'''simple docstring'''





import numpy as np
import qiskit





def   lowerCAmelCase_ (				__lowerCAmelCase		,					__lowerCAmelCase						)->  qiskit.QuantumCircuit:






      '''simple docstring'''





      UpperCAmelCase    : Any      =qiskit.QuantumCircuit(num_qubits + 1						)

      # First, let's deal with the case in which oracle is balanced
      if case == "balanced":
            # First generate a random number that tells us which CNOTs to
            # wrap in X-gates:
            UpperCAmelCase    : Optional[int]      =np.random.randint(1		,					2**num_qubits						)
            # Next, format 'b' as a binary string of length 'n', padded with zeros:
            UpperCAmelCase    : Tuple      =format(__lowerCAmelCase		,					f'''0{num_qubits}b'''						)
            # Next, we place the first X-gates. Each digit in our binary string
            # corresponds to a qubit, if the digit is 0, we do nothing, if it's 1
            # we apply an X-gate to that qubit:
            for index, bit in enumerate(__lowerCAmelCase						):
                  if bit == "1":
                        oracle_qc.x(__lowerCAmelCase						)
        # Do the controlled-NOT gates for each qubit, using the output qubit
        # as the target:
            for index in range(__lowerCAmelCase						):
                  oracle_qc.cx(__lowerCAmelCase		,					__lowerCAmelCase						)
            # Next, place the final X-gates
            for index, bit in enumerate(__lowerCAmelCase						):
                  if bit == "1":
                        oracle_qc.x(__lowerCAmelCase						)

    # Case in which oracle is constant
      if case == "constant":
            # First decide what the fixed output of the oracle will be
            # (either always 0 or always 1)
            UpperCAmelCase    : int      =np.random.randint(2						)
            if output == 1:
                  oracle_qc.x(__lowerCAmelCase						)

      UpperCAmelCase    : int      =oracle_qc.to_gate()
      UpperCAmelCase    : Optional[Any]      ='''Oracle'''  # To show when we display the circuit
      return oracle_gate





def   lowerCAmelCase_ (				__lowerCAmelCase		,					__lowerCAmelCase						)->  qiskit.QuantumCircuit:






      '''simple docstring'''





      UpperCAmelCase    : Union[str, Any]      =qiskit.QuantumCircuit(num_qubits + 1		,					__lowerCAmelCase						)
      # Set up the output qubit:
      dj_circuit.x(__lowerCAmelCase						)
      dj_circuit.h(__lowerCAmelCase						)
      # And set up the input register:
      for qubit in range(__lowerCAmelCase						):
            dj_circuit.h(__lowerCAmelCase						)
      # Let's append the oracle gate to our circuit:
      dj_circuit.append(__lowerCAmelCase		,					range(num_qubits + 1						)						)
      # Finally, perform the H-gates again and measure:
      for qubit in range(__lowerCAmelCase						):
            dj_circuit.h(__lowerCAmelCase						)

      for i in range(__lowerCAmelCase						):
            dj_circuit.measure(__lowerCAmelCase		,					__lowerCAmelCase						)

      return dj_circuit





def   lowerCAmelCase_ (				__lowerCAmelCase		,					__lowerCAmelCase						)->  qiskit.result.counts.Counts:






      '''simple docstring'''





      UpperCAmelCase    : List[Any]      =qiskit.Aer.get_backend('''aer_simulator'''						)

      UpperCAmelCase    : int      =dj_oracle(__lowerCAmelCase		,					__lowerCAmelCase						)
      UpperCAmelCase    : int      =dj_algorithm(__lowerCAmelCase		,					__lowerCAmelCase						)

      # Execute the circuit on the simulator
      UpperCAmelCase    : Dict      =qiskit.execute(__lowerCAmelCase		,					__lowerCAmelCase		,					shots=10_00						)

      # Return the histogram data of the results of the experiment.
      return job.result().get_counts(__lowerCAmelCase						)


if __name__ == "__main__":
     print(f'Deutsch Jozsa - Constant Oracle: {deutsch_jozsa("constant", 3)}')
     print(f'Deutsch Jozsa - Balanced Oracle: {deutsch_jozsa("balanced", 3)}')

import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard







class 			__snake_case   (     unittest.TestCase   ):
 def 	UpperCAmelCase__       (  self						)	->							Optional[Any]:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      ={
           '''model_details''': {
               '''Organization''': '''testing''',
               '''Model date''': '''today''',
               '''Model version''': '''v2.1, Developed by Test Corp in 2019.''',
               '''Architecture''': '''Convolutional Neural Network.''',
           },
           '''metrics''': '''BLEU and ROUGE-1''',
           '''evaluation_data''': {
               '''Datasets''': {'''BLEU''': '''My-great-dataset-v1''', '''ROUGE-1''': '''My-short-dataset-v2.1'''},
               '''Preprocessing''': '''See details on https://arxiv.org/pdf/1810.03993.pdf''',
           },
           '''training_data''': {
               '''Dataset''': '''English Wikipedia dump dated 2018-12-01''',
               '''Preprocessing''': (
                   '''Using SentencePiece vocabulary of size 52k tokens. See details on'''
                   ''' https://arxiv.org/pdf/1810.03993.pdf'''
               ),
           },
           '''quantitative_analyses''': {'''BLEU''': 55.1, '''ROUGE-1''': 76},
       }
 def 	UpperCAmelCase__       (  self						)	->							Dict:
       '''simple docstring'''





       UpperCAmelCase    : Optional[Any]      =ModelCard.from_dict(self.inputs_dict						)
       self.assertTrue(hasattr(snake_case__		,   '''model_details'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''intended_use'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''factors'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''metrics'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''evaluation_data'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''training_data'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''quantitative_analyses'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''ethical_considerations'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''caveats_and_recommendations'''						)						)
 def 	UpperCAmelCase__       (  self						)	->							Tuple:
       '''simple docstring'''





       UpperCAmelCase    : Optional[Any]      =ModelCard.from_dict(self.inputs_dict						)
       UpperCAmelCase    : int      =json.loads(modelcard.to_json_string()						)
       for key, value in self.inputs_dict.items():
             self.assertEqual(obj[key]		,   snake_case__						)
 def 	UpperCAmelCase__       (  self						)	->							Tuple:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      =ModelCard.from_dict(self.inputs_dict						)

       with tempfile.TemporaryDirectory() as tmpdirname:
             UpperCAmelCase    : Optional[Any]      =os.path.join(snake_case__		,   '''modelcard.json'''						)
             model_card_first.to_json_file(snake_case__						)
             UpperCAmelCase    : Tuple      =ModelCard.from_json_file(snake_case__						)

       self.assertEqual(model_card_second.to_dict()		,   model_card_first.to_dict()						)






 def 	UpperCAmelCase__       (  self						)	->							str:
       '''simple docstring'''





       UpperCAmelCase    : Optional[int]      =ModelCard.from_dict(self.inputs_dict						)

       with tempfile.TemporaryDirectory() as tmpdirname:
             model_card_first.save_pretrained(snake_case__						)
             UpperCAmelCase    : Dict      =ModelCard.from_pretrained(snake_case__						)

       self.assertEqual(model_card_second.to_dict()		,   model_card_first.to_dict()						)
