def apply_operator(dtype):
"""Apply the initial_state operator"""
a = tf.zeros(10, dtype=dtype)
return op.initial_state(a)
def _default_initial_state(self) -> tf.Tensor:
"""Creates the |000...0> state for default initialization."""
zeros = tf.zeros(2**self.nqubits, dtype=DTYPES.get('DTYPECPX'))
state = op.initial_state(zeros)
return state
def default(cls, circuit: "DistributedCircuit"):
"""Creates the |000...0> state for default initialization."""
state = cls(circuit)
with tf.device(state.device):
op.initial_state(state.pieces[0])
return state
def grad_custom(var):
with tf.GradientTape() as tape:
loss = custom_operators.initial_state(var)
return tape.gradient(loss, var)