

import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class   __lowercase      (_UpperCAmelCase		,   unittest.TestCase ):
 _UpperCamelCase			  =  LxmertTokenizer
 _UpperCamelCase			  =  LxmertTokenizerFast
 _UpperCamelCase			  =  True
 _UpperCamelCase			  =  True
 def 	UpperCamelCase__  (							self					)					->int:



       '''simple docstring'''





       super().setUp()

       __lowerCAmelCase					:						str					=					[
           '''[UNK]''',
           '''[CLS]''',
           '''[SEP]''',
           '''want''',
           '''##want''',
           '''##ed''',
           '''wa''',
           '''un''',
           '''runn''',
           '''##ing''',
           ''',''',
           '''low''',
           '''lowest''',
       ]
       __lowerCAmelCase					:						Any					=					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 	UpperCamelCase__  (							self      ,							A_					)					->Dict:



       '''simple docstring'''





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



       '''simple docstring'''





       __lowerCAmelCase					:						Any					=					self.tokenizer_class(self.vocab_file					)

       __lowerCAmelCase					:						Union[str, Any]					=					tokenizer.tokenize('''UNwant\u00E9d,running'''					)
       self.assertListEqual(A_      ,							['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']					)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(A_					)      ,							[7, 4, 5, 10, 8, 9]					)





 def 	UpperCamelCase__  (							self					)					->Dict:



       '''simple docstring'''





       if not self.test_rust_tokenizer:
             return

       __lowerCAmelCase					:						Optional[int]					=					self.get_tokenizer()
       __lowerCAmelCase					:						Union[str, Any]					=					self.get_rust_tokenizer()

       __lowerCAmelCase					:						Optional[int]					=					'''I was born in 92000, and this is falsé.'''

       __lowerCAmelCase					:						Optional[Any]					=					tokenizer.tokenize(A_					)
       __lowerCAmelCase					:						Tuple					=					rust_tokenizer.tokenize(A_					)
       self.assertListEqual(A_      ,							A_					)

       __lowerCAmelCase					:						Optional[Any]					=					tokenizer.encode(A_      ,							add_special_tokens=A_					)
       __lowerCAmelCase					:						Union[str, Any]					=					rust_tokenizer.encode(A_      ,							add_special_tokens=A_					)
       self.assertListEqual(A_      ,							A_					)

       __lowerCAmelCase					:						Tuple					=					self.get_rust_tokenizer()
       __lowerCAmelCase					:						Tuple					=					tokenizer.encode(A_					)
       __lowerCAmelCase					:						List[Any]					=					rust_tokenizer.encode(A_					)
       self.assertListEqual(A_      ,							A_					)





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


_UpperCamelCase 			=		logging.get_logger(__name__)

_UpperCamelCase 			=		{
    "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   __lowercase      (_UpperCAmelCase ):
 _UpperCamelCase			  =  """trajectory_transformer"""
 _UpperCamelCase			  =  ["""past_key_values"""]
 _UpperCamelCase			  =  {
     """hidden_size""": """n_embd""",
     """num_attention_heads""": """n_head""",
     """num_hidden_layers""": """n_layer""",
 }
 def __init__(							self      ,							A_=100      ,							A_=5      ,							A_=1      ,							A_=1      ,							A_=249      ,							A_=6      ,							A_=17      ,							A_=25      ,							A_=4      ,							A_=4      ,							A_=128      ,							A_=0.1      ,							A_=0.1      ,							A_=0.1      ,							A_=0.0_006      ,							A_=512      ,							A_=0.02      ,							A_=1e-12      ,							A_=1      ,							A_=True      ,							A_=1      ,							A_=5_0256      ,							A_=5_0256      ,							**A_      ,							)					->int:



       '''simple docstring'''





       __lowerCAmelCase					:						Any					=					vocab_size
       __lowerCAmelCase					:						Tuple					=					action_weight
       __lowerCAmelCase					:						Tuple					=					reward_weight
       __lowerCAmelCase					:						Union[str, Any]					=					value_weight
       __lowerCAmelCase					:						List[str]					=					max_position_embeddings
       __lowerCAmelCase					:						str					=					block_size
       __lowerCAmelCase					:						Optional[Any]					=					action_dim
       __lowerCAmelCase					:						Union[str, Any]					=					observation_dim
       __lowerCAmelCase					:						Union[str, Any]					=					transition_dim
       __lowerCAmelCase					:						Dict					=					learning_rate
       __lowerCAmelCase					:						Any					=					n_layer
       __lowerCAmelCase					:						Any					=					n_head
       __lowerCAmelCase					:						Optional[int]					=					n_embd
       __lowerCAmelCase					:						str					=					embd_pdrop
       __lowerCAmelCase					:						Dict					=					attn_pdrop
       __lowerCAmelCase					:						Optional[int]					=					resid_pdrop
       __lowerCAmelCase					:						Union[str, Any]					=					initializer_range
       __lowerCAmelCase					:						Optional[int]					=					layer_norm_eps
       __lowerCAmelCase					:						Any					=					kaiming_initializer_range
       __lowerCAmelCase					:						List[str]					=					use_cache
       super().__init__(pad_token_id=A_      ,							bos_token_id=A_      ,							eos_token_id=A_      ,							**A_					)


