






"""simple docstring"""






import qiskit



def       _A    (__a					,       __a							)				-> qiskit.result.counts.Counts:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						int							=	qiskit.Aer.get_backend('''aer_simulator'''							)

    # Create a Quantum Circuit acting on the q register
    SCREAMING_SNAKE_CASE_   :						Tuple							=	qiskit.QuantumCircuit(__a					,       __a							)

    # 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
    SCREAMING_SNAKE_CASE_   :						Optional[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__":
  UpperCAmelCase_     :				Optional[Any]         =				single_qubit_measure(2, 2)
  print(f'''Total count for various states are: {counts}''')










"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase_     :				List[str]         =				logging.get_logger(__name__)

UpperCAmelCase_     :				Dict         =				{
    """facebook/data2vec-text-base""": """https://huggingface.co/data2vec/resolve/main/config.json""",
}




class 							lowerCAmelCase__       (    UpperCAmelCase__				):






      '''simple docstring'''

      __UpperCamelCase							=						"data2vec-text"
      def __init__(		self  :						Any		,			lowercase_  :						Any=30522		,			lowercase_  :						Any=768		,			lowercase_  :						Union[str, Any]=12		,			lowercase_  :						Dict=12		,			lowercase_  :						List[Any]=3072		,			lowercase_  :						str="gelu"		,			lowercase_  :						int=0.1		,			lowercase_  :						Dict=0.1		,			lowercase_  :						str=512		,			lowercase_  :						Optional[int]=2		,			lowercase_  :						int=0.02		,			lowercase_  :						int=1e-12		,			lowercase_  :						Any=1		,			lowercase_  :						Any=0		,			lowercase_  :						List[Any]=2		,			lowercase_  :						Tuple="absolute"		,			lowercase_  :						Optional[int]=True		,			lowercase_  :						int=None		,			**lowercase_  :						Tuple		,			):




          '''simple docstring'''


          super().__init__(pad_token_id=lowercase_		,			bos_token_id=lowercase_		,			eos_token_id=lowercase_		,			**lowercase_)

          SCREAMING_SNAKE_CASE_   :						List[Any]							=	vocab_size
          SCREAMING_SNAKE_CASE_   :						Tuple							=	hidden_size
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	num_hidden_layers
          SCREAMING_SNAKE_CASE_   :						List[Any]							=	num_attention_heads
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	hidden_act
          SCREAMING_SNAKE_CASE_   :						Any							=	intermediate_size
          SCREAMING_SNAKE_CASE_   :						Tuple							=	hidden_dropout_prob
          SCREAMING_SNAKE_CASE_   :						Tuple							=	attention_probs_dropout_prob
          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	max_position_embeddings
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	type_vocab_size
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	initializer_range
          SCREAMING_SNAKE_CASE_   :						List[Any]							=	layer_norm_eps
          SCREAMING_SNAKE_CASE_   :						str							=	position_embedding_type
          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	use_cache
          SCREAMING_SNAKE_CASE_   :						str							=	classifier_dropout




class 							lowerCAmelCase__       (    UpperCAmelCase__				):






      '''simple docstring'''

      @property
      def _SCREAMING_SNAKE_CASE				(		self  :						int):




          '''simple docstring'''


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


