import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A__           =							logging.get_logger(__name__)


A__           =							{
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

A__           =							{
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

A__           =							{"""facebook/blenderbot_small-90M""": 512}





def  _lowerCamelCase					(   a_				: List[str]):
			lowerCamelCase						:Tuple						  =     set()
			lowerCamelCase						:str						  =     word[0]
			for char in word[1:]:
						pairs.add((prev_char, char))
						lowerCamelCase						:List[Any]						  =     char

			lowerCamelCase						:Any						  =     set(_snake_case)
			return pairs


class   _lowerCAmelCase		(     __UpperCAmelCase				):
							_UpperCAmelCase						    =     VOCAB_FILES_NAMES
							_UpperCAmelCase						    =     PRETRAINED_VOCAB_FILES_MAP
							_UpperCAmelCase						    =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_UpperCAmelCase						    =     ["""input_ids""", """attention_mask"""]







							def __init__(				self     :    Tuple	,					__snake_case     :    Any	,					__snake_case     :    Optional[int]	,					__snake_case     :    List[str]="__start__"	,					__snake_case     :    str="__end__"	,					__snake_case     :    Union[str, Any]="__unk__"	,					__snake_case     :    Optional[int]="__null__"	,					**__snake_case     :    Union[str, Any]	,					):
										super().__init__(unk_token=UpperCAmelCase_	,					bos_token=UpperCAmelCase_	,					eos_token=UpperCAmelCase_	,					pad_token=UpperCAmelCase_	,					**UpperCAmelCase_		)

										with open(UpperCAmelCase_	,					encoding='''utf-8'''		) as vocab_handle:
													lowerCamelCase						:Dict						  =     json.load(UpperCAmelCase_		)
										lowerCamelCase						:int						  =     {v: k for k, v in self.encoder.items()}
										with open(UpperCAmelCase_	,					encoding='''utf-8'''		) as merges_handle:
													lowerCamelCase						:int						  =     merges_handle.read().split('''\n'''		)[1:-1]
										lowerCamelCase						:Optional[Any]						  =     [tuple(merge.split()		) for merge in merges]
										lowerCamelCase						:Union[str, Any]						  =     dict(zip(UpperCAmelCase_	,					range(len(UpperCAmelCase_		)		)		)		)
										lowerCamelCase						:Tuple						  =     {}







							@property
							def 				snake_case  (				self     :    Tuple		):
										return len(self.encoder		)







							def 				snake_case  (				self     :    List[Any]		):
										return dict(self.encoder	,					**self.added_tokens_encoder		)







							def 				snake_case  (				self     :    str	,					__snake_case     :    Optional[Any]		):
										if token in self.cache:
													return self.cache[token]
										lowerCamelCase						:List[str]						  =     re.sub('''([.,!?()])'''	,					R''' \1'''	,					UpperCAmelCase_		)
										lowerCamelCase						:Optional[Any]						  =     re.sub('''(\')'''	,					R''' \1 '''	,					UpperCAmelCase_		)
										lowerCamelCase						:Optional[int]						  =     re.sub(R'''\s{2,}'''	,					''' '''	,					UpperCAmelCase_		)
										if "\n" in token:
													lowerCamelCase						:List[Any]						  =     token.replace('''\n'''	,					''' __newln__'''		)

										lowerCamelCase						:str						  =     token.split(''' '''		)
										lowerCamelCase						:Dict						  =     []
										for token in tokens:
													if not len(UpperCAmelCase_		):
																continue

													lowerCamelCase						:Tuple						  =     token.lower()
													lowerCamelCase						:List[Any]						  =     tuple(UpperCAmelCase_		)
													lowerCamelCase						:Union[str, Any]						  =     tuple(list(word[:-1]		) + [word[-1] + '''</w>''']		)
													lowerCamelCase						:Union[str, Any]						  =     get_pairs(UpperCAmelCase_		)

													if not pairs:
																words.append(UpperCAmelCase_		)
																continue

													while True:
																lowerCamelCase						:List[Any]						  =     min(UpperCAmelCase_	,					key=lambda __snake_case		: self.bpe_ranks.get(UpperCAmelCase_	,					float('''inf'''		)		)		)
																if bigram not in self.bpe_ranks:
																			break
																lowerCamelCase  ,    lowerCamelCase						:int						  =     bigram
																lowerCamelCase						:Any						  =     []
																lowerCamelCase						:List[Any]						  =     0

																while i < len(UpperCAmelCase_		):
																			try:
																						lowerCamelCase						:Optional[Any]						  =     word.index(UpperCAmelCase_	,					UpperCAmelCase_		)
																						new_word.extend(word[i:j]		)
																						lowerCamelCase						:str						  =     j
																			except ValueError:
																						new_word.extend(word[i:]		)
																						break

