
import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin

class     _UpperCamelCase			(   _A       ,    unittest.TestCase					):






			'''simple docstring'''

			__UpperCamelCase :  Tuple    =	CTRLTokenizer
			__UpperCamelCase :  int    =	False
			__UpperCamelCase :  List[str]    =	False

			def  lowerCAmelCase__		(    self	:    List[str] ):
							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							UpperCamelCase_:							int		=  ["""adapt""", """re@@""", """a@@""", """apt""", """c@@""", """t""", """<unk>"""]
							UpperCamelCase_:							int		=  dict(zip(snake_case_  ,		range(len(snake_case_ ) ) ) )
							UpperCamelCase_:							Union[str, Any]		=  ["""#version: 0.2""", """a p""", """ap t</w>""", """r e""", """a d""", """ad apt</w>""", """"""]
							UpperCamelCase_:							Tuple		=  {"""unk_token""": """<unk>"""}

							UpperCamelCase_:							Optional[Any]		=  os.path.join(self.tmpdirname  ,		VOCAB_FILES_NAMES["""vocab_file"""] )
							UpperCamelCase_:							Dict		=  os.path.join(self.tmpdirname  ,		VOCAB_FILES_NAMES["""merges_file"""] )
							with open(self.vocab_file  ,		"""w"""  ,		encoding="""utf-8""" ) as fp:
											fp.write(json.dumps(snake_case_ ) + """\n""" )
							with open(self.merges_file  ,		"""w"""  ,		encoding="""utf-8""" ) as fp:
											fp.write("""\n""".join(snake_case_ ) )

			def  lowerCAmelCase__		(    self	:    Optional[int]  ,		**snake_case_	:    int ):
							kwargs.update(self.special_tokens_map )
							return CTRLTokenizer.from_pretrained(self.tmpdirname  ,		**snake_case_ )

			def  lowerCAmelCase__		(    self	:    Optional[int]  ,		snake_case_	:    List[str] ):
							UpperCamelCase_:							Dict		=  """adapt react readapt apt"""
							UpperCamelCase_:							List[str]		=  """adapt react readapt apt"""
							return input_text, output_text




			def  lowerCAmelCase__		(    self	:    List[str] ):
							UpperCamelCase_:							str		=  CTRLTokenizer(self.vocab_file  ,		self.merges_file  ,		**self.special_tokens_map )
							UpperCamelCase_:							List[Any]		=  """adapt react readapt apt"""
							UpperCamelCase_:							Optional[int]		=  """adapt re@@ a@@ c@@ t re@@ adapt apt""".split()
							UpperCamelCase_:							int		=  tokenizer.tokenize(snake_case_ )
							self.assertListEqual(snake_case_  ,		snake_case_ )

							UpperCamelCase_:							List[Any]		=  tokens + [tokenizer.unk_token]

							UpperCamelCase_:							Union[str, Any]		=  [0, 1, 2, 4, 5, 1, 0, 3, 6]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case_ )  ,		snake_case_ )








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


lowerCamelCase_  :	Optional[int] 				=					logging.get_logger(__name__)

lowerCamelCase_  :	Optional[int] 				=					{"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}

class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  int    =	"""ctrl"""
			__UpperCamelCase :  Dict    =	["""past_key_values"""]
			__UpperCamelCase :  List[str]    =	{
			    """max_position_embeddings""": """n_positions""",
			    """hidden_size""": """n_embd""",
			    """num_attention_heads""": """n_head""",
			    """num_hidden_layers""": """n_layer""",
			}

			def __init__(    self	:    Dict  ,		snake_case_	:    Any=24_6534  ,		snake_case_	:    Dict=256  ,		snake_case_	:    str=1280  ,		snake_case_	:    Optional[int]=8192  ,		snake_case_	:    Union[str, Any]=48  ,		snake_case_	:    Any=16  ,		snake_case_	:    Optional[int]=0.1  ,		snake_case_	:    Any=0.1  ,		snake_case_	:    Any=1e-6  ,		snake_case_	:    Optional[Any]=0.02  ,		snake_case_	:    Optional[int]=True  ,		**snake_case_	:    Union[str, Any]  ,		):
							UpperCamelCase_:							Union[str, Any]		=  vocab_size
							UpperCamelCase_:							Union[str, Any]		=  n_positions
							UpperCamelCase_:							Optional[int]		=  n_embd
							UpperCamelCase_:							int		=  n_layer
							UpperCamelCase_:							str		=  n_head
							UpperCamelCase_:							Optional[int]		=  dff
							UpperCamelCase_:							Optional[Any]		=  resid_pdrop
							UpperCamelCase_:							Union[str, Any]		=  embd_pdrop
							UpperCamelCase_:							List[str]		=  layer_norm_epsilon
							UpperCamelCase_:							Optional[Any]		=  initializer_range

							UpperCamelCase_:							Optional[Any]		=  use_cache

							super().__init__(**snake_case_ )






