def testmain(self):
# Same specification as before
generation_specification = {"seed": [1, 2, 3, 4, 5, 6, 7, 8], "num_calls": [[10, 20, 30]]}
specifications = SpecificationGenerator().generate(generation_specification)
output_generation_specification = {"seed": [1, 2, 3, 4, 5, 6, 7, 8], "num_calls": [10, 20, 30]}
output_specifications = SpecificationGenerator().generate(output_generation_specification)
name = "test"
# This time we will run them all in parallel
runner = ExperimentRunner()
expr = SimpleExperiment()
runner.run(name, specifications, expr, specification_runner=MultiprocessingRunner(),
use_dashboard=True, propagate_exceptions=True,context_type="spawn")
log_base = os.path.join("experiment_runs",name,"logs")
for root, dirs, files in os.walk(log_base):
for file in files:
with open(os.path.join(root,file),"r") as f:
lines = f.readlines()
self.assertNotEqual([],lines)
for result in experiment_iterator(name):
if result["result"] != []:
output_specifications.remove(result["specification"])
self.assertEqual([],output_specifications)
def testmain(self):
# Same specification as before
generation_specification = {
"seed": [1, 2, 3, 4, 5, 6, 7, 8],
"num_calls": [[10, 20, 30]]
}
specifications = SpecificationGenerator().generate(
generation_specification)
output_generation_specification = {
"seed": [1, 2, 3, 4, 5, 6, 7, 8],
"num_calls": [10, 20, 30]
}
output_specifications = SpecificationGenerator().generate(
output_generation_specification)
name = "test"
# This time we will run them all in parallel
runner = ExperimentRunner()
runner.run(name,
specifications,
SimpleExperiment(),
specification_runner=MultiprocessingRunner(),
use_dashboard=False,
propagate_exceptions=True)
for result in experiment_iterator(name):
if result["result"] != []:
output_specifications.remove(result["specification"])
self.assertEqual([], output_specifications)
print(s)
raise Exception()
def rename_title(s):
if "fn" in s:
return "Dynamic Function"
elif "163636" in s:
return "Validation Environment 1"
else:
return "Validation Environment 2"
df = pandas.DataFrame(columns=[x_name, y_name, hue_var_name, graph_split_name])
df = df.astype({y_name: 'float64', x_name: 'float64', hue_var_name: 'str'})
for experiment in experiment_iterator(experiment_name1):
d = dict()
if experiment["specification"]["rollout_allocation_method"] in [
"sr", "ugapeb"
]:
continue
if experiment['result'] != []:
d[x_name] = experiment[x_var[0]][x_var[1]]
d[y_name] = np.sum(experiment["result"]["Ys"][-1])
d[hue_var_name] = rename_arm_selector(
str(experiment[hue_var[0]][hue_var[1]]))
d[graph_split_name] = experiment[graph_split_var[0]][
graph_split_var[1]]
df = df.append(d, True)
for split_var in df[graph_split_name].unique():