update code

configs/detection/_base_/datasets/fine_tune_based/base_coco.py

@@ -67,10 +67,5 @@ data = dict(
         img_prefix=data_root,
         pipeline=test_pipeline,
         test_mode=True,
-        classes='BASE_CLASSES'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        classes='BASE_CLASSES'))
 evaluation = dict(interval=5000, metric='bbox', classwise=True)

configs/detection/_base_/datasets/fine_tune_based/base_voc.py

@@ -75,10 +75,5 @@ data = dict(
         pipeline=test_pipeline,
         test_mode=True,
         classes=None,
-    ),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+    ))
 evaluation = dict(interval=3000, metric='mAP')

configs/detection/_base_/datasets/fine_tune_based/few_shot_coco.py

@@ -70,12 +70,7 @@ data = dict(
         img_prefix=data_root,
         pipeline=test_pipeline,
         test_mode=True,
-        classes='ALL_CLASSES'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        classes='ALL_CLASSES'))
 evaluation = dict(
     interval=4000,
     metric='bbox',

configs/detection/_base_/datasets/fine_tune_based/few_shot_voc.py

@@ -77,10 +77,5 @@ data = dict(
         img_prefix=data_root,
         pipeline=test_pipeline,
         test_mode=True,
-        classes=None),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        classes=None))
 evaluation = dict(interval=2000, metric='mAP', class_splits=None)

configs/detection/_base_/datasets/nway_kshot/base_coco.py

@@ -89,10 +89,5 @@ data = dict(
         pipeline=train_multi_pipelines['support'],
         instance_wise=True,
         classes='BASE_CLASSES',
-        dataset_name='model_init_dataset'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init_dataset'))
 evaluation = dict(interval=20000, metric='bbox', classwise=True)

configs/detection/_base_/datasets/nway_kshot/base_voc.py

@@ -112,10 +112,5 @@ data = dict(
         use_difficult=False,
         instance_wise=True,
         classes=None,
-        dataset_name='model_init_dataset'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init_dataset'))
 evaluation = dict(interval=5000, metric='mAP')

configs/detection/_base_/datasets/nway_kshot/few_shot_coco.py

@@ -90,12 +90,7 @@ data = dict(
         pipeline=train_multi_pipelines['support'],
         instance_wise=True,
         classes='ALL_CLASSES',
-        dataset_name='model_init_dataset'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init_dataset'))
 evaluation = dict(
     interval=3000,
     metric='bbox',

configs/detection/_base_/datasets/nway_kshot/few_shot_voc.py

@@ -97,10 +97,5 @@ data = dict(
         instance_wise=True,
         num_novel_shots=None,
         classes=None,
-        dataset_name='model_init_dataset'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init_dataset'))
 evaluation = dict(interval=3000, metric='mAP', class_splits=None)

configs/detection/_base_/datasets/query_aware/base_coco.py

@@ -103,10 +103,5 @@ data = dict(
         num_base_shots=10,
         instance_wise=True,
         min_bbox_area=32 * 32,
-        dataset_name='model_init_dataset'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init_dataset'))
 evaluation = dict(interval=20000, metric='bbox', classwise=True)

configs/detection/_base_/datasets/query_aware/base_voc.py

@@ -114,10 +114,5 @@ data = dict(
         instance_wise=True,
         classes=None,
         min_bbox_area=32 * 32,
-        dataset_name='model_init'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init'))
 evaluation = dict(interval=20000, metric='mAP')

configs/detection/_base_/datasets/query_aware/few_shot_coco.py

@@ -101,11 +101,6 @@ data = dict(
         num_base_shots=None,
         instance_wise=True,
         min_bbox_area=32 * 32,
-        dataset_name='model_init_dataset'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init_dataset'))
 evaluation = dict(
     interval=3000, metric='bbox', classwise=True, class_splits=None)

configs/detection/_base_/datasets/query_aware/few_shot_voc.py

@@ -104,10 +104,5 @@ data = dict(
         num_novel_shots=None,
         classes=None,
         min_bbox_area=32 * 32,
-        dataset_name='model_init_dataset'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        dataset_name='model_init_dataset'))
 evaluation = dict(interval=3000, metric='mAP', class_splits=None)

configs/detection/_base_/datasets/two_branch/base_coco.py

@@ -95,10 +95,5 @@ data = dict(
         img_prefix=data_root,
         pipeline=test_pipeline,
         test_mode=True,
-        classes='BASE_CLASSES'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        classes='BASE_CLASSES'))
 evaluation = dict(interval=20000, metric='bbox', classwise=True)

