


import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
		lowerCamelCase						=		'pt'
elif is_tf_available():
		lowerCamelCase						=		'tf'
else:
		lowerCamelCase						=		'jax'





class 					_a							(				SCREAMING_SNAKE_CASE_     ,						unittest.TestCase):
	_a  :  List[Any]          =							PerceiverTokenizer
	_a  :  Optional[int]          =							False




	def 							UpperCAmelCase__(					self						:		Union[str, Any]		)->       Union[str, Any]:
			super().setUp()
			lowerCAmelCase__   :			Union[str, Any]         =					PerceiverTokenizer()
			tokenizer.save_pretrained(self.tmpdirname		)




	@cached_property
	def 							UpperCAmelCase__(					self						:		Tuple		)->       Dict:
			return PerceiverTokenizer.from_pretrained('''deepmind/language-perceiver'''		)




	def 							UpperCAmelCase__(					self						:		Union[str, Any]		,					**_SCREAMING_SNAKE_CASE						:		List[str]		)->       Optional[int]:
			return self.tokenizer_class.from_pretrained(self.tmpdirname		,					**a__		)




	def 							UpperCAmelCase__(					self						:		Any		,					_SCREAMING_SNAKE_CASE						:		List[Any]		,					_SCREAMING_SNAKE_CASE						:		str=False		,					_SCREAMING_SNAKE_CASE						:		List[str]=20		,					_SCREAMING_SNAKE_CASE						:		Optional[int]=5		)->       List[str]:
			# XXX The default common tokenizer tests assume that every ID is decodable on its own.
			# This assumption is invalid for Perceiver because single bytes might not be
			# valid utf-8 (byte 128 for instance).
			# Here we're overriding the smallest possible method to provide
			# a clean sequence without making the same assumption.

			lowerCAmelCase__   :			List[str]         =					[]
			for i in range(len(a__		)		):
					try:
							lowerCAmelCase__   :			int         =					tokenizer.decode([i]		,					clean_up_tokenization_spaces=a__		)
					except UnicodeDecodeError:
							pass
					toks.append((i, tok)		)

			lowerCAmelCase__   :			int         =					list(filter(lambda _SCREAMING_SNAKE_CASE		: re.match(r'''^[ a-zA-Z]+$'''		,					t[1]		)		,					a__		)		)
			lowerCAmelCase__   :			Union[str, Any]         =					list(filter(lambda _SCREAMING_SNAKE_CASE		: [t[0]] == tokenizer.encode(t[1]		,					add_special_tokens=a__		)		,					a__		)		)
			if max_length is not None and len(a__		) > max_length:
					lowerCAmelCase__   :			Optional[int]         =					toks[:max_length]
			if min_length is not None and len(a__		) < min_length and len(a__		) > 0:
					while len(a__		) < min_length:
							lowerCAmelCase__   :			Dict         =					toks + toks
        # toks_str = [t[1] for t in toks]
			lowerCAmelCase__   :			Union[str, Any]         =					[t[0] for t in toks]

			# Ensure consistency
			lowerCAmelCase__   :			Tuple         =					tokenizer.decode(a__		,					clean_up_tokenization_spaces=a__		)
			if " " not in output_txt and len(a__		) > 1:
					lowerCAmelCase__   :			Dict         =					(
					    tokenizer.decode([toks_ids[0]]		,					clean_up_tokenization_spaces=a__		)
					    + """ """
					    + tokenizer.decode(toks_ids[1:]		,					clean_up_tokenization_spaces=a__		)
					)
			if with_prefix_space:
					lowerCAmelCase__   :			Tuple         =					""" """ + output_txt
			lowerCAmelCase__   :			Optional[Any]         =					tokenizer.encode(a__		,					add_special_tokens=a__		)
			return output_txt, output_ids




	def 							UpperCAmelCase__(					self						:		List[str]		)->       List[str]:
			lowerCAmelCase__   :			int         =					self.perceiver_tokenizer
			lowerCAmelCase__   :			Optional[int]         =					"""Unicode €."""
			lowerCAmelCase__   :			Union[str, Any]         =					tokenizer(a__		)
			lowerCAmelCase__   :			List[Any]         =					[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
			self.assertEqual(encoded['''input_ids''']		,					a__		)

