sync
This commit is contained in:
		| @@ -1,4 +1,4 @@ | ||||
| create table c42_vLogistic_6_wmis_siman_results ( | ||||
| create table c42_vLogistic_6_wmis_qpu_results ( | ||||
| 	result_id					char(24), | ||||
|     run							int, | ||||
|     instance_id					char(24), | ||||
| @@ -7,6 +7,7 @@ create table c42_vLogistic_6_wmis_siman_results ( | ||||
|     num_occurrences				int, | ||||
|     energy						float, | ||||
|     satisfiable					boolean, | ||||
|     anneal_time					int, | ||||
|      | ||||
|     primary key (result_id) | ||||
| ); | ||||
| @@ -13,13 +13,22 @@ from dwave.system.samplers import DWaveSampler | ||||
|  | ||||
| from tqdm import tqdm | ||||
|  | ||||
| __QUBO__ = 1 | ||||
| __ISING__ = 2 | ||||
|  | ||||
| def main(): | ||||
|     mode = __get_mode() | ||||
|      | ||||
|     ising_qubo_collection = input("ising/qubo collection: ") | ||||
|      | ||||
|     model_type = __get_model_type() | ||||
|      | ||||
|     result_collection = input("result collection: ") | ||||
|      | ||||
|     if mode == "SIMAN": | ||||
|         __run_siman() | ||||
|         __run_siman(ising_qubo_collection, model_type, result_collection) | ||||
|     elif mode == "QPU": | ||||
|         __run_qpu() | ||||
|         __run_qpu(ising_qubo_collection, model_type, result_collection) | ||||
|      | ||||
| def __get_mode(): | ||||
|     print("choose mode:") | ||||
| @@ -32,31 +41,54 @@ def __get_mode(): | ||||
|     elif mode == 2: | ||||
|         return "QPU" | ||||
|      | ||||
| def __run_siman(): | ||||
| def __get_model_type(): | ||||
|     print("model types:") | ||||
|     print("(q) qubo") | ||||
|     print("(i) ising") | ||||
|     model_type = input("choose: ") | ||||
|      | ||||
|     if model_type == "q": | ||||
|         return __QUBO__ | ||||
|     if model_type == "i": | ||||
|         return __ISING__ | ||||
|      | ||||
| def __run_siman(ising_qubo_collection, model_type, result_collection): | ||||
|     db = script.connect_to_instance_pool() | ||||
|     target_graph =  dnx.chimera_graph(16, 16, 4) | ||||
|     target_graph_id = queries.get_id_of_solver_graph(db["solver_graphs"], | ||||
|                                                      nx.node_link_data(target_graph)) | ||||
|      | ||||
|     solver_input_query = __get_solver_input_query(db, target_graph) | ||||
|     solver_input_query = __get_solver_input_query(db, | ||||
|                                                   target_graph_id, | ||||
|                                                   ising_qubo_collection) | ||||
|      | ||||
|     base_sampler = SimulatedAnnealingSampler() | ||||
|     chimera_sampler = dimod.StructureComposite(base_sampler, | ||||
|                                                target_graph.nodes(), | ||||
|                                                target_graph.edges()) | ||||
|      | ||||
|     __run_on_scope(solver_input_query, db["wmis_siman_results"], base_sampler) | ||||
|     __run_on_scope(solver_input_query, db[result_collection], chimera_sampler, model_type) | ||||
|  | ||||
|  | ||||
| def __run_qpu(): | ||||
| def __run_qpu(ising_qubo_collection, model_type, result_collection): | ||||
|     db = script.connect_to_instance_pool() | ||||
|          | ||||
|     base_solver = DWaveSampler() | ||||
|     solver_graph_id = __get_solver_graph_id(db, base_solver.solver) | ||||
|      | ||||
|     solver_input_query = __get_solver_input_query(db, solver_graph) | ||||
|     solver_input_query = __get_solver_input_query(db, | ||||
|                                                   solver_graph_id, | ||||
|                                                   ising_qubo_collection) | ||||
|  | ||||
|     solver_args = {} | ||||
|     solver_args["annealing_time"] = int(input("annealing time (in us): ")) | ||||
|     solver_args["num_reads"] = int(input("number of reads per sample: ")) | ||||
|      | ||||
|     __run_on_scope(solver_input_query, db["wmis_qpu_results"], base_solver, solver_args) | ||||
|     __run_on_scope(solver_input_query, | ||||
|                    db[result_collection], | ||||
|                    base_solver, | ||||
|                    model_type, | ||||
|                    solver_args) | ||||
|      | ||||
|          | ||||
|  | ||||
| @@ -65,15 +97,20 @@ def __get_solver_graph_id(db, solver): | ||||
|     return queries.get_id_of_solver_graph(db["solver_graphs"], | ||||
|                                           nx.node_link_data(solver_graph)) | ||||
|  | ||||
| def __get_solver_input_query(db, solver): | ||||
|     solver_graph_id = __get_solver_graph_id(db, solver) | ||||
|      | ||||
| def __get_solver_input_query(db, solver_graph_id, ising_qubo_collection): | ||||
|     scope = input("scope: ") | ||||
|      | ||||
|     solver_input_query = queries.WMIS_solver_input_scope_query(db) | ||||
|     solver_input_query = queries.WMIS_solver_input_scope_query(db, ising_qubo_collection) | ||||
|     solver_input_query.query(scope, solver_graph_id) | ||||
|      | ||||
| def __run_on_scope(solver_input_query, result_collection, base_solver, solver_args={}): | ||||
|     return solver_input_query | ||||
|      | ||||
| def __run_on_scope(solver_input_query, | ||||
|                    result_collection, | ||||
|                    base_solver, | ||||
|                    model_type, | ||||
|                    solver_args={}): | ||||
|      | ||||
|     run = int(input("save as run (numbered): ")) | ||||
|      | ||||
|     for solver_input in tqdm(solver_input_query): | ||||
| @@ -83,13 +120,18 @@ def __run_on_scope(solver_input_query, result_collection, base_solver, solver_ar | ||||
|          | ||||
|         solver = FixedEmbeddingComposite(base_solver, embedding) | ||||
|          | ||||
|         res = solver.sample_qubo(qubo, **solver_args) | ||||
|         if model_type == __QUBO__: | ||||
|             res = solver.sample_qubo(qubo, **solver_args) | ||||
|         elif model_type == __ISING__: | ||||
|             h, J = graph.split_ising(qubo) | ||||
|              | ||||
|         script.save_result(result_collection, | ||||
|                            res, | ||||
|                            solver_input, | ||||
|                            emb_list_index = 0, | ||||
|                            run = run) | ||||
|             res = solver.sample_ising(h, J, **solver_args) | ||||
|          | ||||
|         script.save_sample_set(result_collection, | ||||
|                                res, | ||||
|                                solver_input, | ||||
|                                emb_list_index = 0, | ||||
|                                run = run) | ||||
|      | ||||
|      | ||||
|      | ||||
|   | ||||
							
								
								
									
										119
									
								
								testSAT2QUBO.py
									
									
									
									
									
								
							
							
						
						
									
										119
									
								
								testSAT2QUBO.py
									
									
									
									
									
