





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    _SCREAMING_SNAKE_CASE						(	unittest.TestCase    ):







 '''simple docstring'''

 def 							SCREAMING_SNAKE_CASE_					(self				:   List[Any])       ->Any:



   '''simple docstring'''



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

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

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

 def 							SCREAMING_SNAKE_CASE_					(self				:   int)       ->List[str]:



   '''simple docstring'''



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

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

 def 							SCREAMING_SNAKE_CASE_					(self				:   Any)       ->Tuple:



   '''simple docstring'''



   lowerCamelCase__:      Tuple			  =[[1, 2, 3], [1, 2, 4]]

   lowerCamelCase__:      List[Any]			  =DisjunctiveConstraint(UpperCAmelCase_)

   lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__:      Tuple			  =dc.update(1)
   lowerCamelCase__:      str			  =stepped is True and completed is False and reset is False
   self.assertTrue(UpperCAmelCase_)
   self.assertTrue(not dc.completed)
   self.assertTrue(dc.current_seq == [1])

   lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__:      List[str]			  =dc.update(2)
   lowerCamelCase__:      Optional[Any]			  =stepped is True and completed is False and reset is False
   self.assertTrue(UpperCAmelCase_)
   self.assertTrue(not dc.completed)
   self.assertTrue(dc.current_seq == [1, 2])

   lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__:      Optional[int]			  =dc.update(3)
   lowerCamelCase__:      Tuple			  =stepped is True and completed is True and reset is False
   self.assertTrue(UpperCAmelCase_)
   self.assertTrue(dc.completed)  # Completed!
   self.assertTrue(dc.current_seq == [1, 2, 3])







 def 							SCREAMING_SNAKE_CASE_					(self				:   List[str])       ->str:



   '''simple docstring'''



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

   lowerCamelCase__:      Dict			  =DisjunctiveConstraint(UpperCAmelCase_)

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

   lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__:      Tuple			  =dc.update(2)
   self.assertTrue(not dc.completed)
   self.assertTrue(dc.current_seq == [1, 2])

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

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

   dc.reset()

   lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__:      Tuple			  =dc.update(1)
   self.assertTrue(not dc.completed)
   self.assertTrue(dc.remaining() == 3)
   self.assertTrue(dc.current_seq == [1])

   lowerCamelCase__  ,					lowerCamelCase__  ,					lowerCamelCase__:      Tuple			  =dc.update(2)
   self.assertTrue(not dc.completed)
   self.assertTrue(dc.remaining() == 2)
   self.assertTrue(dc.current_seq == [1, 2])

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









from typing import List

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase								=						logging.get_logger(__name__)

__UpperCAmelCase								=						{
    'snap-research/efficientformer-l1-300': (
        'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json'
    ),
}



class   lowerCamelCase      (_snake_case			):







		'''simple docstring'''



		_snake_case    :    Optional[int]       						=  '''efficientformer'''



		def __init__(							self				,		_UpperCamelCase = [3, 2, 6, 4]				,		_UpperCamelCase = [4_8, 9_6, 2_2_4, 4_4_8]				,		_UpperCamelCase = [True, True, True, True]				,		_UpperCamelCase = 4_4_8				,		_UpperCamelCase = 3_2				,		_UpperCamelCase = 4				,		_UpperCamelCase = 7				,		_UpperCamelCase = 5				,		_UpperCamelCase = 8				,		_UpperCamelCase = 4				,		_UpperCamelCase = 0.0				,		_UpperCamelCase = 1_6				,		_UpperCamelCase = 3				,		_UpperCamelCase = 3				,		_UpperCamelCase = 3				,		_UpperCamelCase = 2				,		_UpperCamelCase = 1				,		_UpperCamelCase = 0.0				,		_UpperCamelCase = 1				,		_UpperCamelCase = True				,		_UpperCamelCase = True				,		_UpperCamelCase = 1E-5				,		_UpperCamelCase = "gelu"				,		_UpperCamelCase = 0.02				,		_UpperCamelCase = 1E-12				,		_UpperCamelCase = 2_2_4				,		_UpperCamelCase = 1E-05				,		**_UpperCamelCase				,		)	->							None:
							super().__init__(**_UpperCamelCase   )

							UpperCAmelCase_    :      int            =						hidden_act
							UpperCAmelCase_    :      Union[str, Any]            =						hidden_dropout_prob
							UpperCAmelCase_    :      Tuple            =						hidden_sizes
							UpperCAmelCase_    :      Union[str, Any]            =						num_hidden_layers
							UpperCAmelCase_    :      List[str]            =						num_attention_heads
							UpperCAmelCase_    :      List[Any]            =						initializer_range
							UpperCAmelCase_    :      int            =						layer_norm_eps
							UpperCAmelCase_    :      List[str]            =						patch_size
							UpperCAmelCase_    :      Union[str, Any]            =						num_channels
							UpperCAmelCase_    :      Optional[Any]            =						depths
							UpperCAmelCase_    :      List[Any]            =						mlp_expansion_ratio
							UpperCAmelCase_    :      List[str]            =						downsamples
							UpperCAmelCase_    :      List[Any]            =						dim
							UpperCAmelCase_    :      Tuple            =						key_dim
							UpperCAmelCase_    :      Optional[int]            =						attention_ratio
							UpperCAmelCase_    :      str            =						resolution
							UpperCAmelCase_    :      Dict            =						pool_size
							UpperCAmelCase_    :      Union[str, Any]            =						downsample_patch_size
							UpperCAmelCase_    :      List[str]            =						downsample_stride
							UpperCAmelCase_    :      List[str]            =						downsample_pad
							UpperCAmelCase_    :      Any            =						drop_path_rate
							UpperCAmelCase_    :      Dict            =						num_metaad_blocks
							UpperCAmelCase_    :      Dict            =						distillation
							UpperCAmelCase_    :      int            =						use_layer_scale
							UpperCAmelCase_    :      Any            =						layer_scale_init_value
							UpperCAmelCase_    :      Any            =						image_size
							UpperCAmelCase_    :      Dict            =						batch_norm_eps