			# decoding
			lowerCAmelCase__   :			Union[str, Any]         =					tokenizer.decode(a__		)
			self.assertEqual(a__		,					'''[CLS]Unicode €.[SEP]'''		)

			lowerCAmelCase__   :			Dict         =					tokenizer('''e è é ê ë'''		)
			lowerCAmelCase__   :			int         =					[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
			self.assertEqual(encoded['''input_ids''']		,					a__		)
			# decoding
			lowerCAmelCase__   :			List[str]         =					tokenizer.decode(a__		)
			self.assertEqual(a__		,					'''[CLS]e è é ê ë[SEP]'''		)

			# encode/decode, but with `encode` instead of `__call__`
			self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë'''		)		)		,					'''[CLS]e è é ê ë[SEP]'''		)




	def 							UpperCAmelCase__(					self						:		Optional[Any]		)->       str:
			lowerCAmelCase__   :			str         =					self.perceiver_tokenizer
			lowerCAmelCase__   :			Any         =					["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
			# fmt: off
			lowerCAmelCase__   :			Any         =					[4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
			# fmt: on
			lowerCAmelCase__   :			List[str]         =					tokenizer(a__		,					padding=a__		,					return_tensors=a__		)
			self.assertIsInstance(a__		,					a__		)

			if FRAMEWORK != "jax":
					lowerCAmelCase__   :			str         =					list(batch.input_ids.numpy()[0]		)
			else:
					lowerCAmelCase__   :			List[Any]         =					list(batch.input_ids.tolist()[0]		)

			self.assertListEqual(a__		,					a__		)

			self.assertEqual((2, 38)		,					batch.input_ids.shape		)
			self.assertEqual((2, 38)		,					batch.attention_mask.shape		)




	def 							UpperCAmelCase__(					self						:		List[str]		)->       Dict:
			lowerCAmelCase__   :			Optional[Any]         =					self.perceiver_tokenizer
			lowerCAmelCase__   :			str         =					["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
			lowerCAmelCase__   :			Optional[Any]         =					tokenizer(a__		,					padding=a__		,					return_tensors=a__		)
			# check if input_ids are returned and no decoder_input_ids
			self.assertIn('''input_ids'''		,					a__		)
			self.assertIn('''attention_mask'''		,					a__		)
			self.assertNotIn('''decoder_input_ids'''		,					a__		)
			self.assertNotIn('''decoder_attention_mask'''		,					a__		)




	def 							UpperCAmelCase__(					self						:		Optional[Any]		)->       Dict:
			lowerCAmelCase__   :			Dict         =					self.perceiver_tokenizer
			lowerCAmelCase__   :			int         =					[
			    """Summary of the text.""",
			    """Another summary.""",
			]
			lowerCAmelCase__   :			Optional[int]         =					tokenizer(
			    text_target=a__		,					max_length=32		,					padding='''max_length'''		,					truncation=a__		,					return_tensors=a__		)
			self.assertEqual(32		,					targets['''input_ids'''].shape[1]		)




	def 							UpperCAmelCase__(					self						:		List[Any]		)->       Tuple:
			# safety check on max_len default value so we are sure the test works
			lowerCAmelCase__   :			List[Any]         =					self.get_tokenizers()
			for tokenizer in tokenizers:
					with self.subTest(F'{tokenizer.__class__.__name__}'		):
							self.assertNotEqual(tokenizer.model_max_length		,					42		)

        # Now let's start the test
			lowerCAmelCase__   :			Union[str, Any]         =					self.get_tokenizers()
			for tokenizer in tokenizers:
					with self.subTest(F'{tokenizer.__class__.__name__}'		):
							# Isolate this from the other tests because we save additional tokens/etc
							lowerCAmelCase__   :			Optional[int]         =					tempfile.mkdtemp()

							lowerCAmelCase__   :			Dict         =					""" He is very happy, UNwant\u00E9d,running"""
							lowerCAmelCase__   :			Optional[int]         =					tokenizer.encode(a__		,					add_special_tokens=a__		)
							tokenizer.save_pretrained(a__		)

							lowerCAmelCase__   :			Dict         =					tokenizer.__class__.from_pretrained(a__		)
							lowerCAmelCase__   :			Optional[int]         =					after_tokenizer.encode(a__		,					add_special_tokens=a__		)
							self.assertListEqual(a__		,					a__		)

							shutil.rmtree(a__		)

			lowerCAmelCase__   :			Tuple         =					self.get_tokenizers(model_max_length=42		)
			for tokenizer in tokenizers:
					with self.subTest(F'{tokenizer.__class__.__name__}'		):
							# Isolate this from the other tests because we save additional tokens/etc
							lowerCAmelCase__   :			Optional[Any]         =					tempfile.mkdtemp()