configs/detection/_base_/datasets/two_branch/base_voc.py

@@ -102,10 +102,5 @@ data = dict(
         pipeline=test_pipeline,
         coordinate_offset=[-1, -1, -1, -1],
         test_mode=True,
-        classes=None),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        classes=None))
 evaluation = dict(interval=5000, metric='mAP')

configs/detection/_base_/datasets/two_branch/few_shot_coco.py

@@ -95,12 +95,7 @@ data = dict(
         img_prefix=data_root,
         pipeline=test_pipeline,
         test_mode=True,
-        classes='ALL_CLASSES'),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        classes='ALL_CLASSES'))
 evaluation = dict(
     interval=3000,
     metric='bbox',

configs/detection/_base_/datasets/two_branch/few_shot_voc.py

@@ -102,10 +102,5 @@ data = dict(
         pipeline=test_pipeline,
         coordinate_offset=[-1, -1, -1, -1],
         test_mode=True,
-        classes=None),
-    train_dataloader=dict(persistent_workers=False),
-    val_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2),
-    test_dataloader=dict(
-        persistent_workers=False, samples_per_gpu=1, workers_per_gpu=2))
+        classes=None))
 evaluation = dict(interval=3000, metric='mAP', class_splits=None)

mmfewshot/classification/apis/train.py

@@ -14,7 +14,7 @@ from mmfewshot.classification.core.evaluation import (DistMetaTestEvalHook,
                                                       MetaTestEvalHook)
 from mmfewshot.classification.datasets.builder import (
     build_dataloader, build_dataset, build_meta_test_dataloader)
-from mmfewshot.utils import get_root_logger
+from mmfewshot.utils import compat_cfg, get_root_logger
 
 
 def train_model(model: Union[MMDataParallel, MMDistributedDataParallel],
@@ -25,12 +25,13 @@ def train_model(model: Union[MMDataParallel, MMDistributedDataParallel],
                 timestamp: str = None,
                 device: str = None,
                 meta: Dict = None) -> None:
+    cfg = compat_cfg(cfg)
     logger = get_root_logger(log_level=cfg.log_level)
 
     # prepare data loaders
     dataset = dataset if isinstance(dataset, (list, tuple)) else [dataset]
 
-    loader_cfg = dict(
+    train_dataloader_default_args = dict(
         # cfg.gpus will be ignored if distributed
         num_gpus=len(cfg.gpu_ids),
         dist=distributed,
@@ -38,16 +39,11 @@ def train_model(model: Union[MMDataParallel, MMDistributedDataParallel],
         seed=cfg.get('seed'),
         pin_memory=cfg.get('pin_memory', False),
         use_infinite_sampler=cfg.use_infinite_sampler)
-    # The overall dataloader settings
-    loader_cfg.update({
-        k: v
-        for k, v in cfg.data.items() if k not in [
-            'train', 'val', 'test', 'train_dataloader', 'val_dataloader',
-            'test_dataloader'
-        ]
-    })
     # The specific dataloader settings
-    train_loader_cfg = {**loader_cfg, **cfg.data.get('train_dataloader', {})}
+    train_loader_cfg = {
+        **train_dataloader_default_args,
+        **cfg.data.get('train_dataloader', {})
+    }
 
     data_loaders = [build_dataloader(ds, **train_loader_cfg) for ds in dataset]
 

mmfewshot/detection/apis/train.py

@@ -16,7 +16,7 @@ from mmfewshot.detection.core import (QuerySupportDistEvalHook,
                                       QuerySupportEvalHook)
 from mmfewshot.detection.datasets import (build_dataloader, build_dataset,
                                           get_copy_dataset_type)
-from mmfewshot.utils import get_root_logger
+from mmfewshot.utils import compat_cfg, get_root_logger
 
 
 def train_detector(model: nn.Module,
@@ -26,6 +26,7 @@ def train_detector(model: nn.Module,
                    validate: bool = False,
                    timestamp: Optional[str] = None,
                    meta: Optional[Dict] = None) -> None:
+    cfg = compat_cfg(cfg)
     logger = get_root_logger(log_level=cfg.log_level)
 