								
							| @@ -2,11 +2,14 @@ | ||||
|  | ||||
| from util import SAT2QUBO as s2q | ||||
| from util import randomSAT as rs | ||||
| from util import queries | ||||
| from util import graph | ||||
|  | ||||
| import networkx as nx | ||||
| import dwave_networkx as dnx | ||||
| import minorminer | ||||
| from dwave_qbsolv import QBSolv | ||||
| import dimod | ||||
|  | ||||
| import matplotlib.pyplot as plt | ||||
| import seaborn as sns | ||||
| @@ -51,7 +54,7 @@ def test_kv_range(): | ||||
|              | ||||
|             ksatInstance = rs.generateRandomKSAT(k, v, 3) | ||||
|              | ||||
|             p_qubo = s2q.primitiveQUBO(ksatInstance) | ||||
|             p_qubo = s2q.primitiveQUBO_5(ksatInstance) | ||||
|  | ||||
|             wmis_qubo = s2q.WMISdictQUBO(ksatInstance) | ||||
|              | ||||
| @@ -233,16 +236,20 @@ def medianChainLength(emb): | ||||
|     for chain in emb.values(): | ||||
|         chl.append(len(chain)) | ||||
|          | ||||
|     return np.median(chl) | ||||
|     sns.distplot(chl) | ||||
|     plt.show() | ||||
|      | ||||
|     return np.mean(chl) | ||||
|      | ||||
|      | ||||
| def test2(): | ||||
|     sat = rs.generateRandomKSAT(15, 4, 3) | ||||
|     sat = rs.generateRandomKSAT(42, 10, 3) | ||||
|      | ||||
|     print(sat.toString()) | ||||
|      | ||||
|     qubo = s2q.WMISdictQUBO(sat) | ||||
|     ising = s2q.primitiveQUBO(sat) | ||||
|     #ising = s2q.primitiveQUBO_8(sat) | ||||
|     ising = s2q.WMISdictQUBO_2(sat) | ||||
|      | ||||
|     qg = nx.Graph() | ||||
|      | ||||
| @@ -261,7 +268,7 @@ def test2(): | ||||
|     print(qg.number_of_nodes(), qg.number_of_edges()) | ||||
|     print(ig.number_of_nodes(), ig.number_of_edges()) | ||||
|      | ||||
|     target = dnx.chimera_graph(9, 9, 4) | ||||
|     target = dnx.chimera_graph(16, 16, 4) | ||||
|     #nx.draw_shell(qg, with_labels=True, node_size=50) | ||||
|     #nx.draw_shell(ig, with_labels=True, node_size=50) | ||||
|      | ||||
| @@ -270,16 +277,20 @@ def test2(): | ||||
|     emb = minorminer.find_embedding(eg.edges(), target.edges(), return_overlap=True, | ||||
|                                     threads=8) | ||||
|      | ||||
|     print("median chain length = {}".format(medianChainLength(emb[0]))) | ||||
|      | ||||
|     print(emb[1]) | ||||
|      | ||||
|     for node, chain in emb[0].items(): | ||||
|         print(node, chain) | ||||
|      | ||||
|     print("avrg chain length = {}".format(medianChainLength(emb[0]))) | ||||
|      | ||||
|     dnx.draw_chimera_embedding(G=target, emb=emb[0], embedded_graph=eg, show_labels=True) | ||||
|      | ||||
|     plt.show() | ||||
|      | ||||
|      | ||||
| def test3(): | ||||
|     sat = rs.generateRandomKSAT(15, 4, 3) | ||||
|     sat = rs.generateRandomKSAT(42, 10, 3) | ||||
|      | ||||
|     print(sat.toString()) | ||||
|      | ||||
| @@ -296,6 +307,7 @@ def test3(): | ||||
|      | ||||
|     res = QBSolv().sample_ising(h, J, find_max=False) | ||||
|      | ||||
|      | ||||
|     sample = list(res.samples())[0] | ||||
|      | ||||
|     extracted = {} | ||||
| @@ -342,6 +354,93 @@ def test3(): | ||||
|      | ||||
|     print(model, sat.checkAssignment(model)) | ||||
|  | ||||
| def test3_3(): | ||||
|     sat = rs.generateRandomKSAT(42, 10, 3) | ||||
|      | ||||
|     print(sat.toString()) | ||||
|      | ||||
|     #ising = s2q.primitiveQUBO_8(sat) | ||||
|     ising = s2q.WMISdictQUBO_2(sat) | ||||
|      | ||||
|     #ising = {} | ||||
|      | ||||
|     #ising[("x1", "z1")] = +2 | ||||
|     #ising[("x2", "z2")] = +2 | ||||
|      | ||||
|     #ising[("z1", "z2")] = +2 | ||||
|      | ||||
|     #ising[("z1", "z1")] = -2 | ||||
|     #ising[("z2", "z2")] = -2 | ||||
|      | ||||
|     #ising[("x1", "z3")] = -2 | ||||
|     #ising[("x2", "z3")] = -2 | ||||
|     #ising[("x3", "z3")] = +2 | ||||
|     #ising[("z3", "z3")] = +2     | ||||
|  | ||||
|      | ||||
|     h, J = graph.split_ising(ising) | ||||
|      | ||||
|     #res = QBSolv().sample_ising(h, J, find_max=False) | ||||
|     res = QBSolv().sample_qubo(ising, find_max=False) | ||||
|      | ||||
|     #res = dimod.ExactSolver().sample_ising(h, J) | ||||
|     #res = dimod.ExactSolver().sample_qubo(ising) | ||||
|      | ||||
|     sample = res.first.sample | ||||
|      | ||||
|     print(res.truncate(50)) | ||||
|     #print(res.truncate(10)) | ||||
|      | ||||
|     assignments = {} | ||||
|     vars = set() | ||||
|      | ||||
|     for node, energy in sample.items(): | ||||
|         if node[0] == "x": | ||||
|             lit = int(node[1:]) | ||||
|              | ||||
|             vars.add(abs(lit)) | ||||
|              | ||||
|             assignments[lit] = energy | ||||
|              | ||||
|     conflicts = set() | ||||
|     for var in vars: | ||||
|         if var in assignments and -var in assignments: | ||||
|             if assignments[var] == assignments[-var]: | ||||
|                 print("conflict at var: {}".format(var)) | ||||
|                 conflicts.add(var) | ||||
|                  | ||||
|     #if conflicts: | ||||
|     #    return  | ||||
|      | ||||
|     model = [True for i in range(len(vars))] | ||||
|      | ||||
|     for var in vars: | ||||
|         if var in assignments: | ||||
|             model[var - 1] = True if assignments[var] == 1 else False | ||||
|         elif -var in assignments: | ||||
|             model[var - 1] = True if assignments[-var] == 0 else False | ||||
|      | ||||
|     print() | ||||
|      | ||||
|     print(model) | ||||
|      | ||||
|     print() | ||||
|      | ||||
|     print(sat.checkAssignment(model)) | ||||
|      | ||||
|     print() | ||||
|      | ||||
|     degrees = sat.getDegreesOfVariables() | ||||
|      | ||||
|     for var in conflicts: | ||||
|         node_var = "x{}".format(var) | ||||
|         node_nvar = "x{}".format(-var) | ||||
|         print("var {}: deg={}, coupler={}, e={}, ne={}" | ||||
|               .format(var, | ||||
|                       degrees[var], | ||||
|                       ising[(node_var, node_nvar)], | ||||
|                       assignments[var], | ||||
|                       assignments[-var])) | ||||
|      | ||||
| def test4(): | ||||
|     sat = rs.generateRandomKSAT(50, 13, 3) | ||||
| @@ -400,4 +499,6 @@ def test4(): | ||||
|     print("used nodes (embedding) = {}".format(len(used_nodes))) | ||||
|      | ||||
|  | ||||
| test_k_range() | ||||
| #test3_3() | ||||
| test2() | ||||
| #test_kv_range() | ||||
|   | ||||
| @@ -3,15 +3,20 @@ | ||||
| import util.script as script | ||||
| import util.queries as queries | ||||
| import dimod | ||||
| import random  | ||||
|  | ||||
| from tqdm import tqdm | ||||
|  | ||||
| def main(): | ||||
|     #instance_parameters() | ||||
|     #wmis_results() | ||||
|     #wmis_siman_results_alpha_num_of_assignments() | ||||
|     #wmis_siman_results() | ||||
|     minisat_runs() | ||||
|     wmis_siman_results_alpha_num_of_assignments() | ||||
|     #wmis_qpu_results_alpha_num_of_assignments() | ||||
|     #primitive_2_siman_results_alpha_num_of_assignments() | ||||
|     #primitive_5_siman_results_alpha_num_of_assignments() | ||||
|     #primitive_5_qpu_results_alpha_num_of_assignments() | ||||
|     #primitive_8_siman_results_alpha_num_of_assignments() | ||||
|     #minisat_runs() | ||||
|  | ||||
| def instance_parameters(): | ||||
|     edb = script.connect_to_experimetns_db() | ||||
| @@ -60,9 +65,9 @@ def wmis_siman_results_alpha_num_of_assignments(): | ||||
|     idb = script.connect_to_instance_pool() | ||||
|      | ||||
|     q = queries.WMIS_result_scope_query_raw(idb) | ||||
|     q.query("c42_vLogistic_6", "wmis_siman_results") | ||||
|     q.query("c42_vLogistic_6", "wmis_qubos_2_siman") | ||||
|      | ||||
|     insert_row = ("INSERT INTO c42_vLogistic_6_wmis_siman_results " | ||||
|     insert_row = ("INSERT INTO c42_vLogistic_6_wmis_1_2_siman_results " | ||||
|                   "(result_id, " | ||||
|                   " run, " | ||||
|                   " instance_id, " | ||||
| @@ -71,7 +76,7 @@ def wmis_siman_results_alpha_num_of_assignments(): | ||||
|                   " num_occurrences, " | ||||
|                   " energy, " | ||||
|                   " satisfiable) " | ||||
|                   "VALUES (%s, %s, %s, %s, %s, %s, %s, %s) ") | ||||
|                   "VALUES (%s, %s, %s, %s,wa %s, %s, %s, %s) ") | ||||
|      | ||||
|     for result in tqdm(q): | ||||
|         sample_set = queries.read_raw_wmis_sample_set(result["data"]) | ||||
| @@ -97,6 +102,302 @@ def wmis_siman_results_alpha_num_of_assignments(): | ||||
|     edb_cursor.close() | ||||
|     edb.close() | ||||
|      | ||||
| def primitive_2_siman_results_alpha_num_of_assignments(): | ||||
|     edb = script.connect_to_experimetns_db() | ||||
|     edb_cursor = edb.cursor() | ||||
|      | ||||
|     idb = script.connect_to_instance_pool() | ||||
|      | ||||
|     q = queries.WMIS_result_scope_query_raw(idb) | ||||
|     q.query("c42_vLogistic_6", "primitive_isings_2_siman_results") | ||||
|      | ||||
|     insert_row = ("INSERT INTO c42_vLogistic_6_primitive_2_siman_results " | ||||
|                   "(result_id, " | ||||
|                   " run, " | ||||
|                   " instance_id, " | ||||
|                   " chain_break_fraction, " | ||||
|                   " num_occurrences, " | ||||
|                   " energy, " | ||||
|                   " satisfiable) " | ||||
|                   "VALUES (%s, %s, %s, %s, %s, %s, %s) ") | ||||
|      | ||||
|          | ||||
|     for result in tqdm(q): | ||||
|         sample_set = queries.read_raw_primitive_ising_sample_set(result["data"]) | ||||
|          | ||||
|         data = script.analyze_wmis_sample(sample_set.first) | ||||
|          | ||||
|         sat = queries.get_instance_by_id(idb["instances"], result["instance"]) | ||||
|          | ||||
|         model = queries.extract_primitive_ising_model(sample_set.first.sample) | ||||
|          | ||||
|         isSatisfiable = sat.checkAssignment(model) | ||||
|          | ||||
|         edb_cursor.execute(insert_row, (str(result["_id"]), | ||||
|                                         int(result["run"]), | ||||
|                                         str(result["instance"]), | ||||
|                                         float(data["chain_break_fraction"]), | ||||
|                                         int(data["num_occurrences"]), | ||||
|                                         int(data["energy"]), | ||||
|                                         isSatisfiable)) | ||||
|          | ||||
|     edb.commit() | ||||
|     edb_cursor.close() | ||||
|     edb.close() | ||||
|      | ||||
|      | ||||
| def primitive_5_siman_results_alpha_num_of_assignments(): | ||||
|     edb = script.connect_to_experimetns_db() | ||||
|     edb_cursor = edb.cursor() | ||||
|      | ||||
|     idb = script.connect_to_instance_pool() | ||||
|      | ||||
|     q = queries.WMIS_result_scope_query_raw(idb) | ||||
|     q.query("c42_vLogistic_6", "primitive_isigns_5_siman") | ||||
|      | ||||
|     insert_row = ("INSERT INTO c42_vLogistic_6_primitive_5_siman_results " | ||||
|                   "(result_id, " | ||||
|                   " run, " | ||||
|                   " instance_id, " | ||||
|                   " chain_break_fraction, " | ||||
|                   " num_occurrences, " | ||||
|                   " energy, " | ||||
|                   " satisfiable, " | ||||
|                   " num_conflicts, " | ||||
|                   " monte_carlo_steps) " | ||||
|                   "VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s) ") | ||||
|      | ||||
|          | ||||
|     for result in tqdm(q): | ||||
