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# ---------------------------------------------
# Copyright (c) OpenMMLab. All rights reserved.
# ---------------------------------------------
# Modified by Zhiqi Li
# ---------------------------------------------
# ---------------------------------------------
# Modified by Shihao Wang
# ---------------------------------------------
from .mmdet_train import custom_train_detector
from mmseg.apis import train_segmentor
from mmdet.apis import train_detector
def custom_train_model(model,
dataset,
cfg,
distributed=False,
validate=False,
timestamp=None,
eval_model=None,
meta=None):
"""A function wrapper for launching model training according to cfg.
Because we need different eval_hook in runner. Should be deprecated in the
future.
"""
if cfg.model.type in ['EncoderDecoder3D']:
assert False
else:
custom_train_detector(
model,
dataset,
cfg,
distributed=distributed,
validate=validate,
timestamp=timestamp,
eval_model=eval_model,
meta=meta)
def train_model(model,
dataset,
cfg,
distributed=False,
validate=False,
timestamp=None,
meta=None):
"""A function wrapper for launching model training according to cfg.
Because we need different eval_hook in runner. Should be deprecated in the
future.
"""
if cfg.model.type in ['EncoderDecoder3D']:
train_segmentor(
model,
dataset,
cfg,
distributed=distributed,
validate=validate,
timestamp=timestamp,
meta=meta)
else:
train_detector(
model,
dataset,
cfg,
distributed=distributed,
validate=validate,
timestamp=timestamp,
meta=meta)