     # prepare data loaders
@@ -40,13 +41,6 @@ def train_detector(model: nn.Module,
         data_cfg=copy.deepcopy(cfg.data),
         use_infinite_sampler=cfg.use_infinite_sampler,
         persistent_workers=False)
-    train_dataloader_default_args.update({
-        k: v
-        for k, v in cfg.data.items() if k not in [
-            'train', 'val', 'test', 'train_dataloader', 'val_dataloader',
-            'test_dataloader', 'model_init'
-        ]
-    })
     train_loader_cfg = {
         **train_dataloader_default_args,
         **cfg.data.get('train_dataloader', {})
@@ -115,22 +109,6 @@ def train_detector(model: nn.Module,
             dist=distributed,
             shuffle=False,
             persistent_workers=False)
-
-        # update overall dataloader(for train, val and test) setting
-        val_dataloader_default_args.update({
-            k: v
-            for k, v in cfg.data.items() if k not in [
-                'train', 'val', 'test', 'train_dataloader', 'val_dataloader',
-                'test_dataloader', 'samples_per_gpu', 'model_init'
-            ]
-        })
-        if 'samples_per_gpu' in cfg.data.val:
-            logger.warning('`samples_per_gpu` in `val` field of '
-                           'data will be deprecated, you should'
-                           ' move it to `val_dataloader` field')
-            # keep default value of `sample_per_gpu` is 1
-            val_dataloader_default_args['samples_per_gpu'] = \
-                cfg.data.val.pop('samples_per_gpu')
         val_dataloader_args = {
             **val_dataloader_default_args,
             **cfg.data.get('val_dataloader', {})

mmfewshot/utils/__init__.py

@@ -1,5 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from .collate import multi_pipeline_collate_fn
+from .compat_config import compat_cfg
 from .dist_utils import check_dist_init, sync_random_seed
 from .infinite_sampler import (DistributedInfiniteGroupSampler,
                                DistributedInfiniteSampler,
@@ -12,5 +13,5 @@ __all__ = [
     'multi_pipeline_collate_fn', 'local_numpy_seed',
     'InfiniteEpochBasedRunner', 'InfiniteSampler', 'InfiniteGroupSampler',
     'DistributedInfiniteSampler', 'DistributedInfiniteGroupSampler',
-    'get_root_logger', 'check_dist_init', 'sync_random_seed'
+    'get_root_logger', 'check_dist_init', 'sync_random_seed', 'compat_cfg'
 ]

