




import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest





class     snake_case  (	_snake_case							):


   '''simple docstring'''







   UpperCamelCase__	:       Any     =      (VQDiffusionScheduler,)




   def 	UpperCAmelCase       (					self     :	Any						,    **lowerCamelCase_     :	Any			)					->List[Any]:
     '''simple docstring'''







     UpperCAmelCase__    						=   {
         """num_vec_classes""": 4097,
         """num_train_timesteps""": 100,
     }

     config.update(**lowerCamelCase_			)
     return config




   def 	UpperCAmelCase       (					self     :	Tuple						,    lowerCamelCase_     :	Optional[Any]			)					->Optional[Any]:
     '''simple docstring'''







     UpperCAmelCase__    						=   4
     UpperCAmelCase__    						=   8
     UpperCAmelCase__    						=   8

     UpperCAmelCase__    						=   torch.randint(0						,    lowerCamelCase_						,    (batch_size, height * width)			)

     return sample




   @property
   def 	UpperCAmelCase       (					self     :	Any			)					->Any:
     '''simple docstring'''







     assert False




   def 	UpperCAmelCase       (					self     :	Optional[int]						,    lowerCamelCase_     :	Optional[int]			)					->Optional[int]:
     '''simple docstring'''







     def model(lowerCamelCase_     :	str						,    lowerCamelCase_     :	List[Any]						,    *lowerCamelCase_     :	Optional[int]			):
       UpperCAmelCase__						,					UpperCAmelCase__    						=   sample.shape
       UpperCAmelCase__    						=   torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)			)
       UpperCAmelCase__    						=   F.log_softmax(logits.double()						,    dim=1			).float()
       return return_value

     return model




   def 	UpperCAmelCase       (					self     :	Tuple			)					->List[str]:
     '''simple docstring'''







     for timesteps in [2, 5, 100, 1000]:
       self.check_over_configs(num_train_timesteps=lowerCamelCase_			)




   def 	UpperCAmelCase       (					self     :	Union[str, Any]			)					->int:
     '''simple docstring'''







     for num_vec_classes in [5, 100, 1000, 4000]:
       self.check_over_configs(num_vec_classes=lowerCamelCase_			)




   def 	UpperCAmelCase       (					self     :	Union[str, Any]			)					->int:
     '''simple docstring'''







     for t in [0, 50, 99]:
       self.check_over_forward(time_step=lowerCamelCase_			)







   def 	UpperCAmelCase       (					self     :	Union[str, Any]			)					->int:
     '''simple docstring'''







     pass










from typing import TYPE_CHECKING

from ...utils import _LazyModule


snake_case__ :						List[str]     =			{'''tokenization_phobert''': ['''PhobertTokenizer''']}


if TYPE_CHECKING:
   from .tokenization_phobert import PhobertTokenizer

else:
   import sys

   snake_case__ :						Tuple     =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




