



'''simple docstring'''




import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 		_UpperCamelCase						(							lowercase__					,      unittest.TestCase					):


			'''simple docstring'''

			_A   :	int    					=	None
			_A   :	List[Any]    					=	BloomTokenizerFast
			_A   :	Optional[Any]    					=	BloomTokenizerFast
			_A   :	Tuple    					=	True
			_A   :	str    					=	False
			_A   :	Optional[int]    					=	'''tokenizer_file'''
			_A   :	Dict    					=	{'''bos_token''': '''<s>''', '''eos_token''': '''</s>''', '''unk_token''': '''<unk>''', '''pad_token''': '''<pad>'''}

			def UpperCamelCase__      (							self  :				List[str]		):





					"""simple docstring"""






					super().setUp()
					__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	BloomTokenizerFast.from_pretrained("""bigscience/tokenizer"""		)
					tokenizer.save_pretrained(self.tmpdirname		)

			def UpperCamelCase__      (							self  :				Union[str, Any]							,  **lowerCAmelCase__  :				Any		):





					"""simple docstring"""






					kwargs.update(self.special_tokens_map		)
					return BloomTokenizerFast.from_pretrained(self.tmpdirname							,  **UpperCAmelCase__		)

			def UpperCamelCase__      (							self  :				Any		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	str					 =	self.get_rust_tokenizer()

					__SCREAMING_SNAKE_CASE :	List[str]					 =	['''The quick brown fox</s>''', '''jumps over the lazy dog</s>''']
					__SCREAMING_SNAKE_CASE :	Any					 =	[[2_1_7_5, 2_3_7_1_4, 7_3_1_7_3, 1_4_4_2_5_2, 2], [7_7, 1_3_2_6_1_9, 3_4_7_8, 3_6_8, 1_0_9_5_8_6, 3_5_4_3_3, 2]]

					__SCREAMING_SNAKE_CASE :	Any					 =	tokenizer.batch_encode_plus(UpperCAmelCase__		)['''input_ids''']
					self.assertListEqual(UpperCAmelCase__							,  UpperCAmelCase__		)

					__SCREAMING_SNAKE_CASE :	int					 =	tokenizer.batch_decode(UpperCAmelCase__		)
					self.assertListEqual(UpperCAmelCase__							,  UpperCAmelCase__		)

			def UpperCamelCase__      (							self  :				Tuple							,  lowerCAmelCase__  :				Any=6		):





					"""simple docstring"""






					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"		):
									__SCREAMING_SNAKE_CASE :	Optional[int]					 =	self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__							,  **UpperCAmelCase__		)
									# tokenizer_r.pad_token = None # Hotfixing padding = None
									# Simple input
									__SCREAMING_SNAKE_CASE :	Tuple					 =	'''This is a simple input'''
									__SCREAMING_SNAKE_CASE :	int					 =	['''This is a simple input 1''', '''This is a simple input 2''']
									__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	('''This is a simple input''', '''This is a pair''')
									__SCREAMING_SNAKE_CASE :	int					 =	[
									    ('''This is a simple input 1''', '''This is a simple input 2'''),
									    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
									]

									# Simple input tests
									try:
											tokenizer_r.encode(UpperCAmelCase__							,  max_length=UpperCAmelCase__		)
											tokenizer_r.encode_plus(UpperCAmelCase__							,  max_length=UpperCAmelCase__		)

											tokenizer_r.batch_encode_plus(UpperCAmelCase__							,  max_length=UpperCAmelCase__		)
											tokenizer_r.encode(UpperCAmelCase__							,  max_length=UpperCAmelCase__		)
											tokenizer_r.batch_encode_plus(UpperCAmelCase__							,  max_length=UpperCAmelCase__		)
									except ValueError:
											self.fail("""Bloom Tokenizer should be able to deal with padding"""		)