																			if word[i] == first and i < len(UpperCAmelCase_		) - 1 and word[i + 1] == second:
																						new_word.append(first + second		)
																						i += 2
																			else:
																						new_word.append(word[i]		)
																						i += 1
																lowerCamelCase						:Tuple						  =     tuple(UpperCAmelCase_		)
																lowerCamelCase						:Union[str, Any]						  =     new_word
																if len(UpperCAmelCase_		) == 1:
																			break
																else:
																			lowerCamelCase						:Union[str, Any]						  =     get_pairs(UpperCAmelCase_		)
													lowerCamelCase						:str						  =     '''@@ '''.join(UpperCAmelCase_		)
													lowerCamelCase						:List[str]						  =     word[:-4]

													lowerCamelCase						:List[Any]						  =     word
													words.append(UpperCAmelCase_		)
										return " ".join(UpperCAmelCase_		)







							def 				snake_case  (				self     :    Dict	,					__snake_case     :    Dict		):
										lowerCamelCase						:Dict						  =     []

										lowerCamelCase						:Optional[int]						  =     re.findall(R'''\S+\n?'''	,					UpperCAmelCase_		)

										for token in words:
													split_tokens.extend(list(self.bpe(UpperCAmelCase_		).split(''' '''		)		)		)
										return split_tokens







							def 				snake_case  (				self     :    List[Any]	,					__snake_case     :    Tuple		):
										lowerCamelCase						:List[str]						  =     token.lower()
										return self.encoder.get(UpperCAmelCase_	,					self.encoder.get(self.unk_token		)		)







							def 				snake_case  (				self     :    Optional[Any]	,					__snake_case     :    Dict		):
										return self.decoder.get(UpperCAmelCase_	,					self.unk_token		)







							def 				snake_case  (				self     :    str	,					__snake_case     :    Optional[int]		):
										lowerCamelCase						:List[str]						  =     ''' '''.join(UpperCAmelCase_		).replace('''@@ '''	,					''''''		).strip()
										return out_string







							def 				snake_case  (				self     :    Union[str, Any]	,					__snake_case     :    Union[str, Any]	,					__snake_case     :    Union[str, Any] = None		):
										if not os.path.isdir(UpperCAmelCase_		):
													logger.error(F"Vocabulary path ({save_directory}) should be a directory"		)
													return
										lowerCamelCase						:Any						  =     os.path.join(
										    UpperCAmelCase_	,					(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']		)
										lowerCamelCase						:Union[str, Any]						  =     os.path.join(
										    UpperCAmelCase_	,					(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']		)

										with open(UpperCAmelCase_	,					'''w'''	,					encoding='''utf-8'''		) as f:
													f.write(json.dumps(self.encoder	,					indent=2	,					sort_keys=UpperCAmelCase_	,					ensure_ascii=UpperCAmelCase_		) + '''\n'''		)

										lowerCamelCase						:List[Any]						  =     0
										with open(UpperCAmelCase_	,					'''w'''	,					encoding='''utf-8'''		) as writer:
													writer.write('''#version: 0.2\n'''		)
													for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,					key=lambda __snake_case		: kv[1]		):
																if index != token_index:
																			logger.warning(
																			    F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
																			    ''' Please check that the tokenizer is not corrupted!'''		)
																			lowerCamelCase						:int						  =     token_index
																writer.write(''' '''.join(UpperCAmelCase_		) + '''\n'''		)
																index += 1

										return vocab_file, merge_file




import numpy
class   _lowerCAmelCase		:







							def __init__(				self     :    Dict	,					__snake_case     :    numpy.ndarray	,					__snake_case     :    numpy.ndarray		):
										lowerCamelCase						:Dict						  =     input_array

										# Random initial weights are assigned where first argument is the
										# number of nodes in previous layer and second argument is the
										# number of nodes in the next layer.

										# Random initial weights are assigned.
										# self.input_array.shape[1] is used to represent number of nodes in input layer.
										# First hidden layer consists of 4 nodes.
										lowerCamelCase						:Dict						  =     numpy.random.rand(
										    self.input_array.shape[1]	,					4		)

										# Random initial values for the first hidden layer.
										# First hidden layer has 4 nodes.
										# Second hidden layer has 3 nodes.
										lowerCamelCase						:Dict						  =     numpy.random.rand(
										    4	,					3		)

										# Random initial values for the second hidden layer.
										# Second hidden layer has 3 nodes.
										# Output layer has 1 node.
										lowerCamelCase						:Any						  =     numpy.random.rand(3	,					1		)

										# Real output values provided.
										lowerCamelCase						:Union[str, Any]						  =     output_array

										# Predicted output values by the neural network.
										# Predicted_output array initially consists of zeroes.
										lowerCamelCase						:List[str]						  =     numpy.zeros(output_array.shape		)







							def 				snake_case  (				self     :    Optional[int]		):
										lowerCamelCase						:Any						  =     sigmoid(
										    numpy.dot(self.input_array	,					self.input_layer_and_first_hidden_layer_weights		)		)

										# layer_between_first_hidden_layer_and_second_hidden_layer is the layer
										# connecting the first hidden set of nodes with the second hidden set of nodes.
										lowerCamelCase						:Any						  =     sigmoid(
										    numpy.dot(
										        self.layer_between_input_and_first_hidden_layer	,					self.first_hidden_layer_and_second_hidden_layer_weights	,					)		)