mmfewshot/utils/compat_config.py

@@ -0,0 +1,139 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import copy
+import warnings
+
+from mmcv import ConfigDict
+
+
+def compat_cfg(cfg):
+    """This function would modify some filed to keep the compatibility of
+    config.
+
+    For example, it will move some args which will be deprecated to the correct
+    fields.
+    """
+    cfg = copy.deepcopy(cfg)
+    cfg = compat_imgs_per_gpu(cfg)
+    cfg = compat_loader_args(cfg)
+    cfg = compat_runner_args(cfg)
+    return cfg
+
+
+def compat_runner_args(cfg):
+    if 'runner' not in cfg:
+        cfg.runner = ConfigDict({
+            'type': 'EpochBasedRunner',
+            'max_epochs': cfg.total_epochs
+        })
+        warnings.warn(
+            'config is now expected to have a `runner` section, '
+            'please set `runner` in your config.', UserWarning)
+    else:
+        if 'total_epochs' in cfg:
+            assert cfg.total_epochs == cfg.runner.max_epochs
+    return cfg
+
+
+def compat_imgs_per_gpu(cfg):
+    cfg = copy.deepcopy(cfg)
+    if 'imgs_per_gpu' in cfg.data:
+        warnings.warn('"imgs_per_gpu" is deprecated in MMDet V2.0. '
+                      'Please use "samples_per_gpu" instead')
+        if 'samples_per_gpu' in cfg.data:
+            warnings.warn(
+                f'Got "imgs_per_gpu"={cfg.data.imgs_per_gpu} and '
+                f'"samples_per_gpu"={cfg.data.samples_per_gpu}, "imgs_per_gpu"'
+                f'={cfg.data.imgs_per_gpu} is used in this experiments')
+        else:
+            warnings.warn('Automatically set "samples_per_gpu"="imgs_per_gpu"='
+                          f'{cfg.data.imgs_per_gpu} in this experiments')
+        cfg.data.samples_per_gpu = cfg.data.imgs_per_gpu
+    return cfg
+
+
+def compat_loader_args(cfg):
+    """Deprecated sample_per_gpu in cfg.data."""
+
+    cfg = copy.deepcopy(cfg)
+    if 'train_dataloader' not in cfg.data:
+        cfg.data['train_dataloader'] = ConfigDict()
+    if 'val_dataloader' not in cfg.data:
+        cfg.data['val_dataloader'] = ConfigDict()
+    if 'test_dataloader' not in cfg.data:
+        cfg.data['test_dataloader'] = ConfigDict()
+
+    # special process for train_dataloader
+    if 'samples_per_gpu' in cfg.data:
+
+        samples_per_gpu = cfg.data.pop('samples_per_gpu')
+        assert 'samples_per_gpu' not in \
+               cfg.data.train_dataloader, ('`samples_per_gpu` are set '
+                                           'in `data` field and ` '
+                                           'data.train_dataloader` '
+                                           'at the same time. '
+                                           'Please only set it in '
+                                           '`data.train_dataloader`. ')
+        cfg.data.train_dataloader['samples_per_gpu'] = samples_per_gpu
+
+    if 'persistent_workers' in cfg.data:
+
+        persistent_workers = cfg.data.pop('persistent_workers')
+        assert 'persistent_workers' not in \
+               cfg.data.train_dataloader, ('`persistent_workers` are set '
+                                           'in `data` field and ` '
+                                           'data.train_dataloader` '
+                                           'at the same time. '
+                                           'Please only set it in '
+                                           '`data.train_dataloader`. ')
+        cfg.data.train_dataloader['persistent_workers'] = persistent_workers
+
+    if 'workers_per_gpu' in cfg.data:
+
+        workers_per_gpu = cfg.data.pop('workers_per_gpu')
+        cfg.data.train_dataloader['workers_per_gpu'] = workers_per_gpu
+        cfg.data.val_dataloader['workers_per_gpu'] = workers_per_gpu
+        cfg.data.test_dataloader['workers_per_gpu'] = workers_per_gpu
+
+    # special process for val_dataloader
+    if 'samples_per_gpu' in cfg.data.val:
+        # keep default value of `sample_per_gpu` is 1
+        assert 'samples_per_gpu' not in \
+               cfg.data.val_dataloader, ('`samples_per_gpu` are set '
+                                         'in `data.val` field and ` '
+                                         'data.val_dataloader` at '
+                                         'the same time. '
+                                         'Please only set it in '
+                                         '`data.val_dataloader`. ')
+        cfg.data.val_dataloader['samples_per_gpu'] = \
+            cfg.data.val.pop('samples_per_gpu')
+    # special process for val_dataloader
+
+    # in case the test dataset is concatenated
+    if isinstance(cfg.data.test, dict):
+        if 'samples_per_gpu' in cfg.data.test:
+            assert 'samples_per_gpu' not in \
+                   cfg.data.test_dataloader, ('`samples_per_gpu` are set '
+                                              'in `data.test` field and ` '
+                                              'data.test_dataloader` '
+                                              'at the same time. '
+                                              'Please only set it in '
+                                              '`data.test_dataloader`. ')
+
+            cfg.data.test_dataloader['samples_per_gpu'] = \
+                cfg.data.test.pop('samples_per_gpu')
+
+    elif isinstance(cfg.data.test, list):
+        for ds_cfg in cfg.data.test:
+            if 'samples_per_gpu' in ds_cfg:
+                assert 'samples_per_gpu' not in \
+                       cfg.data.test_dataloader, ('`samples_per_gpu` are set '
+                                                  'in `data.test` field and ` '
+                                                  'data.test_dataloader` at'
+                                                  ' the same time. '
+                                                  'Please only set it in '
+                                                  '`data.test_dataloader`. ')
+        samples_per_gpu = max(
+            [ds_cfg.pop('samples_per_gpu', 1) for ds_cfg in cfg.data.test])
+        cfg.data.test_dataloader['samples_per_gpu'] = samples_per_gpu
+
+    return cfg

