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Symmer import speed up #165

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Symmer import speed up #165

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8 changes: 4 additions & 4 deletions symmer/operators/base.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
import os
import quimb
from symmer.operators.utils import *
import ray
from ray import put, get, remote
import numpy as np
import pandas as pd
import networkx as nx
Expand Down Expand Up @@ -829,8 +829,8 @@ def expval(self, psi: "QuantumState") -> complex:
"""
if self.n_terms > 1:
# parallelize if number of terms greater than one
psi_ray_store = ray.put(psi)
expvals = np.array(ray.get(
psi_ray_store = put(psi)
expvals = np.array(get(
[single_term_expval.remote(P, psi_ray_store) for P in self]))
else:
expvals = np.array(single_term_expval(self, psi))
Expand Down Expand Up @@ -2399,7 +2399,7 @@ def get_ij_operator(i:int, j:int, n_qubits:int,
else:
return ij_symp_matrix, coeffs

@ray.remote(num_cpus=os.cpu_count(),
@remote(num_cpus=os.cpu_count(),
runtime_env={
"env_vars": {
"NUMBA_NUM_THREADS": os.getenv("NUMBA_NUM_THREADS"),
Expand Down
6 changes: 3 additions & 3 deletions symmer/operators/independent_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
import multiprocessing as mp
from symmer.operators.utils import _rref_binary, _cref_binary, check_independent
from symmer.operators import PauliwordOp, QuantumState, symplectic_to_string, single_term_expval
import ray
from ray import put, get, remote

class IndependentOp(PauliwordOp):
"""
Expand Down Expand Up @@ -296,8 +296,8 @@ def update_sector(self,
# self.coeff_vec = np.array(
# list(pool.starmap(assign_value, [(S, ref_state, threshold) for S in self]))
# )
ref_state_ray_store = ray.put(ref_state)
self.coeff_vec = np.array(ray.get(
ref_state_ray_store = put(ref_state)
self.coeff_vec = np.array(get(
[single_term_expval.remote(S, ref_state_ray_store) for S in self]))
# set anything below threshold to be zero
self.coeff_vec[np.abs(self.coeff_vec)<threshold] = 0
Expand Down
8 changes: 4 additions & 4 deletions symmer/operators/noncontextual_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@
from scipy.optimize import differential_evolution, shgo
from symmer.operators import PauliwordOp, IndependentOp, AntiCommutingOp, QuantumState
from symmer.operators.utils import binomial_coefficient, perform_noncontextual_sweep
import ray
from ray import put, get, remote
from symmer.utils import random_anitcomm_2n_1_PauliwordOp

class NoncontextualOp(PauliwordOp):
Expand Down Expand Up @@ -748,8 +748,8 @@ def energy_via_brute_force(self) -> Tuple[float, np.array, np.array]:
nu_list[:,~self.fixed_ev_mask] = np.array(list(itertools.product([-1,1],repeat=np.sum(~self.fixed_ev_mask))))

# # optimize over all discrete value assignments of nu in parallel
noncon_H = ray.put(self.NC_op)
tracker = np.array(ray.get(
noncon_H = put(self.NC_op)
tracker = np.array(get(
[get_noncon_energy.remote(noncon_H, nu_vec) for nu_vec in nu_list]))

# with mp.Pool(mp.cpu_count()) as pool:
Expand Down Expand Up @@ -879,7 +879,7 @@ def energy_xUSO(self) -> Tuple[float, np.array, np.array]:
return self.NC_op.get_energy(nu_vec), nu_vec


@ray.remote(num_cpus=os.cpu_count(),
@remote(num_cpus=os.cpu_count(),
runtime_env={
"env_vars": {
"NUMBA_NUM_THREADS": os.getenv("NUMBA_NUM_THREADS"),
Expand Down
8 changes: 4 additions & 4 deletions symmer/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
from scipy.sparse import kron as sparse_kron
from symmer.operators.utils import _rref_binary
import multiprocessing as mp
import ray
from ray import put, get, remote
import os
# from psutil import cpu_count

Expand Down Expand Up @@ -270,20 +270,20 @@ def get_sparse_matrix_large_pauliwordop(P_op: PauliwordOp) -> csr_matrix:
n_chunks = os.cpu_count()
if (n_chunks<=1) or (P_op.n_terms<=1):
# no multiprocessing possible
mat = ray.get(_get_sparse_matrix_large_pauliwordop.remote(P_op))
mat = get(_get_sparse_matrix_large_pauliwordop.remote(P_op))
else:
# plus one below due to indexing (actual number of chunks ignores this value)
n_chunks += 1
P_op_chunks_inds = np.rint(np.linspace(0, P_op.n_terms, min(n_chunks, P_op.n_terms+1))).astype(set).astype(int)
P_op_chunks = [P_op[P_op_chunks_inds[ind_i]: P_op_chunks_inds[ind_i + 1]] for ind_i, _ in
enumerate(P_op_chunks_inds[1:])]
tracker = np.array(ray.get(
tracker = np.array(get(
[_get_sparse_matrix_large_pauliwordop.remote(op) for op in P_op_chunks]))
mat = reduce(lambda x, y: x + y, tracker)

return mat

@ray.remote(num_cpus=os.cpu_count(),
@remote(num_cpus=os.cpu_count(),
runtime_env={
"env_vars": {
"NUMBA_NUM_THREADS": os.getenv("NUMBA_NUM_THREADS"),
Expand Down
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