





"""simple docstring"""



import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
       import torch

if is_soundfile_availble():
       import soundfile as sf

if is_vision_available():
       from PIL import Image







def 		__lowercase					(       snake_case_  :  Union[str, Any]=""						)       ->str:



    '''simple docstring'''







    __A   :						Tuple									=					tempfile.mkdtemp()
    return os.path.join(snake_case_    ,str(uuid.uuida()						) + suffix						)






@require_soundfile
@require_torch
class 		__snake_case (		unittest.TestCase					):





 """simple docstring"""


 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Optional[Any]									=					torch.rand(12 ,						dtype=torch.floataa  ) - 0.5
     __A   :						str									=					AgentAudio(__lowerCamelCase  )
     __A   :						Optional[Any]									=					str(agent_type.to_string()  )

     # Ensure that the tensor and the agent_type's tensor are the same
     self.assertTrue(torch.allclose(__lowerCamelCase ,						agent_type.to_raw() ,						atol=1e-4  )  )

     del agent_type

     # Ensure the path remains even after the object deletion
     self.assertTrue(os.path.exists(__lowerCamelCase  )  )

     # Ensure that the file contains the same value as the original tensor
     __A			,	__A   :						Tuple									=					sf.read(__lowerCamelCase  )
     self.assertTrue(torch.allclose(__lowerCamelCase ,						torch.tensor(__lowerCamelCase  ) ,						atol=1e-4  )  )







 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Any									=					torch.rand(12 ,						dtype=torch.floataa  ) - 0.5
     __A   :						Optional[int]									=					get_new_path(suffix='''.wav'''  )
     sf.write(__lowerCamelCase ,						__lowerCamelCase ,						1_6000  )

     __A   :						Union[str, Any]									=					AgentAudio(__lowerCamelCase  )

     self.assertTrue(torch.allclose(__lowerCamelCase ,						agent_type.to_raw() ,						atol=1e-4  )  )
     self.assertEqual(agent_type.to_string() ,						__lowerCamelCase  )






@require_vision
@require_torch
class 		__snake_case (		unittest.TestCase					):





 """simple docstring"""


 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Any									=					torch.randint(0 ,						256 ,						(64, 64, 3)  )
     __A   :						List[str]									=					AgentImage(__lowerCamelCase  )
     __A   :						Tuple									=					str(agent_type.to_string()  )

     # Ensure that the tensor and the agent_type's tensor are the same
     self.assertTrue(torch.allclose(__lowerCamelCase ,						agent_type._tensor ,						atol=1e-4  )  )

     self.assertIsInstance(agent_type.to_raw() ,						Image.Image  )

     # Ensure the path remains even after the object deletion
     del agent_type
     self.assertTrue(os.path.exists(__lowerCamelCase  )  )

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[Any]									=					Path(get_tests_dir('''fixtures/tests_samples/COCO'''  )  ) / '''000000039769.png'''
     __A   :						str									=					Image.open(__lowerCamelCase  )
     __A   :						List[Any]									=					AgentImage(__lowerCamelCase  )

     self.assertTrue(path.samefile(agent_type.to_string()  )  )
     self.assertTrue(image == agent_type.to_raw()  )

     # Ensure the path remains even after the object deletion
     del agent_type
     self.assertTrue(os.path.exists(__lowerCamelCase  )  )







 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[str]									=					Path(get_tests_dir('''fixtures/tests_samples/COCO'''  )  ) / '''000000039769.png'''
     __A   :						Optional[int]									=					Image.open(__lowerCamelCase  )
     __A   :						Any									=					AgentImage(__lowerCamelCase  )

     self.assertFalse(path.samefile(agent_type.to_string()  )  )
     self.assertTrue(image == agent_type.to_raw()  )

     # Ensure the path remains even after the object deletion
     del agent_type
     self.assertTrue(os.path.exists(__lowerCamelCase  )  )






class 		__snake_case (		unittest.TestCase					):





 """simple docstring"""


 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						List[Any]									=					'''Hey!'''
     __A   :						Tuple									=					AgentText(__lowerCamelCase  )

     self.assertEqual(__lowerCamelCase ,						agent_type.to_string()  )
     self.assertEqual(__lowerCamelCase ,						agent_type.to_raw()  )
     self.assertEqual(__lowerCamelCase ,						__lowerCamelCase  )











"""simple docstring"""



import numpy as np
import qiskit







def 		__lowercase					(       snake_case_  :  int = 8    ,snake_case_  :  int | None = None						)       ->str:



    '''simple docstring'''







    __A   :						str									=					np.random.default_rng(seed=snake_case_						)

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

    # Quantum Circuit to simulate BB84
    __A   :						Dict									=					qiskit.QuantumCircuit(snake_case_    ,name='''BB84'''						)

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

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

    bbaa_circ.barrier()
    bbaa_circ.measure_all()

    # Simulate the quantum circuit.
    __A   :						List[str]									=					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.
    __A   :						List[str]									=					qiskit.execute(snake_case_    ,snake_case_    ,shots=1    ,seed_simulator=snake_case_						)
    # Returns the result of measurement.
    __A   :						Union[str, Any]									=					job.result().get_counts(snake_case_						).most_frequent()

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

    # Get final key. Pad with 0 if too short, otherwise truncate.
    __A   :						Union[str, Any]									=					gen_key[:key_len] if len(snake_case_						) >= key_len else gen_key.ljust(snake_case_    ,'''0'''						)
    return key


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

       testmod()