|         sample_set = queries.read_raw_primitive_ising_sample_set(result["data"]) | ||||
|          | ||||
|         data = script.analyze_wmis_sample(sample_set.first) | ||||
|          | ||||
|         sat = queries.get_instance_by_id(idb["instances"], result["instance"]) | ||||
|          | ||||
|         post_process_results = __post_process_prim_5_sample(sat, sample_set.first.sample) | ||||
|          | ||||
|         #print(post_process_results) | ||||
|          | ||||
|         edb_cursor.execute(insert_row, (str(result["_id"]), | ||||
|                                         int(result["run"]), | ||||
|                                         str(result["instance"]), | ||||
|                                         float(data["chain_break_fraction"]), | ||||
|                                         int(data["num_occurrences"]), | ||||
|                                         int(data["energy"]), | ||||
|                                         bool(post_process_results["satisfiable"]), | ||||
|                                         int(len(post_process_results["conflicts"])), | ||||
|                                         int(post_process_results["monte_carlo_steps"]))) | ||||
|          | ||||
|     edb.commit() | ||||
|     edb_cursor.close() | ||||
|     edb.close() | ||||
|      | ||||
| def primitive_5_qpu_results_alpha_num_of_assignments(): | ||||
|     edb = script.connect_to_experimetns_db() | ||||
|     edb_cursor = edb.cursor() | ||||
|      | ||||
|     idb = script.connect_to_instance_pool() | ||||
|      | ||||
|     q = queries.WMIS_result_scope_query_raw(idb) | ||||
|     q.query("c42_vLogistic_6", "primitive_isings_5_qpu") | ||||
|      | ||||
|     insert_row = ("INSERT INTO c42_vLogistic_6_primitive_5_qpu_results " | ||||
|                   "(result_id, " | ||||
|                   " run, " | ||||
|                   " instance_id, " | ||||
|                   " chain_break_fraction, " | ||||
|                   " num_occurrences, " | ||||
|                   " energy, " | ||||
|                   " satisfiable, " | ||||
|                   " num_conflicts, " | ||||
|                   " monte_carlo_steps, " | ||||
|                   " anneal_time) " | ||||
|                   "VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s) ") | ||||
|      | ||||
|          | ||||
|     run = int(input("run: ")) | ||||
|      | ||||
|     for result in tqdm(q): | ||||
|         if True: | ||||
|         #if result["run"] == run: | ||||
|             sample_set = queries.read_raw_primitive_ising_sample_set(result["data"]) | ||||
|              | ||||
|             data = script.analyze_wmis_sample(sample_set.first) | ||||
|              | ||||
|             sat = queries.get_instance_by_id(idb["instances"], result["instance"]) | ||||
|              | ||||
|             post_process_results = __post_process_prim_5_sample(sat, | ||||
|                                                                 sample_set.first.sample) | ||||
|              | ||||
|             anneal_time = result["data"]["info"]["timing"]["qpu_anneal_time_per_sample"] | ||||
|             #print(post_process_results) | ||||
|              | ||||
|             edb_cursor.execute(insert_row, (str(result["_id"]), | ||||
|                                             int(result["run"]), | ||||
|                                             str(result["instance"]), | ||||
|                                             float(data["chain_break_fraction"]), | ||||
|                                             int(data["num_occurrences"]), | ||||
|                                             int(data["energy"]), | ||||
|                                             bool(post_process_results["satisfiable"]), | ||||
|                                             int(len(post_process_results["conflicts"])), | ||||
|                                             int(post_process_results["monte_carlo_steps"]), | ||||
|                                             int(anneal_time))) | ||||
|          | ||||
|     edb.commit() | ||||
|     edb_cursor.close() | ||||
|     edb.close() | ||||
|      | ||||
| def primitive_8_siman_results_alpha_num_of_assignments(): | ||||
|     edb = script.connect_to_experimetns_db() | ||||
|     edb_cursor = edb.cursor() | ||||
|      | ||||
|     idb = script.connect_to_instance_pool() | ||||
|      | ||||
|     q = queries.WMIS_result_scope_query_raw(idb) | ||||
|     q.query("c42_vLogistic_6", "wmis_2_qubos_siman") | ||||
|      | ||||
|     insert_row = ("INSERT INTO c42_vLogistic_6_wmis_2_2_siman_results " | ||||
|                   "(result_id, " | ||||
|                   " run, " | ||||
|                   " instance_id, " | ||||
|                   " chain_break_fraction, " | ||||
|                   " num_occurrences, " | ||||
|                   " energy, " | ||||
|                   " satisfiable) " | ||||
|                   "VALUES (%s,  %s, %s, %s, %s, %s, %s) ") | ||||
|      | ||||
|          | ||||
|     run = int(input("run: ")) | ||||
|      | ||||
|     for result in tqdm(q): | ||||
|         if result["run"] == run: | ||||
|             sample_set = queries.read_raw_primitive_ising_sample_set(result["data"]) | ||||
|              | ||||
|             data = script.analyze_wmis_sample(sample_set.first) | ||||
|              | ||||
|             sat = queries.get_instance_by_id(idb["instances"], result["instance"]) | ||||
|              | ||||
|             post_process_results = __post_process_prim_5_sample(sat, | ||||
|                                                                 sample_set.first.sample) | ||||
|              | ||||
|             #print(post_process_results) | ||||
|              | ||||
|             edb_cursor.execute(insert_row, (str(result["_id"]), | ||||
|                                             int(result["run"]), | ||||
|                                             str(result["instance"]), | ||||
|                                             float(data["chain_break_fraction"]), | ||||
|                                             int(data["num_occurrences"]), | ||||
|                                             int(data["energy"]), | ||||
|                                             bool(post_process_results["satisfiable"]))) | ||||
|          | ||||
|     edb.commit() | ||||
|     edb_cursor.close() | ||||
|     edb.close() | ||||
|  | ||||
| def __post_process_prim_5_sample(sat, sample): | ||||
|     post_process_results = {} | ||||
|      | ||||
|     assignments = {} | ||||
|     vars = set() | ||||
|      | ||||
|     for node, energy in sample.items(): | ||||
|         if node[0] == "x": | ||||
|             lit = int(node[1:]) | ||||
|              | ||||
|             vars.add(abs(lit)) | ||||
|              | ||||
|             assignments[lit] = energy | ||||
|      | ||||
|     conflicts = set() | ||||
|     for var in vars: | ||||
|         if var in assignments and -var in assignments: | ||||
|             if assignments[var] == assignments[-var]: | ||||
|                 conflicts.add(var) | ||||
|                  | ||||
|     model = [True for i in range(len(vars))] | ||||
|      | ||||
|     for var in vars: | ||||
|         if var in assignments: | ||||
|             model[var - 1] = True if assignments[var] == 1 else False | ||||
|         elif -var in assignments: | ||||
|             model[var - 1] = True if assignments[-var] == 0 else False | ||||
|              | ||||
|      | ||||
|      | ||||
|     var_list = list(conflicts) | ||||
|      | ||||
|     monte_carlo_steps = 0 | ||||
|     if len(conflicts) > 0: | ||||
|         for i in range(1000): | ||||
|             rand_var = random.choice(var_list) | ||||
|          | ||||
|             if sat.checkAssignment(model): | ||||
|                 monte_carlo_steps | ||||
|                 break | ||||
|          | ||||
|             model[rand_var - 1] = not model[rand_var - 1] | ||||
|          | ||||
|             monte_carlo_steps += 1 | ||||
|          | ||||
|     post_process_results["conflicts"] = conflicts | ||||
|     post_process_results["satisfiable"] = sat.checkAssignment(model) | ||||
|     post_process_results["monte_carlo_steps"] = monte_carlo_steps | ||||
|      | ||||
|     return post_process_results | ||||
|  | ||||
| def wmis_qpu_results_alpha_num_of_assignments(): | ||||
|     edb = script.connect_to_experimetns_db() | ||||
|     edb_cursor = edb.cursor() | ||||
|      | ||||
|     idb = script.connect_to_instance_pool() | ||||
|      | ||||
|     q = queries.WMIS_result_scope_query_raw(idb) | ||||
|     q.query("c42_vLogistic_6", "wmis_qpu_results") | ||||
|      | ||||
|     insert_row = ("INSERT INTO c42_vLogistic_6_wmis_qpu_results " | ||||
|                   "(result_id, " | ||||
|                   " run, " | ||||
|                   " instance_id, " | ||||
|                   " number_of_found_assignments, " | ||||
|                   " chain_break_fraction, " | ||||
|                   " num_occurrences, " | ||||
|                   " energy, " | ||||
|                   " satisfiable, " | ||||
|                   " anneal_time) " | ||||
|                   "VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s) ") | ||||
|      | ||||
|     run = int(input("run: ")) | ||||
|     for result in tqdm(q): | ||||
|         if result["run"] == run: | ||||
|             sample_set = queries.read_raw_wmis_sample_set(result["data"]) | ||||
|          | ||||
|             data = script.analyze_wmis_sample(sample_set.first) | ||||
|          | ||||
|             sat = queries.get_instance_by_id(idb["instances"], result["instance"]) | ||||
|          | ||||
|             model = script.majority_vote_sample(sample_set.first.sample) | ||||
|          | ||||
|             isSatisfiable = sat.checkAssignment(model) | ||||
|          | ||||
|             anneal_time = result["data"]["info"]["timing"]["qpu_anneal_time_per_sample"] | ||||
|          | ||||
|          | ||||
|             edb_cursor.execute(insert_row, (str(result["_id"]), | ||||
|                                             int(result["run"]), | ||||
|                                             str(result["instance"]), | ||||
|                                             int(data["number_of_assignments"]), | ||||
|                                             float(data["chain_break_fraction"]), | ||||
|                                             int(data["num_occurrences"]), | ||||
|                                             int(data["energy"]), | ||||
|                                             isSatisfiable, | ||||
|                                             int(anneal_time))) | ||||
|          | ||||
|     edb.commit() | ||||
|     edb_cursor.close() | ||||
|     edb.close() | ||||
|  | ||||
|  | ||||
| def minisat_runs(): | ||||
|     edb = script.connect_to_experimetns_db() | ||||
|     edb_cursor = edb.cursor(); | ||||
|   | ||||
| @@ -23,13 +23,15 @@ from dwave_qbsolv import QBSolv | ||||
|  | ||||
| import numpy as np | ||||
| import random | ||||
| import re | ||||
|  | ||||
| from tqdm import tqdm | ||||
|  | ||||
| def main(): | ||||
|     #__wmis() | ||||
|     __pqubo_3() | ||||
|     #__pqubo() | ||||
|     __wmis3() | ||||
|     #__wmis3() | ||||
|      | ||||
|  | ||||
| def __qubo_to_nx_graph(qubo): | ||||
| @@ -119,64 +121,74 @@ def __wmis_qpu(): | ||||
|      | ||||
|      | ||||
| def __wmis(): | ||||
|     sat = rand_sat.generateRandomKSAT(25, 6, 3) | ||||
|     qubo = __negate_qubo(SAT2QUBO.WMISdictQUBO(sat)) | ||||
|     #qubo = SAT2QUBO.WMISdictQUBO(sat) | ||||
|     nx_qubo = __qubo_to_nx_graph(qubo) | ||||
|     sat_count = 0 | ||||
|     no_embedding_count = 0 | ||||
|      | ||||
