]	)

   _snake_case							:	Optional[int]			=						dc.update(2	)
   self.assertTrue(not dc.completed	)
   self.assertTrue(dc.remaining() == 2	)
   self.assertTrue(dc.current_seq == [1, 2]	)

   _snake_case							:	Optional[Any]			=						dc.update(5	)
   self.assertTrue(dc.completed	)  # Completed!
   self.assertTrue(dc.remaining() == 0	)
   self.assertTrue(dc.current_seq == [1, 2, 5]	)








"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

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


A_      			=       logging.get_logger(__name__)

A_      			=       {
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}






class       lowercase(  __a				):







 '''simple docstring'''





 lowercase__				      =      "roformer"


 def __init__(       self:	List[str],   a_:	Tuple=50_000,   a_:	Optional[Any]=None,   a_:	List[str]=768,   a_:	Union[str, Any]=12,   a_:	Optional[int]=12,   a_:	Optional[Any]=3_072,   a_:	List[str]="gelu",   a_:	List[str]=0.1,   a_:	Tuple=0.1,   a_:	Optional[int]=1_536,   a_:	Any=2,   a_:	Optional[int]=0.02,   a_:	Tuple=1E-12,   a_:	Dict=0,   a_:	str=False,   a_:	Dict=True,   **a_:	Dict,   ):




   '''simple docstring'''



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

   _snake_case							:	int			=						vocab_size
   _snake_case							:	int			=						hidden_size if embedding_size is None else embedding_size
   _snake_case							:	Dict			=						hidden_size
   _snake_case							:	Optional[int]			=						num_hidden_layers
   _snake_case							:	Any			=						num_attention_heads
   _snake_case							:	Dict			=						hidden_act
   _snake_case							:	Optional[int]			=						intermediate_size
   _snake_case							:	List[Any]			=						hidden_dropout_prob
   _snake_case							:	Union[str, Any]			=						attention_probs_dropout_prob
   _snake_case							:	Any			=						max_position_embeddings
   _snake_case							:	Tuple			=						type_vocab_size
   _snake_case							:	List[Any]			=						initializer_range
   _snake_case							:	List[Any]			=						layer_norm_eps
   _snake_case							:	Optional[Any]			=						rotary_value
   _snake_case							:	List[str]			=						use_cache







class       lowercase(  __a				):







 '''simple docstring'''





 @property
 def 				UpperCamelCase_     (       self:	Dict	):




   '''simple docstring'''



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