tests/test_utils/test_conpat_config.py

@@ -0,0 +1,116 @@
+import pytest
+from mmcv import ConfigDict
+
+from mmfewshot.utils.compat_config import (compat_imgs_per_gpu,
+                                           compat_loader_args,
+                                           compat_runner_args)
+
+
+def test_compat_runner_args():
+    cfg = ConfigDict(dict(total_epochs=12))
+    with pytest.warns(None) as record:
+        cfg = compat_runner_args(cfg)
+    assert len(record) == 1
+    assert 'runner' in record.list[0].message.args[0]
+    assert 'runner' in cfg
+    assert cfg.runner.type == 'EpochBasedRunner'
+    assert cfg.runner.max_epochs == cfg.total_epochs
+
+
+def test_compat_loader_args():
+    cfg = ConfigDict(dict(data=dict(val=dict(), test=dict(), train=dict())))
+    cfg = compat_loader_args(cfg)
+    # auto fill loader args
+    assert 'val_dataloader' in cfg.data
+    assert 'train_dataloader' in cfg.data
+    assert 'test_dataloader' in cfg.data
+    cfg = ConfigDict(
+        dict(
+            data=dict(
+                samples_per_gpu=1,
+                persistent_workers=True,
+                workers_per_gpu=1,
+                val=dict(samples_per_gpu=3),
+                test=dict(samples_per_gpu=2),
+                train=dict())))
+
+    cfg = compat_loader_args(cfg)
+
+    assert cfg.data.train_dataloader.workers_per_gpu == 1
+    assert cfg.data.train_dataloader.samples_per_gpu == 1
+    assert cfg.data.train_dataloader.persistent_workers
+    assert cfg.data.val_dataloader.workers_per_gpu == 1
+    assert cfg.data.val_dataloader.samples_per_gpu == 3
+    assert cfg.data.test_dataloader.workers_per_gpu == 1
+    assert cfg.data.test_dataloader.samples_per_gpu == 2
+
+    # test test is a list
+    cfg = ConfigDict(
+        dict(
+            data=dict(
+                samples_per_gpu=1,
+                persistent_workers=True,
+                workers_per_gpu=1,
+                val=dict(samples_per_gpu=3),
+                test=[dict(samples_per_gpu=2),
+                      dict(samples_per_gpu=3)],
+                train=dict())))
+
+    cfg = compat_loader_args(cfg)
+    assert cfg.data.test_dataloader.samples_per_gpu == 3
+
+    # assert can not set args at the same time
+    cfg = ConfigDict(
+        dict(
+            data=dict(
+                samples_per_gpu=1,
+                persistent_workers=True,
+                workers_per_gpu=1,
+                val=dict(samples_per_gpu=3),
+                test=dict(samples_per_gpu=2),
+                train=dict(),
+                train_dataloader=dict(samples_per_gpu=2))))
+    # samples_per_gpu can not be set in `train_dataloader`
+    # and data field at the same time
+    with pytest.raises(AssertionError):
+        compat_loader_args(cfg)
+    cfg = ConfigDict(
+        dict(
+            data=dict(
+                samples_per_gpu=1,
+                persistent_workers=True,
+                workers_per_gpu=1,
+                val=dict(samples_per_gpu=3),
+                test=dict(samples_per_gpu=2),
+                train=dict(),
+                val_dataloader=dict(samples_per_gpu=2))))
+    # samples_per_gpu can not be set in `val_dataloader`
+    # and data field at the same time
+    with pytest.raises(AssertionError):
+        compat_loader_args(cfg)
+    cfg = ConfigDict(
+        dict(
+            data=dict(
+                samples_per_gpu=1,
+                persistent_workers=True,
+                workers_per_gpu=1,
+                val=dict(samples_per_gpu=3),
+                test=dict(samples_per_gpu=2),
+                test_dataloader=dict(samples_per_gpu=2))))
+    # samples_per_gpu can not be set in `test_dataloader`
+    # and data field at the same time
+    with pytest.raises(AssertionError):
+        compat_loader_args(cfg)
+
+
+def test_compat_imgs_per_gpu():
+    cfg = ConfigDict(
+        dict(
+            data=dict(
+                imgs_per_gpu=1,
+                samples_per_gpu=2,
+                val=dict(),
+                test=dict(),
+                train=dict())))
+    cfg = compat_imgs_per_gpu(cfg)
+    assert cfg.data.samples_per_gpu == cfg.data.imgs_per_gpu

tools/detection/test.py

@@ -13,6 +13,7 @@ from mmcv.runner import (get_dist_info, init_dist, load_checkpoint,
 from mmfewshot.detection.datasets import (build_dataloader, build_dataset,
                                           get_copy_dataset_type)
 from mmfewshot.detection.models import build_detector
+from mmfewshot.utils import compat_cfg
 
 
 def parse_args():
@@ -112,6 +113,7 @@ def main():
         raise ValueError('The output file must be a pkl file.')
 
     cfg = Config.fromfile(args.config)
+    cfg = compat_cfg(cfg)
 
     if args.cfg_options is not None:
         cfg.merge_from_dict(args.cfg_options)
@@ -153,10 +155,15 @@ def main():
             'test_dataloader', 'samples_per_gpu', 'model_init'
         ]
     })
+    test_loader_cfg = {
+        **test_dataloader_default_args,
+        **cfg.data.get('test_dataloader', {})
+    }
+
     # currently only support single images testing
-    assert test_dataloader_default_args['samples_per_gpu'] == 1, \
+    assert test_loader_cfg['samples_per_gpu'] == 1, \
         'currently only support single images testing'
-    data_loader = build_dataloader(dataset, **test_dataloader_default_args)
+    data_loader = build_dataloader(dataset, **test_loader_cfg)
 
     # pop frozen_parameters
     cfg.model.pop('frozen_parameters', None)