|     target_graph = dnx.chimera_graph(16, 16, 4) | ||||
|     for i in range(200): | ||||
|         sat = rand_sat.generateRandomKSAT(40, 14, 3) | ||||
|         qubo = SAT2QUBO.WMISdictQUBO(sat) | ||||
|         #qubo = SAT2QUBO.WMISdictQUBO(sat) | ||||
|         nx_qubo = __qubo_to_nx_graph(qubo) | ||||
|          | ||||
|     emb = minorminer.find_embedding(nx_qubo.edges(), | ||||
|                                     target_graph.edges(), | ||||
|                                     return_overlap=True) | ||||
|         target_graph = dnx.chimera_graph(16, 16, 4) | ||||
|          | ||||
|     if emb[1] != 1: | ||||
|         print("no embedding found") | ||||
|         return | ||||
|         emb = minorminer.find_embedding(nx_qubo.edges(), | ||||
|                                         target_graph.edges(), | ||||
|                                         return_overlap=True) | ||||
|          | ||||
|     print(emb[0]) | ||||
|         if emb[1] != 1: | ||||
|             print("no embedding found") | ||||
|             no_embedding_count += 1 | ||||
|             continue | ||||
|          | ||||
|     chimera_sampler = dimod.StructureComposite(SimulatedAnnealingSampler(), | ||||
|                                                target_graph.nodes(), | ||||
|                                                target_graph.edges()) | ||||
|         #print(emb[0]) | ||||
|          | ||||
|         chimera_sampler = dimod.StructureComposite(SimulatedAnnealingSampler(), | ||||
|                                                 target_graph.nodes(), | ||||
|                                                 target_graph.edges()) | ||||
|          | ||||
|          | ||||
|          | ||||
|     sampler = FixedEmbeddingComposite(chimera_sampler, emb[0]) | ||||
|         sampler = FixedEmbeddingComposite(chimera_sampler, emb[0]) | ||||
|  | ||||
|          | ||||
|     res = sampler.sample_qubo(qubo) | ||||
|     #res = SimulatedAnnealingSampler().sample_qubo(qubo) | ||||
|         res = sampler.sample_qubo(qubo, chain_strength=2) | ||||
|         #res = SimulatedAnnealingSampler().sample_qubo(qubo) | ||||
|          | ||||
|     #dwave.embedding.chain_breaks.majority_vote(res, emb[0]) | ||||
|         #dwave.embedding.chain_breaks.majority_vote(res, emb[0]) | ||||
|          | ||||
|     first = res.first | ||||
|         first = res.first | ||||
|          | ||||
|     print("chain_break_fraction={}".format(first.chain_break_fraction)) | ||||
|     for lit, spin in first.sample.items(): | ||||
|         print(lit, spin) | ||||
|     print("true count: {}".format(np.count_nonzero(list(first.sample.values())))) | ||||
|         print("chain_break_fraction={}".format(first.chain_break_fraction)) | ||||
|         #for lit, spin in first.sample.items(): | ||||
|             #print(lit, spin) | ||||
|         print("true count: {}".format(np.count_nonzero(list(first.sample.values())))) | ||||
|          | ||||
|     assignments = {} | ||||
|         assignments = {} | ||||
|          | ||||
|     for coupler, energy in first.sample.items(): | ||||
|         for coupler, energy in first.sample.items(): | ||||
|              | ||||
|         var = abs(coupler[1]) | ||||
|             var = abs(coupler[1]) | ||||
|              | ||||
|         if var not in assignments: | ||||
|             assignments[var] = {"all": []} | ||||
|             if var not in assignments: | ||||
|                 assignments[var] = {"all": []} | ||||
|              | ||||
|         if energy == 1: | ||||
|             assignments[var]["all"].append(1 if coupler[1] > 0 else 0) | ||||
|             if energy == 1: | ||||
|                 assignments[var]["all"].append(1 if coupler[1] > 0 else 0) | ||||
|          | ||||
|     __majority_vote(assignments) | ||||
|         __majority_vote(assignments) | ||||
|                          | ||||
|     #for var, a in assignments.items(): | ||||
|         ##print(var, np.sort(a["all"]), __majority_percentage(a["all"])) | ||||
|         #print(var, a) | ||||
|     final = __extract_assignment(assignments) | ||||
|     print(final) | ||||
|     print("satisfies sat: {}".format(sat.checkAssignment(final))) | ||||
|         #for var, a in assignments.items(): | ||||
|             ##print(var, np.sort(a["all"]), __majority_percentage(a["all"])) | ||||
|             #print(var, a) | ||||
|         final = __extract_assignment(assignments) | ||||
|         print(final) | ||||
|         print("satisfies sat: {}".format(sat.checkAssignment(final))) | ||||
|          | ||||
|         if sat.checkAssignment(final): | ||||
|             sat_count += 1 | ||||
|          | ||||
|     print("sat ratio: {}".format(sat_count / (200 - no_embedding_count))) | ||||
|  | ||||
| def __optimize_assignment(sat, assignment, consistencies): | ||||
|     rnd = random.Random() | ||||
| @@ -237,7 +249,7 @@ def __majority_percentage(a): | ||||
|     return true_perc if true_perc >= 0.5 else 1 - true_perc | ||||
|  | ||||
| def __pqubo(): | ||||
|     sat = rand_sat.generateRandomKSAT(25, 6, 3) | ||||
|     sat = rand_sat.generateRandomKSAT(42, 7, 3) | ||||
|     ising = SAT2QUBO.primitiveQUBO(sat) | ||||
|     nx_qubo = __qubo_to_nx_graph(ising) | ||||
|      | ||||
| @@ -260,9 +272,167 @@ def __pqubo(): | ||||
|     h, J = __split_ising(ising) | ||||
|      | ||||
|     res = sampler.sample_ising(h, J) | ||||
|     #res = QBSolv().sample_qubo(qubo, find_max=True) | ||||
|     #res = sampler.sample_ising(h, J, find_max=False) | ||||
|      | ||||
|     print(res.first) | ||||
|     print(res.truncate(10)) | ||||
|      | ||||
|     sample = res.first.sample | ||||
|      | ||||
|     extracted = {} | ||||
|      | ||||
|     r = re.compile("c\d+_l-?\d*") | ||||
|      | ||||
|     for label, assignment in sample.items(): | ||||
|         if r.fullmatch(label): | ||||
|              | ||||
|             extracted[tuple(re.split(r"\_l", label[1:]))] = assignment | ||||
|              | ||||
|     model = [True for i in range(len(extracted))] | ||||
|      | ||||
|     assignments = {} | ||||
|      | ||||
|     for label, assignment in extracted.items(): | ||||
|         clause = int(label[0]) | ||||
|         lit = int(label[1]) | ||||
|         var = abs(lit) | ||||
|          | ||||
|         if lit < 0: | ||||
|             assignment *= -1 | ||||
|          | ||||
|         if var in assignments: | ||||
|             assignments[var].append(assignment) | ||||
|         else: | ||||
|             assignments[var] = [assignment] | ||||
|              | ||||
|  | ||||
|     conflicts = False | ||||
|     for var, a in assignments.items(): | ||||
|         if abs(np.sum(a)) != len(a): | ||||
|             conflicts = True | ||||
|             print("conflicts - no solution found") | ||||
|             print(var, np.sort(a)) | ||||
|              | ||||
|     if conflicts: | ||||
|         print(assignments) | ||||
|         return  | ||||
|      | ||||
|     model = [True for i in range(sat.getNumberOfVariables())] | ||||
|      | ||||
|     for var, assignment in assignments.items(): | ||||
|         model[var - 1] = True if assignment[0] > 0 else False | ||||
|      | ||||
|     print(model, sat.checkAssignment(model)) | ||||
|  | ||||
| def __pqubo_3(): | ||||
|     sat_count = 0 | ||||
|     no_embedding_count = 0 | ||||
|      | ||||
|     for i in range(200): | ||||
|         sat = rand_sat.generateRandomKSAT(40, 14, 3) | ||||
|         #ising = SAT2QUBO.primitiveQUBO_8(sat) | ||||
|         ising = SAT2QUBO.WMISdictQUBO_2(sat) | ||||
|         nx_qubo = __qubo_to_nx_graph(ising) | ||||
|          | ||||
|         target_graph = dnx.chimera_graph(16, 16, 4) | ||||
|          | ||||
|         emb = minorminer.find_embedding(nx_qubo.edges(), | ||||
|                                         target_graph.edges(), | ||||
|                                         return_overlap=True) | ||||
|          | ||||
|         if emb[1] != 1: | ||||
|             print("no embedding found") | ||||
|             no_embedding_count += 1 | ||||
|             continue | ||||
|          | ||||
|         chimera_sampler = dimod.StructureComposite(SimulatedAnnealingSampler(), | ||||
|                                                 target_graph.nodes(), | ||||
|                                                 target_graph.edges()) | ||||
|          | ||||
|         sampler = FixedEmbeddingComposite(chimera_sampler, emb[0]) | ||||
|          | ||||
|          | ||||
|         h, J = __split_ising(ising) | ||||
|          | ||||
|         res = sampler.sample_qubo(ising) | ||||
|         #res = sampler.sample_ising(h, J, find_max=False) | ||||
|          | ||||
|         print(res.truncate(10)) | ||||
|          | ||||
|         print("chain_break_fraction", res.first.chain_break_fraction) | ||||
|          | ||||
|         sample = res.first.sample | ||||
|          | ||||
|         assignments = {} | ||||
|         vars = set() | ||||
|          | ||||
|         for node, energy in sample.items(): | ||||
|             if node[0] == "x": | ||||
|                 lit = int(node[1:]) | ||||
|                  | ||||
|                 vars.add(abs(lit)) | ||||
|                  | ||||
|                 assignments[lit] = energy | ||||
|          | ||||
|         print(assignments) | ||||
|          | ||||
|         conflicts = set() | ||||
|         for var in vars: | ||||
|             if var in assignments and -var in assignments: | ||||
|                 if assignments[var] == assignments[-var]: | ||||
|                     print("conflict at var: {}".format(var)) | ||||
|                     conflicts.add(var) | ||||
|                      | ||||
|         #if conflicts: | ||||
|         #    return  | ||||
|          | ||||
|         model = [True for i in range(len(vars))] | ||||
|          | ||||
|         for var in vars: | ||||
|             if var in assignments: | ||||
|                 model[var - 1] = True if assignments[var] == 1 else False | ||||
|             elif -var in assignments: | ||||
|                 model[var - 1] = True if assignments[-var] == 0 else False | ||||
|                  | ||||
|          | ||||
|          | ||||
|         var_list = list(conflicts) | ||||
|          | ||||
|         print(sat.checkAssignment(model)) | ||||
|         if len(var_list) > 0: | ||||
|             for i in range(1000): | ||||
|                  | ||||
|                 if sat.checkAssignment(model): | ||||
|                     print(i) | ||||
|                     break | ||||
|                  | ||||
|                 rand_var = random.choice(var_list) | ||||
|                  | ||||
|                 model[rand_var - 1] = not model[rand_var - 1] | ||||
|                  | ||||
|              | ||||
|         print() | ||||
|          | ||||
|         print(model) | ||||
|         print() | ||||
|          | ||||
|         print(sat.checkAssignment(model)) | ||||
|         if sat.checkAssignment(model): | ||||
|             sat_count += 1 | ||||
|         print() | ||||
|          | ||||
|         degrees = sat.getDegreesOfVariables() | ||||
|          | ||||
|         for var in conflicts: | ||||
|             node_var = "x{}".format(var) | ||||
|             node_nvar = "x{}".format(-var) | ||||
|             print("var {}: deg={}, coupler={}, e={}, ne={}" | ||||
|                 .format(var, | ||||
|                         degrees[var], | ||||
|                         ising[(node_var, node_nvar)], | ||||
|                         assignments[var], | ||||
|                         assignments[-var])) | ||||
|      | ||||
|     print("sat ratio: {}".format(sat_count / (200 - no_embedding_count))) | ||||
|      | ||||
| def __split_ising(ising): | ||||
|     h = {} | ||||
|   | ||||
							
