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():