def __init__(self, train_len, trial):
self.train_len = train_len
experiment_dir = paths.experiment(constants.EXPERIMENT_PATH,
'rand_prunable')
train_len_dir = os.path.join(experiment_dir,
'train{}'.format(train_len))
self.output_dir = paths.trial(train_len_dir, trial)
def __init__(self, trial): self.output_dir = paths.trial(paths.experiment(constants.EXPERIMENT_PATH, 'same_init'), trial)
def trial(trial_name): return paths.trial(EXPERIMENT_PATH, trial_name)
print(text.format(*counters))
else:
for trial in range(len(self.counters[self.print_order[0]])):
print('Trial {}'.format(trial + 1))
for text in self.print_order:
print(text.format(*self.counters[text][trial]))
avg_printer = AveragePrinter(len(sys.argv) > 2 and sys.argv[2] == '-a')
exp_path = paths.experiment(constants.EXPERIMENT_PATH, sys.argv[1])
trial_nums = [
int(re.findall('\d+', trial_dir)[0]) for trial_dir in os.listdir(exp_path)
]
print("Found {} trials".format(max(trial_nums)))
for trial in range(1, max(trial_nums) + 1):
trial_path = paths.trial(exp_path, trial)
if not os.path.isdir(trial_path):
print("Warning: skipping trial {}, does not exist".format(trial))
continue
first_run_path = paths.run(trial_path, 0)
first_run_train_acc = float(
subprocess.check_output(
['tail', '-n', '1',
paths.log(first_run_path, 'train')]).strip().split(',')[-1])
avg_printer.do_print(trial, '\tFirst run train acc: {}',
[first_run_train_acc])
first_run_test_acc = float(
subprocess.check_output(
['tail', '-n', '1',
paths.log(first_run_path, 'test')]).strip().split(',')[-1])
def __init__(self, trial):
self.output_dir = paths.trial(
paths.experiment(constants.EXPERIMENT_PATH,
'half_less_aggressive'), trial)
def __init__(self, trial):
self.output_dir = paths.trial(constants.EXPERIMENT_PATH, trial,
'pruned_neurons')
def __init__(self, trial): self.output_dir = paths.trial(paths.experiment(constants.EXPERIMENT_PATH, 'big_two_layer'), trial)
