





import qiskit




def  lowerCAmelCase_ (							UpperCamelCase_ = 2  )     ->		qiskit.result.counts.Counts:
       UpperCamelCase_          =  qubits

       # Using Aer's simulator
       UpperCamelCase_          =  qiskit.Aer.get_backend("aer_simulator"  )

       # Creating a Quantum Circuit acting on the q register
       UpperCamelCase_          =  qiskit.QuantumCircuit(UpperCamelCase_					,		UpperCamelCase_  )

       # Adding a H gate on qubit 0 (now q0 in superposition)
       circuit.h(0  )

       for i in range(1					,		UpperCamelCase_  ):
              # Adding CX (CNOT) gate
              circuit.cx(i - 1					,		UpperCamelCase_  )

       # Mapping the quantum measurement to the classical bits
       circuit.measure(list(range(UpperCamelCase_  )  )					,		list(range(UpperCamelCase_  )  )  )

       # Now measuring any one qubit would affect other qubits to collapse
       # their super position and have same state as the measured one.

       # Executing the circuit on the simulator
       UpperCamelCase_          =  qiskit.execute(UpperCamelCase_					,		UpperCamelCase_					,		shots=1000  )

       return job.result().get_counts(UpperCamelCase_  )


if __name__ == "__main__":
     print(f'''Total count for various states are: {quantum_entanglement(3)}''')








from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCAmelCase        =				logging.get_logger(__name__)

_UpperCAmelCase        =				{'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}



class 							_UpperCamelCase					(	lowerCAmelCase_     ):
       _UpperCamelCase				:					List[str]         =   '''openai-gpt'''
       _UpperCamelCase				:					List[str]         =   {
           '''max_position_embeddings''': '''n_positions''',
           '''hidden_size''': '''n_embd''',
           '''num_attention_heads''': '''n_head''',
           '''num_hidden_layers''': '''n_layer''',
       }

       def __init__(		self: int					,   _SCREAMING_SNAKE_CASE: int=40478					,   _SCREAMING_SNAKE_CASE: Optional[Any]=512					,   _SCREAMING_SNAKE_CASE: List[Any]=768					,   _SCREAMING_SNAKE_CASE: str=12					,   _SCREAMING_SNAKE_CASE: Any=12					,   _SCREAMING_SNAKE_CASE: Optional[int]="gelu"					,   _SCREAMING_SNAKE_CASE: int=0.1					,   _SCREAMING_SNAKE_CASE: Optional[int]=0.1					,   _SCREAMING_SNAKE_CASE: Union[str, Any]=0.1					,   _SCREAMING_SNAKE_CASE: Any=1e-5					,   _SCREAMING_SNAKE_CASE: Tuple=0.02					,   _SCREAMING_SNAKE_CASE: str="cls_index"					,   _SCREAMING_SNAKE_CASE: Union[str, Any]=True					,   _SCREAMING_SNAKE_CASE: List[Any]=None					,   _SCREAMING_SNAKE_CASE: List[Any]=True					,   _SCREAMING_SNAKE_CASE: List[Any]=0.1					,   **_SCREAMING_SNAKE_CASE: List[Any]					,   )       -> int:




              """simple docstring"""


              UpperCamelCase_          =  vocab_size
              UpperCamelCase_          =  n_positions
              UpperCamelCase_          =  n_embd
              UpperCamelCase_          =  n_layer
              UpperCamelCase_          =  n_head
              UpperCamelCase_          =  afn
              UpperCamelCase_          =  resid_pdrop
              UpperCamelCase_          =  embd_pdrop
              UpperCamelCase_          =  attn_pdrop
              UpperCamelCase_          =  layer_norm_epsilon
              UpperCamelCase_          =  initializer_range
              UpperCamelCase_          =  summary_type
              UpperCamelCase_          =  summary_use_proj
              UpperCamelCase_          =  summary_activation
              UpperCamelCase_          =  summary_first_dropout
              UpperCamelCase_          =  summary_proj_to_labels
              super().__init__(**_SCREAMING_SNAKE_CASE		)