							lowerCAmelCase__   :			List[str]         =					""" He is very happy, UNwant\u00E9d,running"""
							tokenizer.add_tokens(['''bim''', '''bambam''']		)
							lowerCAmelCase__   :			Optional[Any]         =					tokenizer.additional_special_tokens
							additional_special_tokens.append('''new_additional_special_token'''		)
							tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}		)
							lowerCAmelCase__   :			Optional[Any]         =					tokenizer.encode(a__		,					add_special_tokens=a__		)
							tokenizer.save_pretrained(a__		)

							lowerCAmelCase__   :			Tuple         =					tokenizer.__class__.from_pretrained(a__		)
							lowerCAmelCase__   :			Optional[int]         =					after_tokenizer.encode(a__		,					add_special_tokens=a__		)
							self.assertListEqual(a__		,					a__		)
							self.assertIn('''new_additional_special_token'''		,					after_tokenizer.additional_special_tokens		)
							self.assertEqual(after_tokenizer.model_max_length		,					42		)

							lowerCAmelCase__   :			Dict         =					tokenizer.__class__.from_pretrained(a__		,					model_max_length=43		)
							self.assertEqual(tokenizer.model_max_length		,					43		)

							shutil.rmtree(a__		)




	def 							UpperCAmelCase__(					self						:		Optional[Any]		)->       List[str]:
			lowerCAmelCase__   :			Dict         =					[]
			if self.test_slow_tokenizer:
					tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())		)

			if self.test_rust_tokenizer:
					tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())		)

			for tokenizer_class, tokenizer_utils in tokenizer_list:
					with tempfile.TemporaryDirectory() as tmp_dir:
							tokenizer_utils.save_pretrained(a__		)

							with open(os.path.join(a__		,					'''special_tokens_map.json'''		)		,					encoding='''utf-8'''		) as json_file:
									lowerCAmelCase__   :			Any         =					json.load(a__		)

							with open(os.path.join(a__		,					'''tokenizer_config.json'''		)		,					encoding='''utf-8'''		) as json_file:
									lowerCAmelCase__   :			Union[str, Any]         =					json.load(a__		)

							lowerCAmelCase__   :			int         =					[F'<extra_id_{i}>' for i in range(125		)]

							lowerCAmelCase__   :			int         =					added_tokens_extra_ids + [
							    """an_additional_special_token"""
							]
							lowerCAmelCase__   :			Any         =					added_tokens_extra_ids + [
							    """an_additional_special_token"""
							]

							with open(os.path.join(a__		,					'''special_tokens_map.json'''		)		,					'''w'''		,					encoding='''utf-8'''		) as outfile:
									json.dump(a__		,					a__		)
							with open(os.path.join(a__		,					'''tokenizer_config.json'''		)		,					'''w'''		,					encoding='''utf-8'''		) as outfile:
									json.dump(a__		,					a__		)

							# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
							# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
							# "special_tokens_map.json" files
							lowerCAmelCase__   :			List[str]         =					tokenizer_class.from_pretrained(
							    a__		,					)
							self.assertIn(
							    '''an_additional_special_token'''		,					tokenizer_without_change_in_init.additional_special_tokens		)
							self.assertEqual(
							    ['''an_additional_special_token''']		,					tokenizer_without_change_in_init.convert_ids_to_tokens(
							        tokenizer_without_change_in_init.convert_tokens_to_ids(['''an_additional_special_token''']		)		)		,					)

							# Now we test that we can change the value of additional_special_tokens in the from_pretrained
							lowerCAmelCase__   :			List[Any]         =					added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''		,					lstrip=a__		)]
							lowerCAmelCase__   :			List[Any]         =					tokenizer_class.from_pretrained(
							    a__		,					additional_special_tokens=a__		,					)

							self.assertIn('''a_new_additional_special_token'''		,					tokenizer.additional_special_tokens		)
							self.assertEqual(
							    ['''a_new_additional_special_token''']		,					tokenizer.convert_ids_to_tokens(
							        tokenizer.convert_tokens_to_ids(['''a_new_additional_special_token''']		)		)		,					)




	def 							UpperCAmelCase__(					self						:		str		)->       List[str]:
			lowerCAmelCase__   :			List[str]         =					self.perceiver_tokenizer
			self.assertEqual(tokenizer.decode([178]		)		,					'''�'''		)




