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testMPI.py
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testMPI.py
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# This file is designed to be run via: mpiexec -np 4 python -W ignore testMPI.py
# This does not use nosetests because I want to set verbosity differently based on rank (quiet if not rank 0)
# By wrapping asserts in comm.rank == 0, only rank 0 should fail (should help with output)
# Can run with different number of procs, but 4 is minimum to test all modes (pure MPI, pure shared mem, and mixed)
import os
import nose
import numpy as np
from mpi4py import MPI
import pygsti
from pygsti.modelpacks import smq1Q_XYI as std
wcomm = MPI.COMM_WORLD
class ParallelTest(object):
# No setup here, must be defined in the derived classes
def test_simulate_data(self):
comm = self.ralloc.comm
exp_design = std.get_gst_experiment_design(4)
mdl_datagen = std.target_model().depolarize(op_noise=0.1, spam_noise=0.01)
ds_serial = pygsti.data.simulate_data(mdl_datagen, exp_design, 1000, seed=1234, comm=None)
ds_parallel = pygsti.data.simulate_data(mdl_datagen, exp_design, 1000, seed=1234, comm=comm)
if comm is None or comm.rank == 0:
assert (set(ds_serial.keys()) == set(ds_parallel.keys()))
for key in ds_serial.keys():
assert (ds_serial[key].to_dict() == ds_parallel[key].to_dict())
def test_gst(self):
comm = self.ralloc.comm
exp_design = std.get_gst_experiment_design(4)
mdl_datagen = std.target_model().depolarize(op_noise=0.1, spam_noise=0.01)
ds = pygsti.data.simulate_data(mdl_datagen, exp_design, 1000, seed=1234, comm=comm)
data = pygsti.protocols.ProtocolData(exp_design, ds)
initial_model = std.target_model("full TP")
proto = pygsti.protocols.GateSetTomography(initial_model, verbosity=1,
optimizer={'maxiter': 100, 'serial_solve_proc_threshold': 100})
results_serial = proto.run(data, comm=None)
results_parallel = proto.run(data, comm=comm)
# compare resulting models
if comm is None or comm.rank == 0:
best_params_serial = results_serial.estimates["GateSetTomography"].models['stdgaugeopt'].to_vector()
best_params_parallel = results_parallel.estimates["GateSetTomography"].models['stdgaugeopt'].to_vector()
assert np.allclose(best_params_serial, best_params_parallel)
def test_MPI_probs(self):
comm = self.ralloc.comm
#Create some model
mdl = std.target_model()
mdl.kick(0.1,seed=1234)
#Get some operation sequences
maxLengths = [1, 2, 4]
circuits = pygsti.circuits.create_lsgst_circuits(
list(std.target_model().operations.keys()), std.prep_fiducials(),
std.meas_fiducials(), std.germs(), maxLengths)
#Check all-spam-label bulk probabilities
def compare_prob_dicts(a,b,indices=None):
for opstr in circuits:
for outcome in a[opstr].keys():
if indices is None:
assert (np.linalg.norm(a[opstr][outcome] - b[opstr][outcome]) < 1e-6)
else:
for i in indices:
assert (np.linalg.norm(a[opstr][outcome][i] - b[opstr][outcome][i]) < 1e-6)
# non-split tree => automatically adjusts wrt_block_size to accomodate
# the number of processors
serial = mdl.sim.bulk_probs(circuits, clip_to=(-1e6,1e6))
parallel = mdl.sim.bulk_probs(circuits, clip_to=(-1e6,1e6), resource_alloc=self.ralloc)
if comm is None or comm.rank == 0: # output is only given on root proc
compare_prob_dicts(serial, parallel)
serial = mdl.sim.bulk_dprobs(circuits)
parallel = mdl.sim.bulk_dprobs(circuits, resource_alloc=self.ralloc)
if comm is None or comm.rank == 0: # output is only given on root proc
compare_prob_dicts(serial, parallel)