								
								
									
										622
									
								
								util/SAT2QUBO.py
									
									
									
									
									
								
							
							
						
						
									
										622
									
								
								util/SAT2QUBO.py
									
									
									
									
									
								
							| @@ -4,9 +4,10 @@ import numpy as np | ||||
| from . import kSAT | ||||
| from tqdm import tqdm | ||||
| import math | ||||
| import random | ||||
|  | ||||
| __VERTEX_WEIGHT__ = -1 | ||||
| __EDGE_WEIGHT__ = 2 | ||||
| __VERTEX_WEIGHT__ = -2#-1 | ||||
| __EDGE_WEIGHT__ = 2#2 | ||||
|  | ||||
| def WMISdictQUBO(kSATInstance): | ||||
|     quboInstance = {} | ||||
| @@ -32,6 +33,37 @@ def WMISdictQUBO(kSATInstance): | ||||
|      | ||||
|     return quboInstance | ||||
|  | ||||
| def WMISdictQUBO_2(kSATInstance): | ||||
|     quboInstance = {} | ||||
|      | ||||
|     for clauseIndex in range(kSATInstance.getNumberOfClauses()): | ||||
|         clause = kSATInstance.getClause(clauseIndex) | ||||
|          | ||||
|         # build triangles | ||||
|         for varIndexInClause in range(len(clause)): | ||||
|             lit = clause[varIndexInClause] | ||||
|             var = abs(lit) | ||||
|              | ||||
|             aux = "z{}_{}".format(clauseIndex, var) | ||||
|             var_node = "x{}".format(var) | ||||
|              | ||||
|             if lit < 0: | ||||
|                 quboInstance[(aux, aux)] = __VERTEX_WEIGHT__ | ||||
|                 quboInstance[(var_node, aux)] = __EDGE_WEIGHT__ | ||||
|             else: | ||||
|                 quboInstance[(var_node, aux)] = __VERTEX_WEIGHT__ | ||||
|              | ||||
|              | ||||
|              | ||||
|             for i in range(varIndexInClause + 1, len(clause)): | ||||
|                 var2 = abs(clause[i]) | ||||
|                  | ||||
|                 aux2 = "z{}_{}".format(clauseIndex, var2) | ||||
|                  | ||||
|                 quboInstance[(aux, aux2)] = __EDGE_WEIGHT__ | ||||
|      | ||||
|     return quboInstance | ||||
|  | ||||
| # only 3sat | ||||
| def primitiveQUBO(sat): | ||||
|     quboInstance = {} | ||||
| @@ -47,10 +79,10 @@ def primitiveQUBO(sat): | ||||
|         lit1 = "c{}_l{}".format(clauseIndex, clause[0]) | ||||
|         lit2 = "c{}_l{}".format(clauseIndex, clause[1]) | ||||
|         lit3 = "c{}_l{}".format(clauseIndex, clause[2]) | ||||
|         aux1 = "a{}_{}".format(clauseIndex, 1) | ||||
|         aux2 = "a{}_{}".format(clauseIndex, 2) | ||||
|         aux3 = "a{}_{}".format(clauseIndex, 3) | ||||
|         aux4 = "a{}_{}".format(clauseIndex, 4) | ||||
|         aux1 = "z{}_{}".format(clauseIndex, 1) | ||||
|         aux2 = "z{}_{}".format(clauseIndex, 2) | ||||
|         aux3 = "z{}_{}".format(clauseIndex, 3) | ||||
|         aux4 = "z{}_{}".format(clauseIndex, 4) | ||||
|          | ||||
|         quboInstance[(lit1, lit1)] = 1; | ||||
|         quboInstance[(lit2, lit2)] = 1; | ||||
| @@ -91,7 +123,15 @@ def primitiveQUBO(sat): | ||||
|             longestChain = len(nodes) | ||||
|              | ||||
|         if lit > 0 and -1 * lit in chains: | ||||
|             quboInstance[(chains[lit][0], chains[-1*lit][0])] = 2 | ||||
|             len_smaller_chain = min(len(chains[lit]), len(chains[-lit])) | ||||
|              | ||||
|             indices = random.sample(list(range(len_smaller_chain)), | ||||
|                                     round(len_smaller_chain / 2)) | ||||
|              | ||||
|             for index in indices: | ||||
|                 quboInstance[(chains[lit][index], chains[-1*lit][index])] = 10 | ||||
|              | ||||
|             #quboInstance[(chains[lit][0], chains[-1*lit][0])] = 2 | ||||
|              | ||||
|     print("longest chain = {}".format(longestChain)) | ||||
|      | ||||
| @@ -102,6 +142,574 @@ def primitiveQUBO(sat): | ||||
|      | ||||
|     return quboInstance | ||||
|  | ||||
| # only 3sat | ||||
| def primitiveQUBO_2(sat): | ||||
|     quboInstance = {} | ||||
|      | ||||
|     chains = {} | ||||
|      | ||||
|     for clauseIndex in range(sat.getNumberOfClauses()): | ||||
|         clause = sat.getClause(clauseIndex) | ||||
|          | ||||
|         lit1 = clause[0] | ||||
|         lit2 = clause[1] | ||||
|         lit3 = clause[2] | ||||
|          | ||||
|         var1 = abs(lit1) | ||||
|         var2 = abs(lit2) | ||||
|         var3 = abs(lit3) | ||||
|          | ||||
|         sign1 = 1 if lit1 > 0 else -1 | ||||
|         sign2 = 1 if lit2 > 0 else -1 | ||||
|         sign3 = 1 if lit3 > 0 else -1 | ||||
|          | ||||
|         node_var1 = "x{}".format(var1) | ||||
|         node_var2 = "x{}".format(var2) | ||||
|         node_var3 = "x{}".format(var3) | ||||
|          | ||||
|         node_aux1 = "a{}_{}".format(clauseIndex, 1) | ||||
|         node_aux2 = "a{}_{}".format(clauseIndex, 2) | ||||
|         node_aux3 = "a{}_{}".format(clauseIndex, 3) | ||||
|         node_aux4 = "a{}_{}".format(clauseIndex, 4) | ||||
|          | ||||
|          | ||||
|         quboInstance[(node_var1, node_var1)] = 1 * sign1 | ||||
|         quboInstance[(node_var2, node_var2)] = 1 * sign2 | ||||
|         quboInstance[(node_var3, node_var3)] = 1 * sign3 | ||||
|         quboInstance[(node_aux1, node_aux1)] = -2 | ||||
|         quboInstance[(node_aux2, node_aux2)] = 1 | ||||
|         quboInstance[(node_aux3, node_aux3)] = -2 | ||||
|         quboInstance[(node_aux4, node_aux4)] = -2 | ||||
|          | ||||
|         quboInstance[(node_var1, node_var2)] = 1 * sign1 * sign2 | ||||
|         quboInstance[(node_var1, node_aux1)] = -2 * sign1 | ||||
|         quboInstance[(node_var2, node_aux1)] = -2 * sign2 | ||||
|         quboInstance[(node_aux1, node_aux2)] = -2 | ||||
|         quboInstance[(node_aux2, node_var3)] = 1 * sign3 | ||||
|          | ||||
|         quboInstance[(node_var3, node_aux3)] = -2 * sign3 | ||||
|         quboInstance[(node_aux2, node_aux3)] = -2 | ||||
|         quboInstance[(node_var3, node_aux4)] = -2 | ||||
|      | ||||
|     return quboInstance | ||||
|  | ||||
| # only 3sat | ||||
| def primitiveQUBO_3(sat): | ||||
|     quboInstance = {} | ||||
|      | ||||
|     chains = {} | ||||
|      | ||||
|     lits = {} | ||||
|     vars = {} | ||||
|      | ||||
|     n_clauses = sat.getNumberOfClauses() | ||||
|      | ||||
|     for clauseIndex in range(sat.getNumberOfClauses()): | ||||
|         clause = sat.getClause(clauseIndex) | ||||
|          | ||||
|         lit1 = clause[0] | ||||
|         lit2 = clause[1] | ||||
|         lit3 = clause[2] | ||||
|          | ||||
|         lits[lit1] = True | ||||
|         lits[lit2] = True | ||||
|         lits[lit3] = True | ||||
|          | ||||
|         var1 = abs(lit1) | ||||
|         var2 = abs(lit2) | ||||
|         var3 = abs(lit3) | ||||
|          | ||||
|         vars[var1] = True | ||||
|         vars[var2] = True | ||||
|         vars[var3] = True | ||||
|          | ||||
|         node_lit1 = "x{}".format(lit1) | ||||
|         node_lit2 = "x{}".format(lit2) | ||||
|         node_lit3 = "x{}".format(lit3) | ||||
|          | ||||
|         node_aux1 = "z{}_{}".format(clauseIndex, 1) | ||||
|         node_aux2 = "z{}_{}".format(clauseIndex, 2) | ||||
|         node_aux3 = "z{}_{}".format(clauseIndex, 3) | ||||
|         node_aux4 = "z{}_{}".format(clauseIndex, 4) | ||||
|          | ||||
|          | ||||
|         quboInstance[(node_lit1, node_lit1)] = 1 | ||||
|         quboInstance[(node_lit2, node_lit2)] = 1 | ||||
|         quboInstance[(node_lit3, node_lit3)] = 1 | ||||
|         quboInstance[(node_aux1, node_aux1)] = -2 | ||||
|         quboInstance[(node_aux2, node_aux2)] = 1 | ||||
|         quboInstance[(node_aux3, node_aux3)] = -2 | ||||
|         quboInstance[(node_aux4, node_aux4)] = -2 | ||||
|          | ||||
|         quboInstance[(node_lit1, node_lit2)] = 1 | ||||
|         quboInstance[(node_lit1, node_aux1)] = -2 | ||||
|         quboInstance[(node_lit2, node_aux1)] = -2 | ||||
|          | ||||
|         quboInstance[(node_aux1, node_aux2)] = -2 | ||||
|          | ||||
|         quboInstance[(node_aux2, node_lit3)] = 1 | ||||
|         quboInstance[(node_lit3, node_aux3)] = -2 | ||||
|         quboInstance[(node_aux2, node_aux3)] = -2 | ||||
|          | ||||
|         quboInstance[(node_aux3, node_aux4)] = -2 | ||||
|      | ||||
|     for var in vars.keys(): | ||||
|         if var in lits and -var in lits: | ||||
|             node_var = "x{}".format(var) | ||||
|             node_nvar = "x{}".format(-var) | ||||
|              | ||||
|             print((node_var, node_nvar)) | ||||
|             quboInstance[(node_var, node_nvar)] = 2 | ||||
|              | ||||
