





'''simple docstring'''
import qiskit
def 				lowercase__   (   __lowercase						:  int				,  __lowercase						:  int     ) ->      qiskit.result.counts.Counts:



       """simple docstring"""






       __UpperCamelCase       =  qiskit.Aer.get_backend('aer_simulator'     )

       # Create a Quantum Circuit acting on the q register
       __UpperCamelCase       =  qiskit.QuantumCircuit(__lowercase				,  __lowercase     )

       # Apply X (NOT) Gate to Qubits 0 & 1
       circuit.x(0     )
       circuit.x(1     )

       # Map the quantum measurement to the classical bits
       circuit.measure([0, 1]				,  [0, 1]     )

       # Execute the circuit on the qasm simulator
       __UpperCamelCase       =  qiskit.execute(__lowercase				,  __lowercase				,  shots=1000     )

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


if __name__ == "__main__":
    a__							:							Tuple =single_qubit_measure(2, 2)
    print(f'Total count for various states are: {counts}')







from collections import OrderedDict
from typing import Mapping

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


__UpperCAmelCase       :   Optional[int]				       =							logging.get_logger(__name__)

__UpperCAmelCase       :   Optional[int]				       =							{
    "kssteven/ibert-roberta-base": "https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json",
    "kssteven/ibert-roberta-large": "https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json",
    "kssteven/ibert-roberta-large-mnli": (
        "https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"
    ),
}







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       lowerCAmelCase__      		=     """ibert"""




       def __init__(  self :    Dict							,				A :    Union[str, Any]=30_522							,				A :    List[Any]=768							,				A :    List[Any]=12							,				A :    Optional[int]=12							,				A :    Optional[Any]=3_072							,				A :    int="gelu"							,				A :    str=0.1							,				A :    List[Any]=0.1							,				A :    Optional[Any]=512							,				A :    int=2							,				A :    Union[str, Any]=0.02							,				A :    List[str]=1E-12							,				A :    Optional[int]=1							,				A :    Optional[int]=0							,				A :    List[str]=2							,				A :    str="absolute"							,				A :    Any=False							,				A :    Optional[Any]="none"							,				**A :    Any							,				):
         super().__init__(pad_token_id=A							,				bos_token_id=A							,				eos_token_id=A							,				**A		)

         __snake_case:						List[Any]   =						vocab_size
         __snake_case:						Optional[Any]   =						hidden_size
         __snake_case:						List[str]   =						num_hidden_layers
         __snake_case:						Tuple   =						num_attention_heads
         __snake_case:						List[str]   =						hidden_act
         __snake_case:						Optional[Any]   =						intermediate_size
         __snake_case:						Tuple   =						hidden_dropout_prob
         __snake_case:						List[str]   =						attention_probs_dropout_prob
         __snake_case:						Any   =						max_position_embeddings
         __snake_case:						int   =						type_vocab_size
         __snake_case:						List[str]   =						initializer_range
         __snake_case:						List[Any]   =						layer_norm_eps
         __snake_case:						Optional[int]   =						position_embedding_type
         __snake_case:						str   =						quant_mode
         __snake_case:						Optional[int]   =						force_dequant







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       @property
       def 							UpperCAmelCase__ (  self :    Tuple		):
         if self.task == "multiple-choice":
           __snake_case:						List[Any]   =						{0: """batch""", 1: """choice""", 2: """sequence"""}
         else:
           __snake_case:						List[str]   =						{0: """batch""", 1: """sequence"""}
         return OrderedDict(
             [
                 ("""input_ids""", dynamic_axis),
                 ("""attention_mask""", dynamic_axis),
             ]		)