serial = mdl.sim.bulk_hprobs(circuits)
parallel = mdl.sim.bulk_hprobs(circuits, resource_alloc=self.ralloc)
if comm is None or comm.rank == 0: # output is only given on root proc
compare_prob_dicts(serial, parallel, (0, 1, 2))
def test_MPI_products(self):
comm = self.ralloc.comm
#Create some model
mdl = std.target_model()
mdl.kick(0.1, seed=1234)
#Get some operation sequences
maxLengths = [1,2,4,8]
gstrs = pygsti.circuits.create_lsgst_circuits(
std.target_model(), std.fiducials(), std.fiducials(), std.germs(), maxLengths)
#Check bulk products
#bulk_product - no parallelization unless layout is split
serial = mdl.sim.bulk_product(gstrs, scale=False)
parallel = mdl.sim.bulk_product(gstrs, scale=False, resource_alloc=self.ralloc)
assert(np.linalg.norm(serial-parallel) < 1e-6)
serial_scl, sscale = mdl.sim.bulk_product(gstrs, scale=True)
parallel, pscale = mdl.sim.bulk_product(gstrs, scale=True, resource_alloc=self.ralloc)
assert(np.linalg.norm(serial_scl*sscale[:,None,None] -
parallel*pscale[:,None,None]) < 1e-6)
#bulk_dproduct - no split tree => parallel by col
serial = mdl.sim.bulk_dproduct(gstrs, scale=False)
parallel = mdl.sim.bulk_dproduct(gstrs, scale=False, resource_alloc=self.ralloc)
assert(np.linalg.norm(serial-parallel) < 1e-6)
serial_scl, sscale = mdl.sim.bulk_dproduct(gstrs, scale=True)
parallel, pscale = mdl.sim.bulk_dproduct(gstrs, scale=True, resource_alloc=self.ralloc)
assert(np.linalg.norm(serial_scl*sscale[:,None,None,None] -
parallel*pscale[:,None,None,None]) < 1e-6)
def test_objfn_generator(self):
params = [
("map", "logl", 1), ("map", "logl", 4),
("map", "chi2", 1), ("map", "chi2", 4),
("matrix", "logl", 1), ("matrix", "logl", 4),
("matrix", "chi2", 1), ("matrix", "chi2", 4)
]
for sim, objfn, natoms in params:
yield self.run_objfn_values, sim, objfn, natoms
def run_objfn_values(self, sim, objfn, natoms):
comm = self.ralloc.comm
mdl = std.target_model()
exp_design = std.get_gst_experiment_design(1)
mdl_datagen = mdl.depolarize(op_noise=0.01, spam_noise=0.01)
ds = pygsti.data.simulate_data(mdl_datagen, exp_design, 1000, seed=1234, comm=comm)
builder = pygsti.objectivefns.ObjectiveFunctionBuilder.create_from(objfn)
builder.additional_args['array_types'] = ('EP', 'EPP') # HACK - todo this better
if sim == 'map':
mdl.sim = pygsti.forwardsims.MapForwardSimulator(num_atoms=natoms)
elif sim == 'matrix':
mdl.sim = pygsti.forwardsims.MatrixForwardSimulator(num_atoms=natoms)
else:
raise RuntimeError("Improper sim type passed by test_objfn_generator")
circuits = exp_design.all_circuits_needing_data[0:10]
objfn_parallel = builder.build(mdl, ds, circuits, self.ralloc, verbosity=0)
objfn_serial = builder.build(mdl, ds, circuits, None, verbosity=0)
#LSVEC TEST
v_ref = objfn_serial.lsvec()
v = objfn_parallel.lsvec()
globalv = objfn_parallel.layout.gather_local_array('e', v)
if comm is None or comm.rank == 0:
finalv = np.empty_like(globalv); off = 0
for c in circuits:
indices, outcomes = objfn_parallel.layout.global_layout.indices_and_outcomes(c)
assert(outcomes == (('0',), ('1',))) # I think this should always be the ordering (?)
finalv[off:off + len(outcomes)] = globalv[indices]
off += len(outcomes)
finalv_ref = np.empty_like(v_ref); off = 0
for c in circuits:
indices, outcomes = objfn_serial.layout.indices_and_outcomes(c)
assert(outcomes == (('0',), ('1',))) # I think this should always be the ordering (?)
finalv_ref[off:off + len(outcomes)] = v_ref[indices]
off += len(outcomes)
assert np.allclose(finalv, finalv_ref)
#TODO: DLSVEC?
