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[Fix]Sync train api #115

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merged 1 commit into from
Apr 2, 2022
Merged

[Fix]Sync train api #115

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12 changes: 10 additions & 2 deletions mmrazor/apis/mmcls/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -65,6 +65,8 @@ def train_mmcls_model(model,
train_dataset = dataset[0]
dataset[0] = split_dataset(train_dataset)

sampler_cfg = cfg.data.get('sampler', None)

# Difference from mmclassification.
# Build multi dataloaders according the splited datasets.
data_loaders = list()
Expand All @@ -79,7 +81,8 @@ def train_mmcls_model(model,
num_gpus=len(cfg.gpu_ids),
dist=distributed,
round_up=True,
seed=cfg.seed) for item_ds in dset
seed=cfg.seed,
sampler_cfg=sampler_cfg) for item_ds in dset
]
else:
data_loader = build_dataloader(
Expand All @@ -90,7 +93,8 @@ def train_mmcls_model(model,
num_gpus=len(cfg.gpu_ids),
dist=distributed,
round_up=True,
seed=cfg.seed)
seed=cfg.seed,
sampler_cfg=sampler_cfg)

data_loaders.append(data_loader)

Expand Down Expand Up @@ -120,6 +124,10 @@ def train_mmcls_model(model,
model = MMDataParallel(
model.cuda(cfg.gpu_ids[0]), device_ids=cfg.gpu_ids)
elif device == 'cpu':
warnings.warn(
'The argument `device` is deprecated. To use cpu to train, '
'please refers to https://mmclassification.readthedocs.io/en'
'/latest/getting_started.html#train-a-model')
model = model.cpu()
else:
raise ValueError(F'unsupported device name {device}.')
Expand Down
7 changes: 6 additions & 1 deletion mmrazor/apis/mmdet/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,8 @@ def train_mmdet_model(model,
f'{cfg.data.imgs_per_gpu} in this experiments')
cfg.data.samples_per_gpu = cfg.data.imgs_per_gpu

runner_type = 'EpochBasedRunner' if 'runner' not in cfg else cfg.runner[
'type']
data_loader = [
build_dataloader(
ds,
Expand All @@ -84,7 +86,10 @@ def train_mmdet_model(model,
# cfg.gpus will be ignored if distributed
num_gpus=len(cfg.gpu_ids),
dist=distributed,
seed=cfg.seed) for ds in dataset
seed=cfg.seed,
runner_type=runner_type,
persistent_workers=cfg.data.get('persistent_workers', False))
for ds in dataset
]

# put model on gpus
Expand Down