import numpy as np
import qiskit




def 				_snake_case     (       lowerCAmelCase							:       str       ,			lowerCAmelCase							:       int     ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		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:
				SCREAMING_SNAKE_CASE_  :		Dict    				=   np.random.randint(1       ,			2**num_qubits     )
				# Next, format 'b' as a binary string of length 'n', padded with zeros:
				SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   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)
				SCREAMING_SNAKE_CASE_  :		Any    				=   np.random.randint(2     )
				if output == 1:
						oracle_qc.x(lowerCAmelCase     )

		SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   oracle_qc.to_gate()
		SCREAMING_SNAKE_CASE_  :		Tuple    				=   "Oracle"  # To show when we display the circuit
		return oracle_gate




def 				_snake_case     (       lowerCAmelCase							:       qiskit.QuantumCircuit       ,			lowerCAmelCase							:       int     ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		List[str]    				=   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 				_snake_case     (       lowerCAmelCase							:       str       ,			lowerCAmelCase							:       int     ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		List[Any]    				=   qiskit.Aer.get_backend("aer_simulator"     )

		SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   dj_oracle(lowerCAmelCase       ,			lowerCAmelCase     )
		SCREAMING_SNAKE_CASE_  :		List[str]    				=   dj_algorithm(lowerCAmelCase       ,			lowerCAmelCase     )

		# Execute the circuit on the simulator
		SCREAMING_SNAKE_CASE_  :		List[Any]    				=   qiskit.execute(lowerCAmelCase       ,			lowerCAmelCase       ,			shots=1_0_0_0     )

		# 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)}''')

from ..utils import deprecate
from .attention_processor import (  # noqa: F401
    Attention,
    AttentionProcessor,
    AttnAddedKVProcessor,
    AttnProcessor2_0,
    LoRAAttnProcessor,
    LoRALinearLayer,
    LoRAXFormersAttnProcessor,
    SlicedAttnAddedKVProcessor,
    SlicedAttnProcessor,
    XFormersAttnProcessor,
)
from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401


deprecate(
    '''cross_attention''',
    '''0.20.0''',
    '''Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.''',
    standard_warn=False,
)


__lowerCamelCase :     str          =  AttentionProcessor






class 		a__						( A__ ):

					def __init__(   self				:	Tuple,*_A				:	Union[str, Any],**_A				:	Any   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Any    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )







class 		a__						( A__ ):

					def __init__(   self				:	str,*_A				:	Optional[Any],**_A				:	List[str]   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )







class 		a__						( A__ ):

					def __init__(   self				:	str,*_A				:	Dict,**_A				:	Optional[int]   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Any    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )







class 		a__						( A__ ):

					def __init__(   self				:	List[Any],*_A				:	List[str],**_A				:	str   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Tuple    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )







class 		a__						( A__ ):

					def __init__(   self				:	Optional[int],*_A				:	Any,**_A				:	int   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )







class 		a__						( A__ ):

					def __init__(   self				:	Union[str, Any],*_A				:	Union[str, Any],**_A				:	Any   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[Any]    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )







class 		a__						( A__ ):

					def __init__(   self				:	Dict,*_A				:	Dict,**_A				:	Optional[Any]   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[Any]    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )







class 		a__						( A__ ):

					def __init__(   self				:	int,*_A				:	Dict,**_A				:	Union[str, Any]   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		str    				=   F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"   )   )} instead.'
							deprecate("cross_attention","0.20.0",_A,standard_warn=_A   )
							super().__init__(*_A,**_A   )
