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# Ultralytics YOLO base callbacks
# Trainer callbacks ----------------------------------------------------------------------------------------------------
def on_pretrain_routine_start(trainer):
pass
def on_pretrain_routine_end(trainer):
pass
def on_train_start(trainer):
pass
def on_train_epoch_start(trainer):
pass
def on_train_batch_start(trainer):
pass
def optimizer_step(trainer):
pass
def on_before_zero_grad(trainer):
pass
def on_train_batch_end(trainer):
pass
def on_train_epoch_end(trainer):
pass
def on_fit_epoch_end(trainer):
pass
def on_model_save(trainer):
pass
def on_train_end(trainer):
pass
def on_params_update(trainer):
pass
def teardown(trainer):
pass
# Validator callbacks --------------------------------------------------------------------------------------------------
def on_val_start(validator):
pass
def on_val_batch_start(validator):
pass
def on_val_batch_end(validator):
pass
def on_val_end(validator):
pass
# Predictor callbacks --------------------------------------------------------------------------------------------------
def on_predict_start(predictor):
pass
def on_predict_batch_start(predictor):
pass
def on_predict_batch_end(predictor):
pass
def on_predict_end(predictor):
pass
# Exporter callbacks ---------------------------------------------------------------------------------------------------
def on_export_start(exporter):
pass
def on_export_end(exporter):
pass
default_callbacks = {
# Run in trainer
'on_pretrain_routine_start': on_pretrain_routine_start,
'on_pretrain_routine_end': on_pretrain_routine_end,
'on_train_start': on_train_start,
'on_train_epoch_start': on_train_epoch_start,
'on_train_batch_start': on_train_batch_start,
'optimizer_step': optimizer_step,
'on_before_zero_grad': on_before_zero_grad,
'on_train_batch_end': on_train_batch_end,
'on_train_epoch_end': on_train_epoch_end,
'on_fit_epoch_end': on_fit_epoch_end, # fit = train + val
'on_model_save': on_model_save,
'on_train_end': on_train_end,
'on_params_update': on_params_update,
'teardown': teardown,
# Run in validator
'on_val_start': on_val_start,
'on_val_batch_start': on_val_batch_start,
'on_val_batch_end': on_val_batch_end,
'on_val_end': on_val_end,
# Run in predictor
'on_predict_start': on_predict_start,
'on_predict_batch_start': on_predict_batch_start,
'on_predict_batch_end': on_predict_batch_end,
'on_predict_end': on_predict_end,
# Run in exporter
'on_export_start': on_export_start,
'on_export_end': on_export_end}
def add_integration_callbacks(instance):
from .clearml import callbacks as clearml_callbacks
from .hub import callbacks as hub_callbacks
from .tensorboard import callbacks as tb_callbacks
from .wb import callbacks as wb_callbacks
for x in clearml_callbacks, hub_callbacks, tb_callbacks, wb_callbacks:
for k, v in x.items():
instance.callbacks[k].append(v) # callback[name].append(func)