|     return quboInstance | ||||
|  | ||||
| def primitiveQUBO_4(sat): | ||||
|     quboInstance = {} | ||||
|      | ||||
|      | ||||
|     clauses_per_lit = {} | ||||
|      | ||||
|     lits = {} | ||||
|     vars = {} | ||||
|      | ||||
|     n_clauses = sat.getNumberOfClauses() | ||||
|      | ||||
|     master_z = "zm" | ||||
|      | ||||
|     #quboInstance[(master_z, master_z)] = -2 | ||||
|      | ||||
|     for clauseIndex in range(sat.getNumberOfClauses()): | ||||
|         clause = sat.getClause(clauseIndex) | ||||
|          | ||||
|         lit1 = clause[0] | ||||
|         lit2 = clause[1] | ||||
|         lit3 = clause[2] | ||||
|          | ||||
|         lits[lit1] = True | ||||
|         lits[lit2] = True | ||||
|         lits[lit3] = True | ||||
|          | ||||
|         sign1 = 1 if lit1 > 0 else -1 | ||||
|         sign2 = 1 if lit2 > 0 else -1 | ||||
|         sign3 = 1 if lit3 > 0 else -1 | ||||
|          | ||||
|         for lit in clause: | ||||
|             if lit in clauses_per_lit: | ||||
|                 clauses_per_lit[lit] += 1 | ||||
|             else: | ||||
|                 clauses_per_lit[lit] = 1 | ||||
|          | ||||
|         var1 = abs(lit1) | ||||
|         var2 = abs(lit2) | ||||
|         var3 = abs(lit3) | ||||
|          | ||||
|         vars[var1] = True | ||||
|         vars[var2] = True | ||||
|         vars[var3] = True | ||||
|          | ||||
|         node_lit1 = "x{}".format(lit1) | ||||
|         node_lit2 = "x{}".format(lit2) | ||||
|         node_lit3 = "x{}".format(lit3) | ||||
|          | ||||
|         node_aux = "z{}".format(clauseIndex) | ||||
|          | ||||
|         #quboInstance[(node_aux, node_aux)] = -2 | ||||
|         #quboInstance[(node_aux, master_z)] = -2 | ||||
|          | ||||
|         #quboInstance[(node_lit1, node_lit1)] = +1 #* sign3 | ||||
|         #quboInstance[(node_lit2, node_lit2)] = +1 #* sign3 | ||||
|         #quboInstance[(node_lit3, node_lit3)] = +1 #* sign3 | ||||
|          | ||||
|         quboInstance[(node_lit1, node_aux)] = -2 #* sign1 | ||||
|         quboInstance[(node_lit2, node_aux)] = -2 #* sign2 | ||||
|         quboInstance[(node_lit3, node_aux)] = -2 #* sign3 | ||||
|      | ||||
|     for lit in lits.keys(): | ||||
|         node_lit = "x{}".format(lit) | ||||
|          | ||||
|         #quboInstance[(node_lit, node_lit)] = 2 * clauses_per_lit[lit] | ||||
|          | ||||
|     for var in vars.keys(): | ||||
|         if var in lits and -var in lits: | ||||
|             node_var = "x{}".format(var) | ||||
|             node_nvar = "x{}".format(-var) | ||||
|              | ||||
|             max_clauses = max(clauses_per_lit[var], clauses_per_lit[-var]) | ||||
|             num_clauses = clauses_per_lit[var] + clauses_per_lit[-var] | ||||
|               | ||||
|             print((node_var, node_nvar)) | ||||
|             quboInstance[(node_var, node_nvar)] = 2 * num_clauses | ||||
|             #quboInstance[(node_var, node_nvar)] = 2# * num_clauses | ||||
|              | ||||
|     return quboInstance | ||||
|  | ||||
| def primitiveQUBO_5(sat): | ||||
|     quboInstance = {} | ||||
|      | ||||
|      | ||||
|     clauses_per_lit = {} | ||||
|      | ||||
|     lits = {} | ||||
|     vars = {} | ||||
|      | ||||
|     n_clauses = sat.getNumberOfClauses() | ||||
|      | ||||
|     master_z = "zm" | ||||
|      | ||||
|     #quboInstance[(master_z, master_z)] = -2 | ||||
|      | ||||
|     for clauseIndex in range(sat.getNumberOfClauses()): | ||||
|         clause = sat.getClause(clauseIndex) | ||||
|          | ||||
|         lit1 = clause[0] | ||||
|         lit2 = clause[1] | ||||
|         lit3 = clause[2] | ||||
|          | ||||
|         lits[lit1] = True | ||||
|         lits[lit2] = True | ||||
|         lits[lit3] = True | ||||
|          | ||||
|         for lit in clause: | ||||
|             if lit in clauses_per_lit: | ||||
|                 clauses_per_lit[lit] += 1 | ||||
|             else: | ||||
|                 clauses_per_lit[lit] = 1 | ||||
|          | ||||
|         var1 = abs(lit1) | ||||
|         var2 = abs(lit2) | ||||
|         var3 = abs(lit3) | ||||
|          | ||||
|         vars[var1] = True | ||||
|         vars[var2] = True | ||||
|         vars[var3] = True | ||||
|          | ||||
|         node_lit1 = "x{}".format(lit1) | ||||
|         node_lit2 = "x{}".format(lit2) | ||||
|         node_lit3 = "x{}".format(lit3) | ||||
|          | ||||
|         node_aux1 = "z{}_1".format(clauseIndex) | ||||
|         node_aux2 = "z{}_2".format(clauseIndex) | ||||
|          | ||||
|         quboInstance[(node_lit1, node_aux1)] = -2 | ||||
|         quboInstance[(node_lit2, node_aux1)] = -2 | ||||
|         quboInstance[(node_lit1, node_lit2)] = +2 | ||||
|          | ||||
|         quboInstance[(node_aux1, node_lit3)] = +2 | ||||
|         quboInstance[(node_lit3, node_aux2)] = -2 | ||||
|          | ||||
|  | ||||
|          | ||||
|     for var in vars.keys(): | ||||
|         if var in lits and -var in lits: | ||||
|             node_var = "x{}".format(var) | ||||
|             node_nvar = "x{}".format(-var) | ||||
|              | ||||
|             max_clauses = max(clauses_per_lit[var], clauses_per_lit[-var]) | ||||
|             num_clauses = clauses_per_lit[var] + clauses_per_lit[-var] | ||||
|               | ||||
|             #print((node_var, node_nvar)) | ||||
|             quboInstance[(node_var, node_nvar)] = 2 * max_clauses | ||||
|              | ||||
|     return quboInstance | ||||
|  | ||||
| def primitiveQUBO_6(sat): | ||||
|     quboInstance = {} | ||||
|      | ||||
|      | ||||
|     clauses_per_lit = {} | ||||
|      | ||||
|     lits = {} | ||||
|     vars = {} | ||||
|      | ||||
|     n_clauses = sat.getNumberOfClauses() | ||||
|      | ||||
|     master_z = "zm" | ||||
|      | ||||
|     #quboInstance[(master_z, master_z)] = -2 | ||||
|      | ||||
|     for clauseIndex in range(sat.getNumberOfClauses()): | ||||
|         clause = sat.getClause(clauseIndex) | ||||
|          | ||||
|         lit1 = clause[0] | ||||
|         lit2 = clause[1] | ||||
|         lit3 = clause[2] | ||||
|          | ||||
|         lits[lit1] = True | ||||
|         lits[lit2] = True | ||||
|         lits[lit3] = True | ||||
|          | ||||
|         for lit in clause: | ||||
|             if lit in clauses_per_lit: | ||||
|                 clauses_per_lit[lit] += 1 | ||||
|             else: | ||||
|                 clauses_per_lit[lit] = 1 | ||||
|          | ||||
|         var1 = abs(lit1) | ||||
|         var2 = abs(lit2) | ||||
|         var3 = abs(lit3) | ||||
|          | ||||
|         vars[var1] = True | ||||
|         vars[var2] = True | ||||
|         vars[var3] = True | ||||
|          | ||||
|         node_lit1 = "x{}".format(lit1) | ||||
|         node_lit2 = "x{}".format(lit2) | ||||
|         node_lit3 = "x{}".format(lit3) | ||||
|          | ||||
|         node_aux1 = "z{}_1".format(clauseIndex) | ||||
|         node_aux2 = "z{}_2".format(clauseIndex) | ||||
|         node_aux3 = "z{}_3".format(clauseIndex) | ||||
|         node_aux4 = "z{}_4".format(clauseIndex) | ||||
|          | ||||
|         quboInstance[(node_lit1, node_aux1)] = -2 | ||||
|         quboInstance[(node_lit2, node_aux2)] = -2 | ||||
|         quboInstance[(node_aux1, node_aux2)] = +2 | ||||
|          | ||||
|         quboInstance[(node_aux1, node_aux3)] = -2 | ||||
|         quboInstance[(node_aux2, node_aux3)] = -2 | ||||
|          | ||||
|         quboInstance[(node_aux1, node_aux1)] = +2 | ||||
|         quboInstance[(node_aux2, node_aux2)] = +2 | ||||
|          | ||||
|         quboInstance[(node_aux3, node_lit3)] = +2 | ||||
|         quboInstance[(node_lit3, node_aux4)] = -2 | ||||
|          | ||||
|  | ||||
|          | ||||
|     for var in vars.keys(): | ||||
|         if var in lits and -var in lits: | ||||
|             node_var = "x{}".format(var) | ||||
|             node_nvar = "x{}".format(-var) | ||||
|              | ||||
|             max_clauses = max(clauses_per_lit[var], clauses_per_lit[-var]) | ||||
|             num_clauses = clauses_per_lit[var] + clauses_per_lit[-var] | ||||
|               | ||||
|             #print((node_var, node_nvar)) | ||||
|             quboInstance[(node_var, node_nvar)] = 2 * max_clauses | ||||
|              | ||||
|     return quboInstance | ||||
|  | ||||
| def primitiveQUBO_7(sat): | ||||
|     quboInstance = {} | ||||
|      | ||||
|      | ||||
|     clauses_per_lit = {} | ||||
|      | ||||
|     lits = {} | ||||
|     vars = {} | ||||
|      | ||||
|     n_clauses = sat.getNumberOfClauses() | ||||
|      | ||||
|     master_z = "zm" | ||||
|      | ||||
