def generate(config, formats):
for format in formats:
for scenario in config["scenarios"]:
# dict only has one item
for (scenario_name, _) in scenario.items():
pass
args = [""]
if format in config["generator_optional_arguments"]:
for optional_argument in config["generator_optional_arguments"][format]:
args.append("-" + optional_argument)
for arg in args:
path = "./hu.bme.mit.trainbenchmark.generator.{FORMAT}/".format(FORMAT=format)
util.set_working_directory(path)
target = util.get_generator_jar(format)
for size in config["sizes"]:
cmd = flatten(["java",
config["java_opts"],
"-jar", target,
"-scenario", scenario_name,
"-size", str(size),
arg])
try:
subprocess.check_call(cmd)
except subprocess.CalledProcessError:
print("An error occured during model generation, skipping larger sizes for this scenario/format.")
break
util.set_working_directory("..")
def generate(conf):
"""Generates the models.
"""
target = util.get_generator_jar()
for size in conf.sizes:
subprocess.check_call(
flatten(["java", conf.vmargs, "-jar", target, "-size",
str(size)]))
def generate(formats, scenarios, sizes):
"""
Generates the models after the configurations parameter.
"""
for scenario in scenarios:
for format in formats:
path = "./hu.bme.mit.trainbenchmark.generator.{FORMAT}/".format(FORMAT=format)
util.set_working_directory(path)
target = util.get_generator_jar(format)
for size in sizes:
print("Generate model: <format: " + format +
", scenario: " + scenario +
", size: " + str(size) + ">")
subprocess.call(["java", "-Xmx" + java_xmx,
"-jar", target,
"-scenario", scenario,
"-size", str(size)])
util.set_working_directory("..")
def generate(formats, scenarios, sizes):
"""
Generates the models after the configurations parameter.
"""
for scenario in scenarios:
for format in formats:
path = "./hu.bme.mit.trainbenchmark.generator.{FORMAT}/".format(
FORMAT=format)
util.set_working_directory(path)
target = util.get_generator_jar(format)
for size in sizes:
print("Generate model: <format: " + format + ", scenario: " +
scenario + ", size: " + str(size) + ">")
subprocess.call([
"java", "-Xmx" + java_xmx, "-jar", target, "-scenario",
scenario, "-size",
str(size)
])
util.set_working_directory("..")
import util
if __name__ == "__main__":
with open("config/config.yml", 'r') as stream:
config = yaml.load(stream)
formats = ["emf", "graph", "rdf", "sql"]
for format in formats:
for query in config["queries"]:
args = [""]
if format in config["generator_optional_arguments"]:
for optional_argument in config["generator_optional_arguments"][format]:
args.append("-" + optional_argument)
for arg in args:
path = "./hu.bme.mit.trainbenchmark.generator.{FORMAT}/".format(FORMAT=format)
util.set_working_directory(path)
target = util.get_generator_jar(format)
cmd = ["java", "-Xmx" + config["java_opts"]["xmx"],
"-jar", target,
"-scenario", "Minimal",
"-query", query,
arg]
try:
subprocess.check_call(cmd)
except subprocess.CalledProcessError:
print("An error occured during model generation.")
util.set_working_directory("..")
def generate(conf):
"""Generates the models.
"""
target = util.get_generator_jar()
for size in conf.sizes:
subprocess.check_call(flatten(["java", conf.vmargs, "-jar", target, "-size", str(size)]))