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# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from contextlib import suppress
import os
import sys
from typing import Any, Dict
import numpy as np
from utils import create_if_not_exists
from utils.conf import base_path
from utils.metrics import backward_transfer, forward_transfer, forgetting
useless_args = ['dataset', 'tensorboard', 'validation', 'model',
'csv_log', 'notes', 'load_best_args']
def print_mean_accuracy(mean_acc: np.ndarray, task_number: int,
setting: str) -> None:
"""
Prints the mean accuracy on stderr.
:param mean_acc: mean accuracy value
:param task_number: task index
:param setting: the setting of the benchmark
"""
if setting == 'domain-il':
mean_acc, _ = mean_acc
print('\nAccuracy for {} task(s): {} %'.format(
task_number, round(mean_acc, 2)), file=sys.stderr)
else:
mean_acc_class_il, mean_acc_task_il = mean_acc
print('\nAccuracy for {} task(s): \t [Class-IL]: {} %'
' \t [Task-IL]: {} %\n'.format(task_number, round(
mean_acc_class_il, 2), round(mean_acc_task_il, 2)), file=sys.stderr)
class Logger:
def __init__(self, setting_str: str, dataset_str: str,
model_str: str) -> None:
self.accs = []
self.fullaccs = []
if setting_str == 'class-il':
self.accs_mask_classes = []
self.fullaccs_mask_classes = []
self.setting = setting_str
self.dataset = dataset_str
self.model = model_str
self.fwt = None
self.fwt_mask_classes = None
self.bwt = None
self.bwt_mask_classes = None
self.forgetting = None
self.forgetting_mask_classes = None
def dump(self):
dic = {
'accs': self.accs,
'fullaccs': self.fullaccs,
'fwt': self.fwt,
'bwt': self.bwt,
'forgetting': self.forgetting,
'fwt_mask_classes': self.fwt_mask_classes,
'bwt_mask_classes': self.bwt_mask_classes,
'forgetting_mask_classes': self.forgetting_mask_classes,
}
if self.setting == 'class-il':
dic['accs_mask_classes'] = self.accs_mask_classes
dic['fullaccs_mask_classes'] = self.fullaccs_mask_classes
return dic
def load(self, dic):
self.accs = dic['accs']
self.fullaccs = dic['fullaccs']
self.fwt = dic['fwt']
self.bwt = dic['bwt']
self.forgetting = dic['forgetting']
self.fwt_mask_classes = dic['fwt_mask_classes']
self.bwt_mask_classes = dic['bwt_mask_classes']
self.forgetting_mask_classes = dic['forgetting_mask_classes']
if self.setting == 'class-il':
self.accs_mask_classes = dic['accs_mask_classes']
self.fullaccs_mask_classes = dic['fullaccs_mask_classes']
def rewind(self, num):
self.accs = self.accs[:-num]
self.fullaccs = self.fullaccs[:-num]
with suppress(BaseException):
self.fwt = self.fwt[:-num]
self.bwt = self.bwt[:-num]
self.forgetting = self.forgetting[:-num]
self.fwt_mask_classes = self.fwt_mask_classes[:-num]
self.bwt_mask_classes = self.bwt_mask_classes[:-num]
self.forgetting_mask_classes = self.forgetting_mask_classes[:-num]
if self.setting == 'class-il':
self.accs_mask_classes = self.accs_mask_classes[:-num]
self.fullaccs_mask_classes = self.fullaccs_mask_classes[:-num]
def add_fwt(self, results, accs, results_mask_classes, accs_mask_classes):
self.fwt = forward_transfer(results, accs)
if self.setting == 'class-il':
self.fwt_mask_classes = forward_transfer(results_mask_classes, accs_mask_classes)
def add_bwt(self, results, results_mask_classes):
self.bwt = backward_transfer(results)
self.bwt_mask_classes = backward_transfer(results_mask_classes)
def add_forgetting(self, results, results_mask_classes):
self.forgetting = forgetting(results)
self.forgetting_mask_classes = forgetting(results_mask_classes)
def log(self, mean_acc: np.ndarray) -> None:
"""
Logs a mean accuracy value.
:param mean_acc: mean accuracy value
"""
if self.setting == 'general-continual':
self.accs.append(mean_acc)
elif self.setting == 'domain-il':
mean_acc, _ = mean_acc
self.accs.append(mean_acc)
else:
mean_acc_class_il, mean_acc_task_il = mean_acc
self.accs.append(mean_acc_class_il)
self.accs_mask_classes.append(mean_acc_task_il)
def log_fullacc(self, accs):
if self.setting == 'class-il':
acc_class_il, acc_task_il = accs
self.fullaccs.append(acc_class_il)
self.fullaccs_mask_classes.append(acc_task_il)
def write(self, args: Dict[str, Any]) -> None:
"""
writes out the logged value along with its arguments.
:param args: the namespace of the current experiment
"""
wrargs = args.copy()
for i, acc in enumerate(self.accs):
wrargs['accmean_task' + str(i + 1)] = acc
for i, fa in enumerate(self.fullaccs):
for j, acc in enumerate(fa):
wrargs['accuracy_' + str(j + 1) + '_task' + str(i + 1)] = acc
wrargs['forward_transfer'] = self.fwt
wrargs['backward_transfer'] = self.bwt
wrargs['forgetting'] = self.forgetting
target_folder = base_path() + "results/"
create_if_not_exists(target_folder + self.setting)
create_if_not_exists(target_folder + self.setting +
"/" + self.dataset)
create_if_not_exists(target_folder + self.setting +
"/" + self.dataset + "/" + self.model)
path = target_folder + self.setting + "/" + self.dataset\
+ "/" + self.model + "/logs.pyd"
with open(path, 'a') as f:
f.write(str(wrargs) + '\n')
if self.setting == 'class-il':
create_if_not_exists(os.path.join(*[target_folder, "task-il/", self.dataset]))
create_if_not_exists(target_folder + "task-il/"
+ self.dataset + "/" + self.model)
for i, acc in enumerate(self.accs_mask_classes):
wrargs['accmean_task' + str(i + 1)] = acc
for i, fa in enumerate(self.fullaccs_mask_classes):
for j, acc in enumerate(fa):
wrargs['accuracy_' + str(j + 1) + '_task' + str(i + 1)] = acc
wrargs['forward_transfer'] = self.fwt_mask_classes
wrargs['backward_transfer'] = self.bwt_mask_classes
wrargs['forgetting'] = self.forgetting_mask_classes
path = target_folder + "task-il" + "/" + self.dataset + "/"\
+ self.model + "/logs.pyd"
with open(path, 'a') as f:
f.write(str(wrargs) + '\n')
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