|     #quboInstance[(master_z, master_z)] = -2 | ||||
|     direct_cupplers = {} | ||||
|      | ||||
|     for clauseIndex in range(sat.getNumberOfClauses()): | ||||
|         clause = sat.getClause(clauseIndex) | ||||
|          | ||||
|         lit1 = clause[0] | ||||
|         lit2 = clause[1] | ||||
|         lit3 = clause[2] | ||||
|          | ||||
|         lits[lit1] = True | ||||
|         lits[lit2] = True | ||||
|         lits[lit3] = True | ||||
|          | ||||
|         for lit in clause: | ||||
|             if lit in clauses_per_lit: | ||||
|                 clauses_per_lit[lit] += 1 | ||||
|             else: | ||||
|                 clauses_per_lit[lit] = 1 | ||||
|          | ||||
|         var1 = abs(lit1) | ||||
|         var2 = abs(lit2) | ||||
|         var3 = abs(lit3) | ||||
|          | ||||
|         vars[var1] = True | ||||
|         vars[var2] = True | ||||
|         vars[var3] = True | ||||
|          | ||||
|         node_lit1 = "x{}".format(lit1) | ||||
|         node_lit2 = "x{}".format(lit2) | ||||
|         node_lit3 = "x{}".format(lit3) | ||||
|          | ||||
|         node_aux1 = "z{}_1".format(clauseIndex) | ||||
|         node_aux2 = "z{}_2".format(clauseIndex) | ||||
|          | ||||
|         quboInstance[(node_lit1, node_aux1)] = -2 | ||||
|         quboInstance[(node_lit2, node_aux1)] = -2 | ||||
|         quboInstance[(node_lit1, node_lit2)] = +2 | ||||
|          | ||||
|         quboInstance[(node_aux1, node_lit3)] = +2 | ||||
|         quboInstance[(node_lit3, node_aux2)] = -2 | ||||
|          | ||||
|          | ||||
|          | ||||
|         if (node_lit1, node_lit2) in direct_cupplers: | ||||
|             direct_cupplers[(node_lit1, node_lit2)] += 1 | ||||
|         else: | ||||
|             direct_cupplers[(node_lit1, node_lit2)] = 1 | ||||
|          | ||||
|  | ||||
|          | ||||
|     for var in vars.keys(): | ||||
|         if var in lits and -var in lits: | ||||
|             node_var = "x{}".format(var) | ||||
|             node_nvar = "x{}".format(-var) | ||||
|              | ||||
|             max_clauses = max(clauses_per_lit[var], clauses_per_lit[-var]) | ||||
|             num_clauses = clauses_per_lit[var] + clauses_per_lit[-var] | ||||
|               | ||||
|             print((node_var, node_nvar)) | ||||
|             quboInstance[(node_var, node_nvar)] = 2 * max_clauses | ||||
|  | ||||
|              | ||||
|     for coupler, count in direct_cupplers.items():         | ||||
|         quboInstance[coupler] = count * 2 | ||||
|          | ||||
|              | ||||
|     return quboInstance | ||||
|  | ||||
| def primitiveQUBO_8(sat): | ||||
|     quboInstance = {} | ||||
|      | ||||
|      | ||||
|     clauses_per_lit = {} | ||||
|      | ||||
|     lits = {} | ||||
|     vars = {} | ||||
|      | ||||
|     n_clauses = sat.getNumberOfClauses() | ||||
|  | ||||
|     direct_cupplers = {} | ||||
|      | ||||
|     for clauseIndex in range(sat.getNumberOfClauses()): | ||||
|         clause = sorted(sat.getClause(clauseIndex)) | ||||
|          | ||||
|         if clause[2] < 0: | ||||
|             __add_3not_or_clause(quboInstance, clause, clauseIndex) | ||||
|         elif clause[1] < 0: | ||||
|             __add_2not_or_clause(quboInstance, clause, clauseIndex) | ||||
|         elif clause[0] < 0: | ||||
|             __add_1not_or_clause(quboInstance, clause, clauseIndex, direct_cupplers) | ||||
|         else: | ||||
|             __add_3_or_clause(quboInstance, clause, clauseIndex, direct_cupplers) | ||||
|  | ||||
|              | ||||
|     for coupler, count in direct_cupplers.items():         | ||||
|         quboInstance[coupler] = count * 2 | ||||
|          | ||||
|              | ||||
|     return quboInstance | ||||
|  | ||||
| def __add_3not_or_clause(quboInstance, clause, clause_index): | ||||
|     var1 = abs(clause[0]) | ||||
|     var2 = abs(clause[1]) | ||||
|     var3 = abs(clause[2]) | ||||
|      | ||||
|      | ||||
|     node_var1 = "x{}".format(var1) | ||||
|     node_var2 = "x{}".format(var2) | ||||
|     node_var3 = "x{}".format(var3) | ||||
|      | ||||
|     node_aux1 = "z{}_1".format(clause_index) | ||||
|     node_aux2 = "z{}_2".format(clause_index) | ||||
|     node_aux3 = "z{}_3".format(clause_index) | ||||
|      | ||||
|     quboInstance[(node_var1, node_aux1)] = +2 | ||||
|     quboInstance[(node_var2, node_aux2)] = +2 | ||||
|     quboInstance[(node_aux1, node_aux2)] = +2 | ||||
|      | ||||
|     quboInstance[(node_aux1, node_aux1)] = -2 | ||||
|     quboInstance[(node_aux2, node_aux2)] = -2 | ||||
|      | ||||
|     quboInstance[(node_var1, node_aux3)] = -2 | ||||
|     quboInstance[(node_var2, node_aux3)] = -2 | ||||
|     quboInstance[(node_var3, node_aux3)] = +2 | ||||
|     quboInstance[(node_aux3, node_aux3)] = +2 | ||||
|      | ||||
| def __add_2not_or_clause(quboInstance, clause, clause_index): | ||||
|     var1 = abs(clause[0]) | ||||
|     var2 = abs(clause[1]) | ||||
|     var3 = abs(clause[2]) | ||||
|      | ||||
|      | ||||
|     node_var1 = "x{}".format(var1) | ||||
|     node_var2 = "x{}".format(var2) | ||||
|     node_var3 = "x{}".format(var3) | ||||
|      | ||||
|     node_aux1 = "z{}_1".format(clause_index) | ||||
|     node_aux2 = "z{}_2".format(clause_index) | ||||
|     node_aux3 = "z{}_3".format(clause_index) | ||||
|     node_aux4 = "z{}_4".format(clause_index) | ||||
|     node_aux5 = "z{}_5".format(clause_index) | ||||
|      | ||||
|     quboInstance[(node_var1, node_aux1)] = +2 | ||||
|     quboInstance[(node_var2, node_aux2)] = +2 | ||||
|     quboInstance[(node_aux1, node_aux2)] = +2 | ||||
|      | ||||
|     quboInstance[(node_aux1, node_aux3)] = -2 | ||||
|     quboInstance[(node_aux2, node_aux3)] = -2 | ||||
|     quboInstance[(node_aux3, node_aux3)] = +2 | ||||
|      | ||||
|     quboInstance[(node_aux3, node_aux4)] = -2 | ||||
|     quboInstance[(node_var3, node_aux5)] = -2 | ||||
|     quboInstance[(node_aux4, node_aux5)] = +2 | ||||
|  | ||||
| def __add_1not_or_clause(quboInstance, clause, clause_index, direct_cupplers): | ||||
|     var1 = abs(clause[1]) | ||||
|     var2 = abs(clause[2]) | ||||
|     var3 = abs(clause[0]) | ||||
|      | ||||
|      | ||||
|     node_var1 = "x{}".format(var1) | ||||
|     node_var2 = "x{}".format(var2) | ||||
|     node_var3 = "x{}".format(var3) | ||||
|      | ||||
|     node_aux1 = "z{}_1".format(clause_index) | ||||
|     node_aux2 = "z{}_2".format(clause_index) | ||||
|      | ||||
|     quboInstance[(node_var1, node_var2)] = +2 | ||||
|     quboInstance[(node_var1, node_aux1)] = -2 | ||||
|     quboInstance[(node_var2, node_aux1)] = -2 | ||||
|      | ||||
|     quboInstance[(node_aux1, node_aux2)] = +2 | ||||
|     quboInstance[(node_var3, node_aux2)] = +2 | ||||
|      | ||||
|     quboInstance[(node_aux2, node_aux2)] = -2 | ||||
|      | ||||
|     if (node_var1, node_var2) in direct_cupplers: | ||||
|         direct_cupplers[(node_var1, node_var2)] += 1 | ||||
|     else: | ||||
|         direct_cupplers[(node_var1, node_var2)] = 1 | ||||
|          | ||||
| def __add_3_or_clause(quboInstance, clause, clause_index, direct_cupplers): | ||||
|     var1 = abs(clause[0]) | ||||
|     var2 = abs(clause[1]) | ||||
|     var3 = abs(clause[2]) | ||||
|      | ||||
|      | ||||
|     node_var1 = "x{}".format(var1) | ||||
|     node_var2 = "x{}".format(var2) | ||||
|     node_var3 = "x{}".format(var3) | ||||
|      | ||||
|     node_aux1 = "z{}_1".format(clause_index) | ||||
|     node_aux2 = "z{}_2".format(clause_index) | ||||
|      | ||||
|     quboInstance[(node_var1, node_var2)] = +2 | ||||
|     quboInstance[(node_var1, node_aux1)] = -2 | ||||
|     quboInstance[(node_var2, node_aux1)] = -2 | ||||
|      | ||||
|     quboInstance[(node_aux1, node_var3)] = +2 | ||||
|     quboInstance[(node_var3, node_aux2)] = -2 | ||||
|      | ||||
|     if (node_var1, node_var2) in direct_cupplers: | ||||
|         direct_cupplers[(node_var1, node_var2)] += 1 | ||||
|     else: | ||||
|         direct_cupplers[(node_var1, node_var2)] = 1 | ||||
|  | ||||
|      | ||||
| class QuboWriter: | ||||
|     def __init__(self, qubo): | ||||
|         self.__labelIndexDict = {} | ||||
|   | ||||
| @@ -25,3 +25,15 @@ def create_qpu_solver_nxgraph(solver): | ||||
|     graph.add_edges_from(solver.edges) | ||||
|      | ||||
|     return graph | ||||
|  | ||||
| def split_ising(ising): | ||||
|     h = {} | ||||
|     J = {} | ||||
|      | ||||
|     for coupler, energy in ising.items(): | ||||
|         if coupler[0] == coupler[1]: | ||||
|             h[coupler[0]] = energy | ||||
|         else: | ||||
|             J[coupler] = energy | ||||
|      | ||||
|     return h, J | ||||
|   | ||||
							
