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EarlyStopper updates (#4679)

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Glenn Jocher authored and GitHub committed 2021-09-05 19:09:53 +02:00
1 parent f64fab5825
commit 548745181a
2 files changed
+8 -5
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train.py
+3 -3
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@@ -344,7 +344,7 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary
# mAP # mAP
callbacks.on_train_epoch_end(epoch=epoch) callbacks.on_train_epoch_end(epoch=epoch)
ema.update_attr(model, include=['yaml', 'nc', 'hyp', 'names', 'stride', 'class_weights']) ema.update_attr(model, include=['yaml', 'nc', 'hyp', 'names', 'stride', 'class_weights'])
final_epoch = epoch + 1 == epochs final_epoch = (epoch + 1 == epochs) or stopper.possible_stop
if not noval or final_epoch: # Calculate mAP if not noval or final_epoch: # Calculate mAP
results, maps, _ = val.run(data_dict, results, maps, _ = val.run(data_dict,
batch_size=batch_size // WORLD_SIZE * 2, batch_size=batch_size // WORLD_SIZE * 2,
@@ -384,7 +384,7 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary
callbacks.on_model_save(last, epoch, final_epoch, best_fitness, fi) callbacks.on_model_save(last, epoch, final_epoch, best_fitness, fi)
# Stop Single-GPU # Stop Single-GPU
if stopper(epoch=epoch, fitness=fi): if RANK == -1 and stopper(epoch=epoch, fitness=fi):
break break
# Stop DDP TODO: known issues shttps://github.com/ultralytics/yolov5/pull/4576 # Stop DDP TODO: known issues shttps://github.com/ultralytics/yolov5/pull/4576
@@ -462,7 +462,7 @@ def parse_opt(known=False):
parser.add_argument('--artifact_alias', type=str, default="latest", help='version of dataset artifact to be used') parser.add_argument('--artifact_alias', type=str, default="latest", help='version of dataset artifact to be used')
parser.add_argument('--local_rank', type=int, default=-1, help='DDP parameter, do not modify') parser.add_argument('--local_rank', type=int, default=-1, help='DDP parameter, do not modify')
parser.add_argument('--freeze', type=int, default=0, help='Number of layers to freeze. backbone=10, all=24') parser.add_argument('--freeze', type=int, default=0, help='Number of layers to freeze. backbone=10, all=24')
parser.add_argument('--patience', type=int, default=30, help='EarlyStopping patience (epochs)') parser.add_argument('--patience', type=int, default=100, help='EarlyStopping patience (epochs without improvement)')
opt = parser.parse_known_args()[0] if known else parser.parse_args() opt = parser.parse_known_args()[0] if known else parser.parse_args()
return opt return opt
utils/torch_utils.py
+5 -2
View File
@@ -298,13 +298,16 @@ class EarlyStopping:
def __init__(self, patience=30): def __init__(self, patience=30):
self.best_fitness = 0.0 # i.e. mAP self.best_fitness = 0.0 # i.e. mAP
self.best_epoch = 0 self.best_epoch = 0
self.patience = patience # epochs to wait after fitness stops improving to stop self.patience = patience or float('inf') # epochs to wait after fitness stops improving to stop
self.possible_stop = False # possible stop may occur next epoch
def __call__(self, epoch, fitness): def __call__(self, epoch, fitness):
if fitness >= self.best_fitness: # >= 0 to allow for early zero-fitness stage of training if fitness >= self.best_fitness: # >= 0 to allow for early zero-fitness stage of training
self.best_epoch = epoch self.best_epoch = epoch
self.best_fitness = fitness self.best_fitness = fitness
stop = (epoch - self.best_epoch) >= self.patience # stop training if patience exceeded delta = epoch - self.best_epoch # epochs without improvement
self.possible_stop = delta >= (self.patience - 1) # possible stop may occur next epoch
stop = delta >= self.patience # stop training if patience exceeded
if stop: if stop:
LOGGER.info(f'EarlyStopping patience {self.patience} exceeded, stopping training.') LOGGER.info(f'EarlyStopping patience {self.patience} exceeded, stopping training.')
return stop return stop