	def 							UpperCAmelCase__(					self						:		int		)->       Union[str, Any]:
			pass




	def 							UpperCAmelCase__(					self						:		List[Any]		)->       List[str]:
			pass




	def 							UpperCAmelCase__(					self						:		List[str]		)->       str:
			pass




	def 							UpperCAmelCase__(					self						:		Dict		)->       List[str]:
			pass




	def 							UpperCAmelCase__(					self						:		Any		)->       str:
			# The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
			# strings and special added tokens as tokens
			lowerCAmelCase__   :			int         =					self.get_tokenizers(fast=a__		,					do_lower_case=a__		)
			for tokenizer in tokenizers:
					with self.subTest(F'{tokenizer.__class__.__name__}'		):
							lowerCAmelCase__   :			List[str]         =					["""[CLS]""", """t""", """h""", """i""", """s""", """ """, """i""", """s""", """ """, """a""", """ """, """t""", """e""", """s""", """t""", """[SEP]"""]
							lowerCAmelCase__   :			Union[str, Any]         =					tokenizer.convert_tokens_to_string(a__		)

							self.assertIsInstance(a__		,					a__		)





"""simple docstring"""




import numpy as np
import qiskit





def 							SCREAMING_SNAKE_CASE     (			_lowerCamelCase						:       int = 8			,_lowerCamelCase						:       int | None = None	)       ->      str:
  _lowerCAmelCase						:       int  			=     np.random.default_rng(seed=_lowerCamelCase	)

  # Roughly 25% of the qubits will contribute to the key.
  # So we take more than we need.
  _lowerCAmelCase						:       Tuple  			=     6 * key_len
  # Measurement basis for Alice's qubits.
  _lowerCAmelCase						:       Dict  			=     rng.integers(2			,size=_lowerCamelCase	)
  # The set of states Alice will prepare.
  _lowerCAmelCase						:       Tuple  			=     rng.integers(2			,size=_lowerCamelCase	)
  # Measurement basis for Bob's qubits.
  _lowerCAmelCase						:       Union[str, Any]  			=     rng.integers(2			,size=_lowerCamelCase	)

  # Quantum Circuit to simulate BB84
  _lowerCAmelCase						:       Dict  			=     qiskit.QuantumCircuit(_lowerCamelCase			,name="""BB84"""	)

  # Alice prepares her qubits according to rules above.
  for index, _ in enumerate(_lowerCamelCase	):
    if alice_state[index] == 1:
      bbaa_circ.x(_lowerCamelCase	)
    if alice_basis[index] == 1:
      bbaa_circ.h(_lowerCamelCase	)
  bbaa_circ.barrier()

  # Bob measures the received qubits according to rules above.
  for index, _ in enumerate(_lowerCamelCase	):
    if bob_basis[index] == 1:
      bbaa_circ.h(_lowerCamelCase	)

  bbaa_circ.barrier()
  bbaa_circ.measure_all()

  # Simulate the quantum circuit.
  _lowerCAmelCase						:       int  			=     qiskit.Aer.get_backend("""aer_simulator"""	)
  # We only need to run one shot because the key is unique.
  # Multiple shots will produce the same key.
  _lowerCAmelCase						:       List[str]  			=     qiskit.execute(_lowerCamelCase			,_lowerCamelCase			,shots=1			,seed_simulator=_lowerCamelCase	)
  # Returns the result of measurement.
  _lowerCAmelCase						:       List[Any]  			=     job.result().get_counts(_lowerCamelCase	).most_frequent()

  # Extracting the generated key from the simulation results.
  # Only keep measurement results where Alice and Bob chose the same basis.
  _lowerCAmelCase						:       str  			=     """""".join(
      [
          result_bit
          for alice_basis_bit, bob_basis_bit, result_bit in zip(
              _lowerCamelCase			,_lowerCamelCase			,_lowerCamelCase	)
          if alice_basis_bit == bob_basis_bit
      ]	)

  # Get final key. Pad with 0 if too short, otherwise truncate.
  _lowerCAmelCase						:       List[Any]  			=     gen_key[:key_len] if len(_lowerCamelCase	) >= key_len else gen_key.ljust(_lowerCamelCase			,"""0"""	)
  return key


if __name__ == "__main__":
     print(F"""The generated key is : {bbaa(8, seed=0)}""")
     from doctest import testmod

     testmod()




