


from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
_UpperCAmelCase			:  Optional[int]     =HfArgumentParser(InitializationArguments)
_UpperCAmelCase			:  Optional[int]     =parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
_UpperCAmelCase			:  Union[str, Any]     =AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
_UpperCAmelCase			:  Union[str, Any]     ={
    """vocab_size""": len(tokenizer),
    """scale_attn_by_inverse_layer_idx""": True,
    """reorder_and_upcast_attn""": True,
}

# Load model config (GPT-2 large in this case)
_UpperCAmelCase			:  str     =AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
_UpperCAmelCase			:  int     =AutoModelForCausalLM.from_config(config)

# Save model to the hub
model.save_pretrained(args.model_name, push_to_hub=args.push_to_hub)



import math

import qiskit



def 			lowerCAmelCase (		lowerCAmelCase_ = 1 ,   lowerCAmelCase_ = 1 ,   lowerCAmelCase_ = 1 )-> qiskit.result.counts.Counts:
				if (
				    isinstance(lowerCAmelCase_ ,   lowerCAmelCase_ )
				    or isinstance(lowerCAmelCase_ ,   lowerCAmelCase_ )
				    or isinstance(lowerCAmelCase_ ,   lowerCAmelCase_ )
				):
								raise TypeError('''inputs must be integers.''' )

				if (input_a < 0) or (input_a < 0) or (carry_in < 0):
								raise ValueError('''inputs must be positive.''' )

				if (
				    (math.floor(lowerCAmelCase_ ) != input_a)
				    or (math.floor(lowerCAmelCase_ ) != input_a)
				    or (math.floor(lowerCAmelCase_ ) != carry_in)
				):
								raise ValueError('''inputs must be exact integers.''' )

				if (input_a > 2) or (input_a > 2) or (carry_in > 2):
								raise ValueError('''inputs must be less or equal to 2.''' )

				# build registers
				lowerCAmelCase_ :      str    				=				qiskit.QuantumRegister(4 ,   '''qr''' )
				lowerCAmelCase_ :      str    				=				qiskit.ClassicalRegister(2 ,   '''cr''' )
				# list the entries
				lowerCAmelCase_ :      Any    				=				[input_a, input_a, carry_in]

				lowerCAmelCase_ :      int    				=				qiskit.QuantumCircuit(lowerCAmelCase_ ,   lowerCAmelCase_ )

				for i in range(0 ,   3 ):
								if entry[i] == 2:
												quantum_circuit.h(lowerCAmelCase_ )  # for hadamard entries
								elif entry[i] == 1:
												quantum_circuit.x(lowerCAmelCase_ )  # for 1 entries
								elif entry[i] == 0:
												quantum_circuit.i(lowerCAmelCase_ )  # for 0 entries

    # build the circuit
				quantum_circuit.ccx(0 ,   1 ,   3 )  # ccx = toffoli gate
				quantum_circuit.cx(0 ,   1 )
				quantum_circuit.ccx(1 ,   2 ,   3 )
				quantum_circuit.cx(1 ,   2 )
				quantum_circuit.cx(0 ,   1 )

				quantum_circuit.measure([2, 3] ,   lowerCAmelCase_ )  # measure the last two qbits

				lowerCAmelCase_ :      Tuple    				=				qiskit.Aer.get_backend('''aer_simulator''' )
				lowerCAmelCase_ :      Union[str, Any]    				=				qiskit.execute(lowerCAmelCase_ ,   lowerCAmelCase_ ,   shots=1_000 )

				return job.result().get_counts(lowerCAmelCase_ )


if __name__ == "__main__":
						print(f"""Total sum count for state is: {quantum_full_adder(1, 1, 1)}""")