									__SCREAMING_SNAKE_CASE :	Optional[int]					 =	None  # Hotfixing padding = None
									self.assertRaises(UpperCAmelCase__							,  tokenizer_r.encode							,  UpperCAmelCase__							,  max_length=UpperCAmelCase__							,  padding="""max_length"""		)

									# Simple input
									self.assertRaises(UpperCAmelCase__							,  tokenizer_r.encode_plus							,  UpperCAmelCase__							,  max_length=UpperCAmelCase__							,  padding="""max_length"""		)

									# Simple input
									self.assertRaises(
									    UpperCAmelCase__							,  tokenizer_r.batch_encode_plus							,  UpperCAmelCase__							,  max_length=UpperCAmelCase__							,  padding="""max_length"""							,  )

									# Pair input
									self.assertRaises(UpperCAmelCase__							,  tokenizer_r.encode							,  UpperCAmelCase__							,  max_length=UpperCAmelCase__							,  padding="""max_length"""		)

									# Pair input
									self.assertRaises(UpperCAmelCase__							,  tokenizer_r.encode_plus							,  UpperCAmelCase__							,  max_length=UpperCAmelCase__							,  padding="""max_length"""		)

									# Pair input
									self.assertRaises(
									    UpperCAmelCase__							,  tokenizer_r.batch_encode_plus							,  UpperCAmelCase__							,  max_length=UpperCAmelCase__							,  padding="""max_length"""							,  )

			def UpperCamelCase__      (							self  :				Union[str, Any]		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	self.get_rust_tokenizer()
					__SCREAMING_SNAKE_CASE :	Dict					 =	load_dataset("""xnli"""							,  """all_languages"""							,  split="""test"""							,  streaming=UpperCAmelCase__		)

					__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	next(iter(UpperCAmelCase__		)		)['''premise''']  # pick up one data
					__SCREAMING_SNAKE_CASE :	int					 =	list(sample_data.values()		)

					__SCREAMING_SNAKE_CASE :	Any					 =	list(map(tokenizer.encode							,  UpperCAmelCase__		)		)
					__SCREAMING_SNAKE_CASE :	List[str]					 =	[tokenizer.decode(UpperCAmelCase__							,  clean_up_tokenization_spaces=UpperCAmelCase__		) for x in output_tokens]
					self.assertListEqual(UpperCAmelCase__							,  UpperCAmelCase__		)



			def UpperCamelCase__      (							self  :				List[Any]		):





					"""simple docstring"""






					self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map		)							,  1		)
					self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()		)[0]		)							,  1		)




'''simple docstring'''




import qiskit


def        lowerCAmelCase_     (			_lowerCamelCase:     int = 2      ):
		__SCREAMING_SNAKE_CASE :	Dict					 =	qubits

		# Using Aer's simulator
		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	qiskit.Aer.get_backend("""aer_simulator"""      )

		# Creating a Quantum Circuit acting on the q register
		__SCREAMING_SNAKE_CASE :	str					 =	qiskit.QuantumCircuit(_lowerCamelCase ,   _lowerCamelCase      )

		# Adding a H gate on qubit 0 (now q0 in superposition)
		circuit.h(0      )

		for i in range(1 ,   _lowerCamelCase      ):
				# Adding CX (CNOT) gate
				circuit.cx(i - 1 ,   _lowerCamelCase      )

		# Mapping the quantum measurement to the classical bits
		circuit.measure(list(range(_lowerCamelCase      )      ) ,   list(range(_lowerCamelCase      )      )      )

		# Now measuring any one qubit would affect other qubits to collapse
		# their super position and have same state as the measured one.

		# Executing the circuit on the simulator
		__SCREAMING_SNAKE_CASE :	str					 =	qiskit.execute(_lowerCamelCase ,   _lowerCamelCase ,   shots=10_00      )

		return job.result().get_counts(_lowerCamelCase      )


if __name__ == "__main__":
						print(f"Total count for various states are: {quantum_entanglement(3)}")