								
								
									
										144
									
								
								util/queries.py
									
									
									
									
									
								
							
							
						
						
									
										144
									
								
								util/queries.py
									
									
									
									
									
								
							| @@ -59,6 +59,56 @@ class Instance_scope_query: | ||||
|          | ||||
|         return sat, document["_id"] | ||||
|  | ||||
| class Qubo_ising_scope_query_raw: | ||||
|     def __init__(self, database, collection): | ||||
|         self.__database = database | ||||
|         self.__collection = collection | ||||
|         self.__query = None | ||||
|         self.__qubo_ids = [] | ||||
|         self.__qubo_id_iterator = None | ||||
|      | ||||
|     def query(self, scope): | ||||
|         self.__query = self.__database["experiment_scopes"].aggregate([ | ||||
|             { | ||||
|                 "$match": {"_id": scope} | ||||
|             }, | ||||
|             { | ||||
|                 "$unwind": "$instances" | ||||
|             }, | ||||
|             { | ||||
|                 "$lookup": | ||||
|                 { | ||||
|                     "from": self.__collection, | ||||
|                     "localField": "instances", | ||||
|                     "foreignField": "instance", | ||||
|                     "as": "qubo" | ||||
|                 } | ||||
|             }, | ||||
|             { | ||||
|                 "$unwind": "$qubo" | ||||
|             }, | ||||
|             { | ||||
|                 "$project": {"qubo_id": "$qubo._id"} | ||||
|             } | ||||
|         ]) | ||||
|          | ||||
|         self.__qubo_ids = [] | ||||
|         for doc in self.__query: | ||||
|             self.__qubo_ids.append(doc["qubo_id"]) | ||||
|          | ||||
|         self.__qubo_id_iterator = iter(self.__qubo_ids) | ||||
|              | ||||
|     def __len__(self): | ||||
|         return self.query.count_documents({}) | ||||
|              | ||||
|     def __iter__(self): | ||||
|         return self | ||||
|      | ||||
|     def __next__(self): | ||||
|         qubo_filter = {"_id": self.__qubo_id_iterator.__next__()} | ||||
|          | ||||
|         return self.__database[self.__collection].find_one(qubo_filter) | ||||
|  | ||||
| class WMIS_scope_query_raw: | ||||
|      | ||||
|     def __init__(self, database): | ||||
| @@ -115,12 +165,27 @@ class WMIS_scope_query (WMIS_scope_query_raw): | ||||
|         doc = super(WMIS_scope_query, self).__next__() | ||||
|          | ||||
|          | ||||
|         return read_raw_qubo(doc["qubo"]), doc["_id"] | ||||
|      | ||||
| class Ising_scope_query (Qubo_ising_scope_query_raw): | ||||
|      | ||||
|     def __next__(self): | ||||
|         doc = super(Ising_scope_query, self).__next__() | ||||
|          | ||||
|         return read_raw_ising(doc["qubo"]), doc["_id"] | ||||
|  | ||||
| class Qubo_scope_query (Qubo_ising_scope_query_raw): | ||||
|      | ||||
|     def __next__(self): | ||||
|         doc = super(Qubo_scope_query, self).__next__() | ||||
|          | ||||
|         return read_raw_qubo(doc["qubo"]), doc["_id"] | ||||
|      | ||||
| class WMIS_solver_input_scope_query_raw: | ||||
|      | ||||
|     def __init__(self, database): | ||||
|     def __init__(self, database, ising_qubo_collection): | ||||
|         self.__database = database | ||||
|         self.__ising_qubo_collection = ising_qubo_collection | ||||
|         self.__query = None | ||||
|         self.__ids = [] | ||||
|         self.__id_iterator = None; | ||||
| @@ -139,7 +204,7 @@ class WMIS_solver_input_scope_query_raw: | ||||
|             { | ||||
|                 "$lookup": | ||||
|                 { | ||||
|                     "from": "wmis_qubos", | ||||
|                     "from": self.__ising_qubo_collection, | ||||
|                     "localField": "instance_id",   | ||||
|                     "foreignField": "instance", | ||||
|                     "as": "wmis_qubo" | ||||
| @@ -230,7 +295,9 @@ class WMIS_solver_input_scope_query_raw: | ||||
|         doc["instance_id"] = ids["instance_id"] | ||||
|          | ||||
|         qubo_filter = {"_id": ids["wmis_qubo_id"]} | ||||
|         doc["wmis_qubo"] = self.__database["wmis_qubos"].find_one(qubo_filter) | ||||
|          | ||||
|         ising_qubo_collection = self.__database[self.__ising_qubo_collection] | ||||
|         doc["wmis_qubo"] = ising_qubo_collection.find_one(qubo_filter) | ||||
|          | ||||
|         embeddings_filter = {"_id": ids["embeddings_id"]} | ||||
|         doc["embeddings"] = self.__database["embeddings"].find_one(embeddings_filter) | ||||
| @@ -257,6 +324,26 @@ class WMIS_solver_input_scope_query (WMIS_solver_input_scope_query_raw): | ||||
|              | ||||
|         return data | ||||
|      | ||||
| class Ising_solver_input_scope_query (WMIS_solver_input_scope_query_raw): | ||||
|      | ||||
|     def __next__(self): | ||||
|         doc = super(Ising_solver_input_scope_query, self).__next__() | ||||
|          | ||||
|         data = {} | ||||
|          | ||||
|         data["instance_id"] = doc["instance_id"] | ||||
|          | ||||
|         data["qubo_id"] = doc["wmis_qubo"]["_id"] | ||||
|         data["qubo"] = read_raw_ising(doc["wmis_qubo"]["qubo"]) | ||||
|          | ||||
|         data["embeddings_id"] = doc["embeddings"]["_id"] | ||||
|          | ||||
|         data["embeddings"] = [] | ||||
|         for raw_emb in doc["embeddings"]["embeddings"]: | ||||
|             data["embeddings"].append(read_raw_ising_embedding(raw_emb)) | ||||
|              | ||||
|         return data | ||||
|      | ||||
| class WMIS_result_scope_query_raw: | ||||
|     def __init__(self, database): | ||||
|         self.__database = database | ||||
| @@ -395,6 +482,19 @@ def read_raw_qubo(raw_qubo): | ||||
|          | ||||
|     return qubo | ||||
|  | ||||
| def read_raw_ising(raw_ising): | ||||
|     ising = {} | ||||
|      | ||||
|     for entry in raw_ising: | ||||
|         energy = entry[1] | ||||
|         raw_coupler = entry[0] | ||||
|         node1 = raw_coupler[0] | ||||
|         node2 = raw_coupler[1] | ||||
|          | ||||
|         ising[(node1, node2)] = energy | ||||
|      | ||||
|     return ising | ||||
|  | ||||
| def read_raw_embedding(raw_embedding): | ||||
|     emb = {} | ||||
|      | ||||
| @@ -406,6 +506,17 @@ def read_raw_embedding(raw_embedding): | ||||
|          | ||||
|     return emb | ||||
|  | ||||
| def read_raw_ising_embedding(raw_embedding): | ||||
|     emb = {} | ||||
|      | ||||
|     if "embedding" in raw_embedding: | ||||
|         raw_embedding = raw_embedding["embedding"] | ||||
|          | ||||
|     for entry in raw_embedding: | ||||
|         emb[entry[0]] = entry[1] | ||||
|          | ||||
|     return emb | ||||
|  | ||||
| def read_raw_wmis_sample_set(raw_sample_set): | ||||
|     sample_set_data = raw_sample_set.copy() | ||||
|      | ||||
| @@ -416,6 +527,16 @@ def read_raw_wmis_sample_set(raw_sample_set): | ||||
|          | ||||
|     return dimod.SampleSet.from_serializable(sample_set_data) | ||||
|  | ||||
| def read_raw_primitive_ising_sample_set(raw_sample_set): | ||||
|     sample_set_data = raw_sample_set.copy() | ||||
|      | ||||
|     sample_set_data["variable_labels"] = [] | ||||
|      | ||||
|     for label in raw_sample_set["variable_labels"]: | ||||
|         sample_set_data["variable_labels"].append("".join(label)) | ||||
|          | ||||
|     return dimod.SampleSet.from_serializable(sample_set_data) | ||||
|  | ||||
| def get_instance_by_id(collection, id): | ||||
|     doc = collection.find_one({"_id": bson.ObjectId(id)}) | ||||
|      | ||||
| @@ -426,3 +547,20 @@ def get_instance_by_id(collection, id): | ||||
|          | ||||
|     return sat | ||||
|  | ||||
| def extract_primitive_ising_model(sample): | ||||
|     variable_bindings = {} | ||||
|      | ||||
|     for node, energy in sample.items(): | ||||
|         if node[0] == "x": | ||||
|             var = int(node[1:]) | ||||
|             variable_bindings[var] = True if energy > 0 else False | ||||
|              | ||||
|     model = [True for i in range(len(variable_bindings))] | ||||
|      | ||||
|     for var, binding in variable_bindings.items(): | ||||
|         model[var - 1] = binding | ||||
|          | ||||
|     return model | ||||
|      | ||||
|      | ||||
|      | ||||
|   | ||||
| @@ -186,7 +186,43 @@ def create_wmis_qubos_for_scope(db, scope): | ||||
|     for instance, instance_id in instances: | ||||
|         qubo = SAT2QUBO.WMISdictQUBO(instance) | ||||
|          | ||||
|         write_qubo_to_pool_db(db["wmis_qubos"], qubo, instance_id) | ||||
|         write_qubo_to_pool_db(db["wmis_qubos_2"], qubo, instance_id) | ||||
|          | ||||
| def create_wmis_2_qubos_for_scope(db, scope): | ||||
|     instances = queries.Instance_scope_query(db) | ||||
|     instances.query(scope) | ||||
|      | ||||
|     for instance, instance_id in instances: | ||||
|         qubo = SAT2QUBO.WMISdictQUBO_2(instance) | ||||
|          | ||||
|         write_qubo_to_pool_db(db["wmis_2_qubos"], qubo, instance_id) | ||||
|  | ||||
| def create_primitive_isings_for_scope_2(db, scope): | ||||
|     instances = queries.Instance_scope_query(db) | ||||
|     instances.query(scope) | ||||
|      | ||||
|     for instance, instance_id in instances: | ||||
|         ising = SAT2QUBO.primitiveQUBO_2(instance) | ||||
|          | ||||
|         write_qubo_to_pool_db(db["primitive_isings_2"], ising, instance_id) | ||||
|          | ||||
| def create_primitive_qubo_for_scope_5(db, scope): | ||||
|     instances = queries.Instance_scope_query(db) | ||||
|     instances.query(scope) | ||||
|      | ||||
|     for instance, instance_id in tqdm(instances): | ||||
|         ising = SAT2QUBO.primitiveQUBO_5(instance) | ||||
|          | ||||
|         write_qubo_to_pool_db(db["primitive_isings_5"], ising, instance_id) | ||||
|          | ||||
| def create_primitive_qubo_for_scope_8(db, scope): | ||||
|     instances = queries.Instance_scope_query(db) | ||||
|     instances.query(scope) | ||||
|      | ||||
|     for instance, instance_id in tqdm(instances): | ||||
|         ising = SAT2QUBO.primitiveQUBO_8(instance) | ||||
|          | ||||
|         write_qubo_to_pool_db(db["primitive_isings_8"], ising, instance_id) | ||||
|      | ||||
| def __qubo_to_JSON(qubo): | ||||
|     quboJSON = [] | ||||
| @@ -306,6 +342,53 @@ def find_wmis_embeddings_for_scope(db, scope, solver_graph): | ||||
|                                                    percentage)) | ||||
|     print("{} new embeddigns found".format(new_embeddings_found)) | ||||
|      | ||||
| def find_embeddings_for_scope(db, solver_graph, qubo_ising_query): | ||||
|     solver_graph_id = write_solver_graph_to_pool_db(db["solver_graphs"],  | ||||
|                                                     solver_graph) | ||||
|      | ||||
|     new_embeddings_found = 0 | ||||
|     already_found = 0 | ||||
|     total_count = 0 | ||||
|     for qubo, qubo_id in tqdm(qubo_ising_query): | ||||
|         total_count += 1 | ||||
|          | ||||
|         max_no_improvement = 10 | ||||
|         for i in range(5): | ||||
|             if __embedding_entry_exists(db["embeddings"], qubo_id, solver_graph_id): | ||||
|                 if i == 0: | ||||
|                     already_found += 1 | ||||
|                 break; | ||||
|             else:  | ||||
|                 nx_qubo = graph.qubo_to_nx_graph(qubo) | ||||
|                  | ||||
|                 seed = random.randint(0, sys.maxsize) | ||||
|                  | ||||
|                 emb = minorminer.find_embedding(nx_qubo.edges(), | ||||
|                                                 solver_graph.edges(), | ||||
|                                                 return_overlap=True, | ||||
|                                                 max_no_improvement=max_no_improvement, | ||||
|                                                 random_seed=seed) | ||||
|                  | ||||
|                 if emb[1] == 1: | ||||
|                     write_wmis_embedding_to_pool_db(db["embeddings"], | ||||
|                                                     qubo_id, | ||||
|                                                     solver_graph_id, | ||||
|                                                     seed, | ||||
|                                                     emb[0]) | ||||
|                     new_embeddings_found += 1 | ||||
|                      | ||||
|             max_no_improvement *= 1.5 | ||||
|      | ||||
|     percentage = 0 | ||||
|      | ||||
|     if total_count > 0: | ||||
|         percentage = round(((new_embeddings_found + already_found) / total_count) * 100) | ||||
|      | ||||
|     print("found {} of {} embeddigns ({}%)".format(new_embeddings_found + already_found, | ||||
|                                                    total_count, | ||||
|                                                    percentage)) | ||||
|     print("{} new embeddigns found".format(new_embeddings_found)) | ||||
|  | ||||
| def save_sample_set(collection, result, solver_input, emb_list_index, run): | ||||
|     doc = {} | ||||
|      | ||||
|   | ||||
		Reference in New Issue
	
	Block a user