def print_test_info(cfg, step, metrics):
"""Print validate information on the screen.
Inputs:
cfg: training options
step: a list includes --> [per_step, total_step]
metrics: the current batch testing metrics
"""
report = info = message = ""
if step[0] == 0:
equal_left, equal_right = cal_equal(15)
info += "\n" + "=" * equal_left + " Start Testing " + "=" * equal_right
print(info)
if cfg.opts.save_test_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR, 'Test_log.txt'),
info,
mode='w',
show=False)
progress_bar(step[0], step[1], display=False)
if cfg.opts.test_label != 'None':
if step[0] + 1 >= step[1]:
report, message = prepare_metrics(report, message, metrics)
if cfg.opts.save_test_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR,
'Test_log.txt'),
message + "\n" + report,
mode='a',
show=False)
def print_val_info(val_flag, cfg, step, metrics):
"""Print validate information on the screen.
Inputs:
val_flag: whether print the information or not(bool)
cfg: training options
step: a list includes --> [per_step, total_step]
metrics: the current batch validating metrics
"""
report = info = message = ""
if val_flag:
if step[0] - 1 == 0:
info += ">>> Validate on the val dataset ..."
print(info)
if cfg.opts.save_train_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR,
'Train_Log.txt'),
info,
mode='a',
show=False)
progress_bar(step[0] - 1, step[1], display=False)
if step[0] >= step[1]:
report, message = prepare_metrics(report, message, metrics)
if cfg.opts.save_train_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR,
'Train_Log.txt'),
message + "\n" + report,
mode='a',
show=False)
def display_options(self, args, display_path, display_param):
"""Save and Display parameter options or path options"""
path_message = self.path_message()
param_message = self.param_message(args)
if display_path:
print(path_message)
if display_param:
print(param_message)
file_name = self.mode + '_Options.txt'
wrote_txt_file(os.path.join(self.CHECKPOINT_DIR, file_name),
path_message + '\n' + param_message)
def print_train_info(val_flag, cfg, epoch, step, loss, lr, metrics):
"""Print training epoch, step, loss, lr, and auc information on the screen.
Inputs:
val_flag: whether print the val info according to the epoch(bool)
cfg: training options
epoch: a list includes --> [start_epoch, per_epoch, total_epoch]
step: a list includes --> [per_step, total_step]
loss: a float includes --> train loss value
lr: the current learning rate
metrics: the current batch training metrics
"""
message = ""
# print '==== Start training ===='
if epoch[1] == 1 and step[0] == 1:
equal_left, equal_right = cal_equal(16)
message += "\n" + "=" * equal_left + " Start Training " + "=" * equal_right
# print '==== Start training ===='
elif epoch[1] == epoch[0] and epoch[1] != 1 and step[0] == 1:
equal_left, equal_right = cal_equal(19)
message += "\n" + "=" * equal_left + " Continue Training " + "=" * equal_right
# print '---- Epoch [1/10] ----'
if (epoch[1] % cfg.opts.print_epoch == 0 or epoch[1] == epoch[0]
or epoch[1] == epoch[2]) and step[0] - 1 == 0:
val_flag = True
info = " Epoch [{}/{}] ".format(epoch[1], epoch[2])
equal_left, equal_right = cal_equal(len(info))
message += "\n" + "-" * equal_left + info + "-" * equal_right
message += "\n>>> Learning rate {:.7f}\n".format(lr)
# print time, per_step, loss and acc
if val_flag and (step[0] - 1 == 0 or step[0] == step[1]
or step[0] % cfg.opts.print_step == 0):
current_time = time.strftime("%m-%d %H:%M:%S", time.localtime())
message += "{} Step:[{}/{}]".format(current_time, step[0], step[1])
message += " " * (len(str(step[1])) -
len(str(step[0]))) + " Loss:{:.4f} ".format(loss)
for metric in metrics:
message += "{}:{:.3f}% ".format(metric, metrics[metric] * 100)
if len(message) != 0:
print(message)
if cfg.opts.save_train_log:
mode = 'w' if epoch[1] == 1 and step[0] == 1 else 'a'
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR, 'Train_Log.txt'),
message,
mode=mode,
show=False)
return val_flag
def print_test_info(cfg, step, loss=100.0, metric=0.0):
"""Print validate information on the screen.
Inputs:
cfg: training options
step: a list includes --> [per_step, total_step]
loss: a float includes --> val loss value
metric: the current batch testing metric
"""
info = message = ""
if step[0] == 0:
equal_left, equal_right = cal_equal(15)
info += "\n" + "=" * equal_left + " Start Testing " + "=" * equal_right
print(info)
if cfg.opts.save_test_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR, 'Test_log.txt'), info, mode='w', show=False)
progress_bar(step[0], step[1], display=False)
if cfg.opts.test_label != 'None':
if step[0] + 1 >= step[1]:
message += "\n>>> Loss:{:.4f} ACC:{:.3f}% ".format(loss / step[1], metric / step[1] * 100)
print(message)
if cfg.opts.save_test_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR, 'Test_log.txt'), message, mode='a', show=False)
def print_val_info(val_flag, cfg, step, loss=100.0, metric=0.0):
"""Print validate information on the screen.
Inputs:
val_flag: whether print the information or not(bool)
cfg: training options
step: a list includes --> [per_step, total_step]
loss: a float includes --> val loss value
metric: the current batch validating metric
"""
info = message = ""
if val_flag:
if step[0] - 1 == 0:
info += ">>> Validate on the val dataset ..."
print(info)
if cfg.opts.save_train_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR, 'Train_Log.txt'), info, mode='a', show=False)
progress_bar(step[0]-1, step[1], display=False)
if step[0] >= step[1]:
message += "\n>>> Loss:{:.4f} ACC:{:.3f}% ".format(loss/step[1], metric/step[1]*100)
print(message)
if cfg.opts.save_train_log:
wrote_txt_file(os.path.join(cfg.CHECKPOINT_DIR, 'Train_Log.txt'), message, mode='a', show=False)