def assemble_circuits(circuits,
qobj_id=None,
qobj_header=None,
run_config=None):
"""Assembles a list of circuits into a qobj which can be run on the backend.
Args:
circuits (list[QuantumCircuits]): circuit(s) to assemble
qobj_id (int): identifier for the generated qobj
qobj_header (QobjHeader): header to pass to the results
run_config (RunConfig): configuration of the runtime environment
Returns:
QasmQobj: the Qobj to be run on the backends
"""
qobj_config = QasmQobjConfig()
if run_config:
qobj_config = QasmQobjConfig(**run_config.to_dict())
# Pack everything into the Qobj
experiments = []
max_n_qubits = 0
max_memory_slots = 0
for circuit in circuits:
# header stuff
n_qubits = 0
memory_slots = 0
qubit_labels = []
clbit_labels = []
qreg_sizes = []
creg_sizes = []
for qreg in circuit.qregs:
qreg_sizes.append([qreg.name, qreg.size])
for j in range(qreg.size):
qubit_labels.append([qreg.name, j])
n_qubits += qreg.size
for creg in circuit.cregs:
creg_sizes.append([creg.name, creg.size])
for j in range(creg.size):
clbit_labels.append([creg.name, j])
memory_slots += creg.size
# TODO: why do we need creq_sizes and qreg_sizes in header
# TODO: we need to rethink memory_slots as they are tied to classical bit
experimentheader = QobjExperimentHeader(qubit_labels=qubit_labels,
n_qubits=n_qubits,
qreg_sizes=qreg_sizes,
clbit_labels=clbit_labels,
memory_slots=memory_slots,
creg_sizes=creg_sizes,
name=circuit.name)
# TODO: why do we need n_qubits and memory_slots in both the header and the config
experimentconfig = QasmQobjExperimentConfig(n_qubits=n_qubits,
memory_slots=memory_slots)
# Convert conditionals from QASM-style (creg ?= int) to qobj-style
# (register_bit ?= 1), by assuming device has unlimited register slots
# (supported only for simulators). Map all measures to a register matching
# their clbit_index, create a new register slot for every conditional gate
# and add a bfunc to map the creg=val mask onto the gating register bit.
is_conditional_experiment = any(op.control
for (op, qargs, cargs) in circuit.data)
max_conditional_idx = 0
instructions = []
for op_context in circuit.data:
op = op_context[0]
qargs = op_context[1]
cargs = op_context[2]
current_instruction = QasmQobjInstruction(name=op.name)
if qargs:
qubit_indices = [
qubit_labels.index([qubit[0].name, qubit[1]])
for qubit in qargs
]
current_instruction.qubits = qubit_indices
if cargs:
clbit_indices = [
clbit_labels.index([clbit[0].name, clbit[1]])
for clbit in cargs
]
current_instruction.memory = clbit_indices
# If the experiment has conditional instructions, assume every
# measurement result may be needed for a conditional gate.
if op.name == "measure" and is_conditional_experiment:
current_instruction.register = clbit_indices
if op.params:
# Evalute Sympy parameters
params = [
x.evalf() if hasattr(x, 'evalf') else x for x in op.params
]
params = [
sympy.matrix2numpy(x, dtype=complex) if isinstance(
x, sympy.Matrix) else x for x in params
]
current_instruction.params = params
# TODO: I really dont like this for snapshot. I also think we should change
# type to snap_type
if op.name == 'snapshot':
current_instruction.label = str(op.params[0])
current_instruction.snapshot_type = str(op.params[1])
if op.name == 'unitary':
if op._label:
current_instruction.label = op._label
if op.control:
# To convert to a qobj-style conditional, insert a bfunc prior
# to the conditional instruction to map the creg ?= val condition
# onto a gating register bit.
mask = 0
val = 0
for clbit in clbit_labels:
if clbit[0] == op.control[0].name:
mask |= (1 << clbit_labels.index(clbit))
val |= (((op.control[1] >> clbit[1]) & 1) <<
clbit_labels.index(clbit))
conditional_reg_idx = memory_slots + max_conditional_idx
conversion_bfunc = QasmQobjInstruction(
name='bfunc',
mask="0x%X" % mask,
relation='==',
val="0x%X" % val,
register=conditional_reg_idx)
instructions.append(conversion_bfunc)
current_instruction.conditional = conditional_reg_idx
max_conditional_idx += 1
instructions.append(current_instruction)
experiments.append(
QasmQobjExperiment(instructions=instructions,
header=experimentheader,
config=experimentconfig))
if n_qubits > max_n_qubits:
max_n_qubits = n_qubits
if memory_slots > max_memory_slots:
max_memory_slots = memory_slots
qobj_config.memory_slots = max_memory_slots
qobj_config.n_qubits = max_n_qubits
return QasmQobj(qobj_id=qobj_id,
config=qobj_config,
experiments=experiments,
header=qobj_header)
def assemble_circuits(circuits, run_config=None, qobj_header=None, qobj_id=None):
"""Assembles a list of circuits into a qobj which can be run on the backend.
Args:
circuits (list[QuantumCircuits] or QuantumCircuit): circuits to assemble
run_config (RunConfig): RunConfig object
qobj_header (QobjHeader): header to pass to the results
qobj_id (int): identifier for the generated qobj
Returns:
QasmQobj: the Qobj to be run on the backends
"""
qobj_header = qobj_header or QobjHeader()
run_config = run_config or RunConfig()
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
userconfig = QasmQobjConfig(**run_config.to_dict())
experiments = []
max_n_qubits = 0
max_memory_slots = 0
for circuit in circuits:
# header stuff
n_qubits = 0
memory_slots = 0
qubit_labels = []
clbit_labels = []
qreg_sizes = []
creg_sizes = []
for qreg in circuit.qregs:
qreg_sizes.append([qreg.name, qreg.size])
for j in range(qreg.size):
qubit_labels.append([qreg.name, j])
n_qubits += qreg.size
for creg in circuit.cregs:
creg_sizes.append([creg.name, creg.size])
for j in range(creg.size):
clbit_labels.append([creg.name, j])
memory_slots += creg.size
# TODO: why do we need creq_sizes and qreg_sizes in header
# TODO: we need to rethink memory_slots as they are tied to classical bit
experimentheader = QobjExperimentHeader(qubit_labels=qubit_labels,
n_qubits=n_qubits,
qreg_sizes=qreg_sizes,
clbit_labels=clbit_labels,
memory_slots=memory_slots,
creg_sizes=creg_sizes,
name=circuit.name)
# TODO: why do we need n_qubits and memory_slots in both the header and the config
experimentconfig = QasmQobjExperimentConfig(n_qubits=n_qubits, memory_slots=memory_slots)
instructions = []
for op_context in circuit.data:
op = op_context[0]
qargs = op_context[1]
cargs = op_context[2]
current_instruction = QasmQobjInstruction(name=op.name)
if qargs:
qubit_indices = [qubit_labels.index([qubit[0].name, qubit[1]])
for qubit in qargs]
current_instruction.qubits = qubit_indices
if cargs:
clbit_indices = [clbit_labels.index([clbit[0].name, clbit[1]])
for clbit in cargs]
current_instruction.memory = clbit_indices
if op.params:
params = list(map(lambda x: x.evalf(), op.params))
params = [sympy.matrix2numpy(x, dtype=complex)
if isinstance(x, sympy.Matrix) else x for x in params]
if len(params) == 1 and isinstance(params[0], numpy.ndarray):
# TODO: Aer expects list of rows for unitary instruction params;
# change to matrix in Aer.
params = params[0]
current_instruction.params = params
# TODO: I really dont like this for snapshot. I also think we should change
# type to snap_type
if op.name == "snapshot":
current_instruction.label = str(op.params[0])
current_instruction.type = str(op.params[1])
if op.name == 'unitary':
if op._label:
current_instruction.label = op._label
if op.control:
mask = 0
for clbit in clbit_labels:
if clbit[0] == op.control[0].name:
mask |= (1 << clbit_labels.index(clbit))
current_instruction.conditional = QobjConditional(mask="0x%X" % mask,
type='equals',
val="0x%X" % op.control[1])
instructions.append(current_instruction)
experiments.append(QasmQobjExperiment(instructions=instructions, header=experimentheader,
config=experimentconfig))
if n_qubits > max_n_qubits:
max_n_qubits = n_qubits
if memory_slots > max_memory_slots:
max_memory_slots = memory_slots
userconfig.memory_slots = max_memory_slots
userconfig.n_qubits = max_n_qubits
return QasmQobj(qobj_id=qobj_id or str(uuid.uuid4()), config=userconfig,
experiments=experiments, header=qobj_header)