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def on_pretrain_routine_start(trainer):
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pass
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def on_pretrain_routine_end(trainer):
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pass
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def on_train_start(trainer):
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pass
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def on_train_epoch_start(trainer):
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pass
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def on_train_batch_start(trainer):
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pass
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def optimizer_step(trainer):
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pass
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def on_before_zero_grad(trainer):
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pass
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def on_train_batch_end(trainer):
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pass
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def on_train_epoch_end(trainer):
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pass
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def on_val_start(trainer):
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pass
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def on_val_batch_start(trainer):
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pass
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def on_val_image_end(trainer):
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pass
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def on_val_batch_end(trainer):
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pass
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def on_val_end(trainer):
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pass
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def on_fit_epoch_end(trainer):
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pass
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def on_model_save(trainer):
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pass
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def on_train_end(trainer):
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pass
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def on_params_update(trainer):
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pass
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def teardown(trainer):
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pass
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default_callbacks = {
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'on_pretrain_routine_start': on_pretrain_routine_start,
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'on_pretrain_routine_end': on_pretrain_routine_end,
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'on_train_start': on_train_start,
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'on_train_epoch_start': on_train_epoch_start,
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'on_train_batch_start': on_train_batch_start,
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|
'optimizer_step': optimizer_step,
|
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|
'on_before_zero_grad': on_before_zero_grad,
|
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|
'on_train_batch_end': on_train_batch_end,
|
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|
'on_train_epoch_end': on_train_epoch_end,
|
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|
'on_val_start': on_val_start,
|
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|
'on_val_batch_start': on_val_batch_start,
|
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|
|
'on_val_image_end': on_val_image_end,
|
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|
'on_val_batch_end': on_val_batch_end,
|
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|
'on_val_end': on_val_end,
|
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|
|
|
'on_fit_epoch_end': on_fit_epoch_end, # fit = train + val
|
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|
'on_model_save': on_model_save,
|
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|
|
'on_train_end': on_train_end,
|
|
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|
|
'on_params_update': on_params_update,
|
|
|
|
|
'teardown': teardown}
|
|
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|
|
def add_integration_callbacks(trainer):
|
|
|
|
|
from .clearml import callbacks as clearml_callbacks
|
|
|
|
|
from .tb import callbacks as tb_callbacks
|
|
|
|
|
|
|
|
|
|
for x in tb_callbacks, clearml_callbacks:
|
|
|
|
|
for k, v in x.items():
|
|
|
|
|
trainer.add_callback(k, v) # add_callback(name, func)
|
