
'''simple docstring'''




import math

import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute







def 						lowerCAmelCase_							(  snake_case__ = 3		):




    '''simple docstring'''



    if isinstance(snake_case__						,							snake_case__		):
        raise TypeError('''number of qubits must be a integer.'''		)
    if number_of_qubits <= 0:
        raise ValueError('''number of qubits must be > 0.'''		)
    if math.floor(snake_case__		) != number_of_qubits:
        raise ValueError('''number of qubits must be exact integer.'''		)
    if number_of_qubits > 10:
        raise ValueError('''number of qubits too large to simulate(>10).'''		)

    A			:  List[Any]   =		QuantumRegister(snake_case__						,							'''qr'''		)
    A			:  Tuple   =		ClassicalRegister(snake_case__						,							'''cr'''		)

    A			:  List[str]   =		QuantumCircuit(snake_case__						,							snake_case__		)

    A			:  Union[str, Any]   =		number_of_qubits

    for i in range(snake_case__		):
        quantum_circuit.h(number_of_qubits - i - 1		)
        counter -= 1
        for j in range(snake_case__		):
            quantum_circuit.cp(np.pi / 2 ** (counter - j)						,							snake_case__						,							snake_case__		)

    for k in range(number_of_qubits // 2		):
        quantum_circuit.swap(snake_case__						,							number_of_qubits - k - 1		)

    # measure all the qubits
    quantum_circuit.measure(snake_case__						,							snake_case__		)
    # simulate with 10000 shots
    A			:  Optional[Any]   =		Aer.get_backend('''qasm_simulator'''		)
    A			:  List[str]   =		execute(snake_case__						,							snake_case__						,							shots=1_0000		)

    return job.result().get_counts(snake_case__		)


if __name__ == "__main__":
      print(
          f'''Total count for quantum fourier transform state is: \
    {quantum_fourier_transform(3)}'''
      )






'''simple docstring'''




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re

from ..utils import cached_file


# docstyle-ignore
lowercase     :							Tuple       						=     '\nHuman: <<task>>\n\nAssistant: '


lowercase     :							Union[str, Any]       						=     'huggingface-tools/default-prompts'
lowercase     :							int       						=     {'chat': 'chat_prompt_template.txt', 'run': 'run_prompt_template.txt'}







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__						,							snake_case__="run"		):




    '''simple docstring'''



    if prompt_or_repo_id is None:
        A			:  List[Any]   =		DEFAULT_PROMPTS_REPO

    # prompt is considered a repo ID when it does not contain any kind of space
    if re.search('''\\s'''						,							snake_case__		) is not None:
        return prompt_or_repo_id

    A			:  int   =		cached_file(
        snake_case__						,							PROMPT_FILES[mode]						,							repo_type='''dataset'''						,							user_agent={'''agent''': agent_name}		)
    with open(snake_case__						,							'''r'''						,							encoding='''utf-8'''		) as f:
        return f.read()