										# layer_between_second_hidden_layer_and_output is the layer connecting
										# second hidden layer with the output node.
										lowerCamelCase						:Dict						  =     sigmoid(
										    numpy.dot(
										        self.layer_between_first_hidden_layer_and_second_hidden_layer	,					self.second_hidden_layer_and_output_layer_weights	,					)		)

										return self.layer_between_second_hidden_layer_and_output







							def 				snake_case  (				self     :    Any		):
										lowerCamelCase						:Union[str, Any]						  =     numpy.dot(
										    self.layer_between_first_hidden_layer_and_second_hidden_layer.T	,					2
										    * (self.output_array - self.predicted_output)
										    * sigmoid_derivative(self.predicted_output		)	,					)
										lowerCamelCase						:Dict						  =     numpy.dot(
										    self.layer_between_input_and_first_hidden_layer.T	,					numpy.dot(
										        2
										        * (self.output_array - self.predicted_output)
										        * sigmoid_derivative(self.predicted_output		)	,					self.second_hidden_layer_and_output_layer_weights.T	,					)
										    * sigmoid_derivative(
										        self.layer_between_first_hidden_layer_and_second_hidden_layer		)	,					)
										lowerCamelCase						:int						  =     numpy.dot(
										    self.input_array.T	,					numpy.dot(
										        numpy.dot(
										            2
										            * (self.output_array - self.predicted_output)
										            * sigmoid_derivative(self.predicted_output		)	,					self.second_hidden_layer_and_output_layer_weights.T	,					)
										        * sigmoid_derivative(
										            self.layer_between_first_hidden_layer_and_second_hidden_layer		)	,					self.first_hidden_layer_and_second_hidden_layer_weights.T	,					)
										    * sigmoid_derivative(self.layer_between_input_and_first_hidden_layer		)	,					)

										self.input_layer_and_first_hidden_layer_weights += (
										    updated_input_layer_and_first_hidden_layer_weights
										)
										self.first_hidden_layer_and_second_hidden_layer_weights += (
										    updated_first_hidden_layer_and_second_hidden_layer_weights
										)
										self.second_hidden_layer_and_output_layer_weights += (
										    updated_second_hidden_layer_and_output_layer_weights
										)







							def 				snake_case  (				self     :    Dict	,					__snake_case     :    numpy.ndarray	,					__snake_case     :    int	,					__snake_case     :    bool		):
										for iteration in range(1	,					iterations + 1		):
													lowerCamelCase						:Union[str, Any]						  =     self.feedforward()
													self.back_propagation()
													if give_loss:
																lowerCamelCase						:Tuple						  =     numpy.mean(numpy.square(output - self.feedforward()		)		)
																print(F"Iteration {iteration} Loss: {loss}"		)







							def 				snake_case  (				self     :    Optional[int]	,					__snake_case     :    numpy.ndarray		):
										lowerCamelCase						:int						  =     input_arr

										lowerCamelCase						:Union[str, Any]						  =     sigmoid(
										    numpy.dot(self.array	,					self.input_layer_and_first_hidden_layer_weights		)		)

										lowerCamelCase						:Optional[Any]						  =     sigmoid(
										    numpy.dot(
										        self.layer_between_input_and_first_hidden_layer	,					self.first_hidden_layer_and_second_hidden_layer_weights	,					)		)

										lowerCamelCase						:Optional[int]						  =     sigmoid(
										    numpy.dot(
										        self.layer_between_first_hidden_layer_and_second_hidden_layer	,					self.second_hidden_layer_and_output_layer_weights	,					)		)

										return int(self.layer_between_second_hidden_layer_and_output > 0.6		)





def  _lowerCamelCase					(   a_				: numpy.ndarray):
			return 1 / (1 + numpy.exp(-value))





def  _lowerCamelCase					(   a_				: numpy.ndarray):
			return (value) * (1 - (value))





def  _lowerCamelCase					(   ):
			lowerCamelCase						:Optional[Any]						  =     numpy.array(
			    (
			        [0, 0, 0],
			        [0, 0, 1],
			        [0, 1, 0],
			        [0, 1, 1],
			        [1, 0, 0],
			        [1, 0, 1],
			        [1, 1, 0],
			        [1, 1, 1],
			    )						,			dtype=numpy.floataa						,			)

			# True output values for the given input values.
			lowerCamelCase						:int						  =     numpy.array(([0], [1], [1], [0], [1], [0], [0], [1])						,			dtype=numpy.floataa)

			# Calling neural network class.
			lowerCamelCase						:List[Any]						  =     TwoHiddenLayerNeuralNetwork(
			    input_array=a_						,			output_array=a_)

			# Calling training function.
			# Set give_loss to True if you want to see loss in every iteration.
			neural_network.train(output=a_						,			iterations=10						,			give_loss=a_)

			return neural_network.predict(numpy.array(([1, 1, 1])						,			dtype=numpy.floataa))


if __name__ == "__main__":
			example()