#HESSIAN TEST
hessian_ref = objfn_serial.hessian()
hessian = objfn_parallel.hessian() # already a global qty, just on root proc
bhessian_ref = objfn_serial.hessian_brute()
bhessian = objfn_parallel.hessian_brute()
if comm is None or comm.rank == 0:
assert np.allclose(bhessian_ref, hessian_ref)
assert np.allclose(hessian, hessian_ref)
assert np.allclose(bhessian, bhessian_ref)
def test_fills_generator(self):
sims = ["map", "matrix"]
# XYI model with maxL = 1 has 92 circuits and 60 parameters
layout_params = [(1, None), (4, None),
(1, 15), (4, 15)
]
for s in sims:
for natoms, nparams in layout_params:
yield self.run_fills, s, natoms, nparams
def run_fills(self, sim, natoms, nparams):
comm = self.ralloc.comm
#Create some model
mdl = std.target_model()
mdl.kick(0.1,seed=1234)
#Get some operation sequences
maxLengths = [1]
circuits = pygsti.circuits.create_lsgst_circuits(
list(std.target_model().operations.keys()), std.prep_fiducials(),
std.meas_fiducials(), std.germs(), maxLengths)
nP = mdl.num_params
if sim == 'map':
mdl.sim = pygsti.forwardsims.MapForwardSimulator(num_atoms=natoms, param_blk_sizes=(nparams, nparams))
elif sim == 'matrix':
mdl.sim = pygsti.forwardsims.MatrixForwardSimulator(num_atoms=natoms, param_blk_sizes=(nparams, nparams))
else:
raise RuntimeError("Improper sim type passed by test_fills_generator")
serial_layout = mdl.sim.create_layout(circuits, array_types=('E','EP','EPP'), derivative_dimension=nP)
nE = serial_layout.num_elements
nC = len(circuits)
vp_serial = np.empty( nE, 'd')
vdp_serial = np.empty( (nE,nP), 'd')
vhp_serial = np.empty( (nE,nP,nP), 'd')
mdl.sim.bulk_fill_probs(vp_serial, serial_layout)
mdl.sim.bulk_fill_dprobs(vdp_serial, serial_layout)
mdl.sim.bulk_fill_hprobs(vhp_serial, serial_layout)
#Note: when there are multiple atoms, the serial_layout returned above may not preserve
