components/qnn.py
def NormalVQC(inputs, entangling_weights):
      '''
      A variational quantum circuit (VQC) (without data re-uploading)
      '''
      qml.AngleEmbedding(features=inputs, wires=range(n_qubits))
      qml.StronglyEntanglingLayers(entangling_weights, wires=range(n_qubits))
      return [qml.expval(qml.PauliZ(wires=i)) for i in range(n_qubits)]

      A variational quantum circuit (VQC) (without data re-uploading)
      
A variational quantum circuit (VQC) (without data re-uploading)
A variational quantum circuit ( VQC ) ( without data re - uploading )
def NormalVQC(inputs, entangling_weights):
      qml.AngleEmbedding(features=inputs, wires=range(n_qubits))
      qml.StronglyEntanglingLayers(entangling_weights, wires=range(n_qubits))
      return [qml.expval(qml.PauliZ(wires=i)) for i in range(n_qubits)]
def NormalVQC ( inputs , entangling_weights ) : qml . AngleEmbedding ( features = inputs , wires = range ( n_qubits ) ) qml . StronglyEntanglingLayers ( entangling_weights , wires = range ( n_qubits ) ) return [ qml . expval ( qml . PauliZ ( wires = i ) ) for i in range ( n_qubits ) ]
A variational quantum circuit (VQC) (without data re-uploading)
A variational quantum circuit ( VQC ) ( without data re - uploading )
'''
      A variational quantum circuit (VQC) (without data re-uploading)
      '''
inputs
entangling_weights