


"""simple docstring"""






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


__snake_case				=				logging.get_logger(__name__)

__snake_case				=				{
    '''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
        '''https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json'''
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}


class 			__lowerCamelCase     (    __snake_case ):

     '''simple docstring'''
     A_				:		Optional[Any]			=						"""trajectory_transformer"""
     A_				:		Dict			=						["""past_key_values"""]
     A_				:		List[Any]			=						{
         """hidden_size""": """n_embd""",
         """num_attention_heads""": """n_head""",
         """num_hidden_layers""": """n_layer""",
     }


     def __init__(					self			, __UpperCAmelCase=100			, __UpperCAmelCase=5			, __UpperCAmelCase=1			, __UpperCAmelCase=1			, __UpperCAmelCase=249			, __UpperCAmelCase=6			, __UpperCAmelCase=17			, __UpperCAmelCase=25			, __UpperCAmelCase=4			, __UpperCAmelCase=4			, __UpperCAmelCase=128			, __UpperCAmelCase=0.1			, __UpperCAmelCase=0.1			, __UpperCAmelCase=0.1			, __UpperCAmelCase=0.0006			, __UpperCAmelCase=512			, __UpperCAmelCase=0.02			, __UpperCAmelCase=1e-1_2			, __UpperCAmelCase=1			, __UpperCAmelCase=True			, __UpperCAmelCase=1			, __UpperCAmelCase=50256			, __UpperCAmelCase=50256			, **__UpperCAmelCase			, )				->							List[str]:
          _a					= vocab_size
          _a					= action_weight
          _a					= reward_weight
          _a					= value_weight
          _a					= max_position_embeddings
          _a					= block_size
          _a					= action_dim
          _a					= observation_dim
          _a					= transition_dim
          _a					= learning_rate
          _a					= n_layer
          _a					= n_head
          _a					= n_embd
          _a					= embd_pdrop
          _a					= attn_pdrop
          _a					= resid_pdrop
          _a					= initializer_range
          _a					= layer_norm_eps
          _a					= kaiming_initializer_range
          _a					= use_cache
          super().__init__(pad_token_id=__UpperCAmelCase			, bos_token_id=__UpperCAmelCase			, eos_token_id=__UpperCAmelCase			, **__UpperCAmelCase							)


import unittest

from transformers import DonutProcessor


snake_case_			  = '''naver-clova-ix/donut-base'''


class       SCREAMING_SNAKE_CASE__					(unittest.TestCase     ):





    def       snake_case_				(      self):
         lowercase__    :   Dict      =       DonutProcessor.from_pretrained(a)





    def       snake_case_				(      self):
         lowercase__    :   Tuple      =       {
             'name': 'John Doe',
             'age': '99',
             'city': 'Atlanta',
             'state': 'GA',
             'zip': '30301',
             'phone': '123-4567',
             'nicknames': [{'nickname': 'Johnny'}, {'nickname': 'JD'}],
         }

         lowercase__    :   Tuple      =       (
             '<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>'
             '<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>'
             '<s_nicknames><s_nickname>Johnny</s_nickname>'
             '<sep/><s_nickname>JD</s_nickname></s_nicknames>'
         )
         lowercase__    :   str      =       self.processor.tokenajson(a)

         self.assertDictEqual(a						,   a)