# the original circuit ordering, i.e., serial_layout.circuits != circuits. The global
# layout does have this property, and so we use it to avoid having to lookup which circuit
# is which index in serial_layout. No gathering is needed, since there only 1 processor.
global_serial_layout = serial_layout.global_layout
#Use a parallel layout to compute the same probabilities & their derivatives
local_layout = mdl.sim.create_layout(circuits, array_types=('E','EP','EPP'), derivative_dimension=nP,
resource_alloc=self.ralloc)
vp_local = local_layout.allocate_local_array('e', 'd')
vdp_local = local_layout.allocate_local_array('ep', 'd')
vhp_local = local_layout.allocate_local_array('epp', 'd')
mdl.sim.bulk_fill_probs(vp_local, local_layout)
mdl.sim.bulk_fill_dprobs(vdp_local, local_layout)
mdl.sim.bulk_fill_hprobs(vhp_local, local_layout)
#Gather data to produce arrays for the "global" layout (global_parallel_layout should be the same on all procs)
# but only on proc 0
global_parallel_layout = local_layout.global_layout
vp_global_parallel = local_layout.gather_local_array('e', vp_local)
vdp_global_parallel = local_layout.gather_local_array('ep', vdp_local)
vhp_global_parallel = local_layout.gather_local_array('epp', vhp_local)
#Free the local arrays when we're done with them (they could be shared mem)
local_layout.free_local_array(vp_local)
local_layout.free_local_array(vdp_local)
local_layout.free_local_array(vhp_local)
#Compare the two, but note that different layouts may order the elements differently,
# so we can't just compare the arrays directly - we have to use the layout to map
# circuit index -> element indices:
if comm is None or comm.rank == 0:
for i,opstr in enumerate(circuits):
assert(np.linalg.norm(vp_global_parallel[ global_parallel_layout.indices_for_index(i) ] -
vp_serial[ global_serial_layout.indices_for_index(i) ]) < 1e-6)
assert(np.linalg.norm(vdp_global_parallel[ global_parallel_layout.indices_for_index(i) ] -
vdp_serial[ global_serial_layout.indices_for_index(i) ]) < 1e-6)
assert(np.linalg.norm(vhp_global_parallel[ global_parallel_layout.indices_for_index(i) ] -
vhp_serial[ global_serial_layout.indices_for_index(i) ]) < 1e-6)
def test_MPI_printer(self):
comm = self.ralloc.comm
#Test output of each rank to separate file:
pygsti.baseobjs.VerbosityPrinter._comm_path = "./"
pygsti.baseobjs.VerbosityPrinter._comm_file_name = "mpi_test_output"
printer = pygsti.baseobjs.VerbosityPrinter(verbosity=2, comm=comm)
printer.log("HELLO!")
#
#
# #Note: no need to test "wrtFilter" business - that was removed
#
#
## There are other tests within testmpiMain.py that don't need much/any alteration and would be
## good to transfer to the new MPI unit tests, but:
## - test_MPI_mlgst_forcefn(comm) -- this is never used anymore, you can ignore this test
## - test_MPI_derivcols(comm) -- this is essentially tested by varying the layout types
class PureMPIParallel_Test(ParallelTest):
@classmethod
def setup_class(cls):
# Turn off all shared memory usage
os.environ['PYGSTI_USE_SHARED_MEMORY'] = "0"
cls.ralloc = pygsti.baseobjs.ResourceAllocation(wcomm)
#class OnePerHostShmemParallel_Test(ParallelTest):
# @classmethod
# def setup_class(cls):
# # Use 1 host per shared memory group (i.e. no shared mem communication)
# os.environ['PYGSTI_MAX_HOST_PROCS'] = "1"
# cls.ralloc = pygsti.baseobjs.ResourceAllocation(wcomm)
#
#class TwoPerHostShmemParallel_Test(ParallelTest):
# @classmethod
# def setup_class(cls):
# # Use 2 hosts per shared memory group (i.e. mixed MPI + shared mem if more than 2 procs)
# os.environ['PYGSTI_MAX_HOST_PROCS'] = "2"
# cls.ralloc = pygsti.baseobjs.ResourceAllocation(wcomm)
#
#class AllShmemParallel_Test(ParallelTest):
# @classmethod
# def setup_class(cls):
# # Set as many procs per host as possible to use shared memory
# os.environ['PYGSTI_MAX_HOST_PROCS'] = str(wcomm.size)
# cls.ralloc = pygsti.baseobjs.ResourceAllocation(wcomm)
if __name__ == '__main__':
config = nose.config.Config()
config.verbosity = 2 if wcomm.rank == 0 else 0
nose.main(config=config)
#Eriks manual runs so that debugger can start (I couldn't figure out how to set options to nose)
#tester = PureMPIParallel_Test()
#tester.setup_class()
#tester.ralloc = pygsti.baseobjs.ResourceAllocation(wcomm)
##tester.run_objfn_values('matrix','logl',4)
#tester.run_fills('map',1, None)
#tester.run_fills('map',4, None)
#tester.run_fills('matrix',4, 15)