mirror of
https://github.com/Brandon-Rozek/matmod.git
synced 2025-07-29 20:52:01 +00:00
183 lines
6.2 KiB
Python
Executable file
183 lines
6.2 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
|
|
# NOTE: Perhaps we should use process_cpu_count but that's not available to all Python versions
|
|
from os import cpu_count
|
|
from typing import Dict, Iterator, Optional, Tuple
|
|
from queue import Empty as QueueEmpty
|
|
import argparse
|
|
import multiprocessing as mp
|
|
|
|
from logic import Conjunction, Disjunction, Negation, Implication, Operation
|
|
from model import Model, ModelFunction
|
|
from parse_magic import SourceFile, parse_matrices
|
|
from vsp import has_vsp
|
|
|
|
def restructure_solutions(solutions: Iterator[Tuple[Model, Dict[Operation, ModelFunction]]], args) -> \
|
|
Iterator[Tuple[Model, ModelFunction, Optional[ModelFunction], Optional[ModelFunction], Optional[ModelFunction]]]:
|
|
"""
|
|
When subprocess gets spawned, the logical operations will
|
|
have a different memory address than what's expected in interpretation.
|
|
Therefore, we need to pass the model functions directly instead.
|
|
|
|
While we're at it, filter out models until we get to --skip-to
|
|
if applicable.
|
|
"""
|
|
start_processing = args.get("skip_to") is None
|
|
for model, interpretation in solutions:
|
|
# If skip_to is defined, then don't process models
|
|
# until then.
|
|
if not start_processing and model.name == args.get("skip_to"):
|
|
start_processing = True
|
|
if not start_processing:
|
|
continue
|
|
impfunction = interpretation[Implication]
|
|
mconjunction = interpretation.get(Conjunction)
|
|
mdisjunction = interpretation.get(Disjunction)
|
|
mnegation = interpretation.get(Negation)
|
|
yield (model, impfunction, mconjunction, mdisjunction, mnegation)
|
|
|
|
def has_vsp_plus_model(model, impfunction, mconjunction, mdisjunction, mnegation):
|
|
"""
|
|
Wrapper which also stores the models along with its vsp result
|
|
"""
|
|
vsp_result = has_vsp(model, impfunction, mconjunction, mdisjunction, mnegation)
|
|
return (model, vsp_result)
|
|
|
|
def worker_vsp(task_queue, result_queue):
|
|
"""
|
|
Worker process which processes models from the task
|
|
queue and adds the result to the result_queue.
|
|
|
|
Adds the sentinal value None when exception occurs and when there's
|
|
no more to process.
|
|
"""
|
|
try:
|
|
while True:
|
|
task = task_queue.get()
|
|
# If sentinal value, break
|
|
if task is None:
|
|
break
|
|
(model, impfunction, mconjunction, mdisjunction, mnegation) = task
|
|
result = has_vsp_plus_model(model, impfunction, mconjunction, mdisjunction, mnegation)
|
|
result_queue.put(result)
|
|
finally:
|
|
# Either an exception occured or the worker finished
|
|
# Push sentinal value
|
|
result_queue.put(None)
|
|
|
|
def worker_parser(data_file_path, num_sentinal_values, task_queue):
|
|
"""
|
|
Function which parses the MaGIC file
|
|
and adds models to the task_queue.
|
|
|
|
Intended to be deployed with a dedicated process.
|
|
"""
|
|
try:
|
|
data_file = open(data_file_path, "r")
|
|
solutions = parse_matrices(SourceFile(data_file))
|
|
solutions = restructure_solutions(solutions, args)
|
|
|
|
while True:
|
|
try:
|
|
item = next(solutions)
|
|
task_queue.put(item)
|
|
except StopIteration:
|
|
break
|
|
finally:
|
|
data_file.close()
|
|
for _ in range(num_sentinal_values):
|
|
task_queue.put(None)
|
|
|
|
|
|
|
|
|
|
if __name__ == "__main__":
|
|
parser = argparse.ArgumentParser(description="VSP Checker")
|
|
parser.add_argument("--verbose", action='store_true', help="Print out all parsed matrices")
|
|
parser.add_argument("-i", type=str, help="Path to MaGIC ugly data file")
|
|
parser.add_argument("-c", type=int, help="Number of CPUs to use. Default: MAX - 2.")
|
|
parser.add_argument("--skip-to", type=str, help="Skip until a model name is found and process from then onwards.")
|
|
args = vars(parser.parse_args())
|
|
|
|
data_file_path = args.get("i")
|
|
if data_file_path is None:
|
|
data_file_path = input("Path to MaGIC Ugly Data File: ")
|
|
|
|
|
|
num_cpu = args.get("c")
|
|
if num_cpu is None:
|
|
num_cpu = max(cpu_count() - 2, 1)
|
|
|
|
# Set up parallel verification
|
|
num_tested = 0
|
|
num_has_vsp = 0
|
|
num_workers = max(num_cpu - 1, 1)
|
|
|
|
# Create queues
|
|
task_queue = mp.Queue(maxsize=1000)
|
|
result_queue = mp.Queue()
|
|
|
|
# Create dedicated process to parse the MaGIC file
|
|
process_parser = mp.Process(target=worker_parser, args=(data_file_path, num_workers, task_queue))
|
|
process_parser.start()
|
|
|
|
# Create dedicated processes which check VSP
|
|
process_workers = []
|
|
for _ in range(num_workers):
|
|
p = mp.Process(target=worker_vsp, args=(task_queue, result_queue))
|
|
process_workers.append(p)
|
|
p.start()
|
|
|
|
|
|
# Check results and add new tasks until finished
|
|
result_sentinal_count = 0
|
|
while True:
|
|
|
|
# Read a result
|
|
try:
|
|
result = result_queue.get(True, 60)
|
|
except QueueEmpty:
|
|
if all((not p.is_alive() for p in process_workers)):
|
|
# All workers finished without us receiving all the
|
|
# sentinal values.
|
|
break
|
|
|
|
task_queue_size = 0
|
|
try:
|
|
task_queue_size = task_queue.qsize()
|
|
except NotImplementedError:
|
|
# MacOS doesn't implement this
|
|
pass
|
|
|
|
if task_queue_size == 0 and not process_parser.is_alive():
|
|
# For Linux/Windows this means that the process_parser
|
|
# died before sending the sentinal values.
|
|
# For Mac, this doesn't guarentee anything but might
|
|
# as well push more sentinal values.
|
|
for _ in range(num_workers):
|
|
task_queue.put(None)
|
|
|
|
|
|
# When we receive None, it means a child process has finished
|
|
if result is None:
|
|
result_sentinal_count += 1
|
|
# If all workers have finished break
|
|
if result_sentinal_count == len(process_workers):
|
|
break
|
|
continue
|
|
|
|
# Process result
|
|
model, vsp_result = result
|
|
print(vsp_result)
|
|
num_tested += 1
|
|
|
|
if vsp_result.has_vsp:
|
|
print(model)
|
|
|
|
if vsp_result.has_vsp:
|
|
num_has_vsp += 1
|
|
|
|
|
|
print(f"Tested {num_tested} models, {num_has_vsp} of which satisfy VSP")
|
|
|
|
|