tfq.append_circuit

Merge programs in the input tensors.

tfq.append_circuit(
    programs, programs_to_append
)

Given two tensors of programs, this function merges the programs pairwise and returns a single tensor containing the merged programs. Note that this function is not differentiable because the output has type string.

q = cirq.GridQubit(0, 0)
p0 = [cirq.Circuit(cirq.H(q)), cirq.Circuit(cirq.S(q))]
p1 = [cirq.Circuit(cirq.Z(q)), cirq.Circuit(cirq.X(q))]
p0_t = tfq.convert_to_tensor(p0)
p1_t = tfq.convert_to_tensor(p1)
tfq.from_tensor(append_circuit(p0_t, p1_t))
array([cirq.Circuit([
    cirq.Moment(
        cirq.H(cirq.GridQubit(0, 0)),
    ),
    cirq.Moment(
        cirq.Z(cirq.GridQubit(0, 0)),
    ),
]),
       cirq.Circuit([
    cirq.Moment(
        cirq.S(cirq.GridQubit(0, 0)),
    ),
    cirq.Moment(
        cirq.X(cirq.GridQubit(0, 0)),
    ),
])], dtype=object)

Args
`programs`	`tf.Tensor` of strings with shape [batch_size] containing the string representations of circuits.
`programs_to_append`	`tf.Tensor` of strings with shape [batch_size] containing the string representations of circuits to append.

Returns
`tf.Tensor` with shape [batch_size]. Entry `i` is the string representing the circuit which is `programs_to_append[i]` appended to `programs[i]`.

tfq.append_circuit

Args

Returns