
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase__						:	Optional[Any]	     = logging.get_logger(__name__)

UpperCAmelCase__						:	Any	     = {
    'google/electra-small-generator': 'https://huggingface.co/google/electra-small-generator/resolve/main/config.json',
    'google/electra-base-generator': 'https://huggingface.co/google/electra-base-generator/resolve/main/config.json',
    'google/electra-large-generator': 'https://huggingface.co/google/electra-large-generator/resolve/main/config.json',
    'google/electra-small-discriminator': (
        'https://huggingface.co/google/electra-small-discriminator/resolve/main/config.json'
    ),
    'google/electra-base-discriminator': (
        'https://huggingface.co/google/electra-base-discriminator/resolve/main/config.json'
    ),
    'google/electra-large-discriminator': (
        'https://huggingface.co/google/electra-large-discriminator/resolve/main/config.json'
    ),
}






class UpperCAmelCase  (		SCREAMING_SNAKE_CASE__  ):





   '''simple docstring'''
   __UpperCamelCase						:       Optional[int]												=       '''electra'''


   def __init__(   self	:				str     ,     lowerCAmelCase_	:				Dict=3_0_5_2_2     ,     lowerCAmelCase_	:				List[Any]=1_2_8     ,     lowerCAmelCase_	:				Tuple=2_5_6     ,     lowerCAmelCase_	:				Optional[Any]=1_2     ,     lowerCAmelCase_	:				Optional[int]=4     ,     lowerCAmelCase_	:				Dict=1_0_2_4     ,     lowerCAmelCase_	:				Optional[Any]="gelu"     ,     lowerCAmelCase_	:				List[Any]=0.1     ,     lowerCAmelCase_	:				Optional[Any]=0.1     ,     lowerCAmelCase_	:				Any=5_1_2     ,     lowerCAmelCase_	:				List[Any]=2     ,     lowerCAmelCase_	:				Union[str, Any]=0.02     ,     lowerCAmelCase_	:				Any=1e-12     ,     lowerCAmelCase_	:				Optional[int]="first"     ,     lowerCAmelCase_	:				int=True     ,     lowerCAmelCase_	:				Dict="gelu"     ,     lowerCAmelCase_	:				Any=0.1     ,     lowerCAmelCase_	:				str=0     ,     lowerCAmelCase_	:				Optional[int]="absolute"     ,     lowerCAmelCase_	:				Tuple=True     ,     lowerCAmelCase_	:				List[Any]=None     ,     **lowerCAmelCase_	:				List[Any]     ,     ):

      """simple docstring"""
      super().__init__(pad_token_id=lowerCAmelCase_     ,     **lowerCAmelCase_	)

      _A:    Any						     =			vocab_size
      _A:    List[str]						     =			embedding_size
      _A:    Union[str, Any]						     =			hidden_size
      _A:    List[str]						     =			num_hidden_layers
      _A:    Optional[int]						     =			num_attention_heads
      _A:    Tuple						     =			intermediate_size
      _A:    Dict						     =			hidden_act
      _A:    List[Any]						     =			hidden_dropout_prob
      _A:    Dict						     =			attention_probs_dropout_prob
      _A:    Tuple						     =			max_position_embeddings
      _A:    int						     =			type_vocab_size
      _A:    Union[str, Any]						     =			initializer_range
      _A:    Dict						     =			layer_norm_eps

      _A:    List[Any]						     =			summary_type
      _A:    int						     =			summary_use_proj
      _A:    Dict						     =			summary_activation
      _A:    List[Any]						     =			summary_last_dropout
      _A:    Optional[Any]						     =			position_embedding_type
      _A:    int						     =			use_cache
      _A:    Optional[Any]						     =			classifier_dropout






class UpperCAmelCase  (		SCREAMING_SNAKE_CASE__  ):





   '''simple docstring'''


   @property
   def 					__magic_name__							(   self	:				Tuple	):

      """simple docstring"""
      if self.task == "multiple-choice":
         _A:    Union[str, Any]						     =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
      else:
         _A:    List[Any]						     =			{0: '''batch''', 1: '''sequence'''}
      return OrderedDict(
          [
              ('''input_ids''', dynamic_axis),
              ('''attention_mask''', dynamic_axis),
              ('''token_type_ids''', dynamic_axis),
          ]	)





import numpy as np
import qiskit






def     lowerCamelCase__				(   a						,						a ) ->  qiskit.QuantumCircuit:
   _A:    List[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:
      _A:    Any						     =			np.random.randint(1						,						2**num_qubits )
      # Next, format 'b' as a binary string of length 'n', padded with zeros:
      _A:    int						     =			format(a						,						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(a ):
         if bit == "1":
            oracle_qc.x(a )
        # Do the controlled-NOT gates for each qubit, using the output qubit
        # as the target:
      for index in range(a ):
         oracle_qc.cx(a						,						a )
      # Next, place the final X-gates
      for index, bit in enumerate(a ):
         if bit == "1":
            oracle_qc.x(a )

    # 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)
      _A:    int						     =			np.random.randint(2 )
      if output == 1:
         oracle_qc.x(a )

   _A:    int						     =			oracle_qc.to_gate()
   _A:    str						     =			'''Oracle'''  # To show when we display the circuit
   return oracle_gate






def     lowerCamelCase__				(   a						,						a ) ->  qiskit.QuantumCircuit:
   _A:    Optional[int]						     =			qiskit.QuantumCircuit(num_qubits + 1						,						a )
   # Set up the output qubit:
   dj_circuit.x(a )
   dj_circuit.h(a )
   # And set up the input register:
   for qubit in range(a ):
      dj_circuit.h(a )
   # Let's append the oracle gate to our circuit:
   dj_circuit.append(a						,						range(num_qubits + 1 ) )
   # Finally, perform the H-gates again and measure:
   for qubit in range(a ):
      dj_circuit.h(a )

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

   return dj_circuit






def     lowerCamelCase__				(   a						,						a ) ->  qiskit.result.counts.Counts:
   _A:    int						     =			qiskit.Aer.get_backend('''aer_simulator''' )

   _A:    Optional[Any]						     =			dj_oracle(a						,						a )
   _A:    int						     =			dj_algorithm(a						,						a )

   # Execute the circuit on the simulator
   _A:    int						     =			qiskit.execute(a						,						a						,						shots=10_00 )

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


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



