[Feature]Add loader args to config (#1388)

* update pr

* add ut

* fix ut

* fix ut err

* fix ut name

* resolve comment

mmdet3d/utils/__init__.py

@@ -2,10 +2,11 @@
 from mmcv.utils import Registry, build_from_cfg, print_log
 
 from .collect_env import collect_env
+from .compat_cfg import compat_cfg
 from .logger import get_root_logger
 from .setup_env import setup_multi_processes
 
 __all__ = [
     'Registry', 'build_from_cfg', 'get_root_logger', 'collect_env',
-    'print_log', 'setup_multi_processes'
+    'print_log', 'setup_multi_processes', 'compat_cfg'
 ]

mmdet3d/utils/compat_cfg.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

mmdet3d/utils/setup_env.py

@@ -27,7 +27,13 @@ def setup_multi_processes(cfg):
 
     # setup OMP threads
     # This code is referred from https://github.com/pytorch/pytorch/blob/master/torch/distributed/run.py  # noqa
-    if 'OMP_NUM_THREADS' not in os.environ and cfg.data.workers_per_gpu > 1:
+    workers_per_gpu = cfg.data.get('workers_per_gpu', 1)
+    if 'train_dataloader' in cfg.data:
+        workers_per_gpu = \
+            max(cfg.data.train_dataloader.get('workers_per_gpu', 1),
+                workers_per_gpu)
+
+    if 'OMP_NUM_THREADS' not in os.environ and workers_per_gpu > 1:
         omp_num_threads = 1
         warnings.warn(
             f'Setting OMP_NUM_THREADS environment variable for each process '
@@ -37,7 +43,7 @@ def setup_multi_processes(cfg):
         os.environ['OMP_NUM_THREADS'] = str(omp_num_threads)
 
     # setup MKL threads
-    if 'MKL_NUM_THREADS' not in os.environ and cfg.data.workers_per_gpu > 1:
+    if 'MKL_NUM_THREADS' not in os.environ and workers_per_gpu > 1:
         mkl_num_threads = 1
         warnings.warn(
             f'Setting MKL_NUM_THREADS environment variable for each process '

tests/test_utils/test_compat_cfg.py

@@ -0,0 +1,126 @@
+import pytest
+from mmcv import ConfigDict
+
+from mmdet3d.utils.compat_cfg 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())))
+    with pytest.warns(None) as record:
+        cfg = compat_loader_args(cfg)
+    # 5 warning
+    assert len(record) == 5
+    # assert the warning message
+    assert 'train_dataloader' in record.list[0].message.args[0]
+    assert 'samples_per_gpu' in record.list[0].message.args[0]
+    assert 'persistent_workers' in record.list[1].message.args[0]
+    assert 'train_dataloader' in record.list[1].message.args[0]
+    assert 'workers_per_gpu' in record.list[2].message.args[0]
+    assert 'train_dataloader' in record.list[2].message.args[0]
+    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())))
+
+    with pytest.warns(None) as record:
+        cfg = compat_loader_args(cfg)
+    # 6 warning
+    assert len(record) == 6
+    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/test.py

@@ -24,6 +24,13 @@
 except ImportError:
     from mmdet3d.utils import setup_multi_processes
 
+try:
+    # If mmdet version > 2.23.0, compat_cfg would be imported and
+    # used from mmdet instead of mmdet3d.
+    from mmdet.utils import compat_cfg
+except ImportError:
+    from mmdet3d.utils import compat_cfg
+
 
 def parse_args():
     parser = argparse.ArgumentParser(
@@ -138,6 +145,8 @@ def main():
     if args.cfg_options is not None:
         cfg.merge_from_dict(args.cfg_options)
 
+    cfg = compat_cfg(cfg)
+
     # set multi-process settings
     setup_multi_processes(cfg)
 
@@ -146,23 +155,6 @@ def main():
         torch.backends.cudnn.benchmark = True
 
     cfg.model.pretrained = None
-    # in case the test dataset is concatenated
-    samples_per_gpu = 1
-    if isinstance(cfg.data.test, dict):
-        cfg.data.test.test_mode = True
-        samples_per_gpu = cfg.data.test.pop('samples_per_gpu', 1)
-        if samples_per_gpu > 1:
-            # Replace 'ImageToTensor' to 'DefaultFormatBundle'
-            cfg.data.test.pipeline = replace_ImageToTensor(
-                cfg.data.test.pipeline)
-    elif isinstance(cfg.data.test, list):
-        for ds_cfg in cfg.data.test:
-            ds_cfg.test_mode = True
-        samples_per_gpu = max(
-            [ds_cfg.pop('samples_per_gpu', 1) for ds_cfg in cfg.data.test])
-        if samples_per_gpu > 1:
-            for ds_cfg in cfg.data.test:
-                ds_cfg.pipeline = replace_ImageToTensor(ds_cfg.pipeline)
 
     if args.gpu_ids is not None:
         cfg.gpu_ids = args.gpu_ids[0:1]
@@ -180,18 +172,35 @@ def main():
         distributed = True
         init_dist(args.launcher, **cfg.dist_params)
 
+    test_dataloader_default_args = dict(
+        samples_per_gpu=1, workers_per_gpu=2, dist=distributed, shuffle=False)
+
+    # in case the test dataset is concatenated
+    if isinstance(cfg.data.test, dict):
+        cfg.data.test.test_mode = True
+        if cfg.data.test_dataloader.get('samples_per_gpu', 1) > 1:
+            # Replace 'ImageToTensor' to 'DefaultFormatBundle'
+            cfg.data.test.pipeline = replace_ImageToTensor(
+                cfg.data.test.pipeline)
+    elif isinstance(cfg.data.test, list):
+        for ds_cfg in cfg.data.test:
+            ds_cfg.test_mode = True
+        if cfg.data.test_dataloader.get('samples_per_gpu', 1) > 1:
+            for ds_cfg in cfg.data.test:
+                ds_cfg.pipeline = replace_ImageToTensor(ds_cfg.pipeline)
+
+    test_loader_cfg = {
+        **test_dataloader_default_args,
+        **cfg.data.get('test_dataloader', {})
+    }
+
     # set random seeds
     if args.seed is not None:
         set_random_seed(args.seed, deterministic=args.deterministic)
 
     # build the dataloader
     dataset = build_dataset(cfg.data.test)
-    data_loader = build_dataloader(
-        dataset,
-        samples_per_gpu=samples_per_gpu,
-        workers_per_gpu=cfg.data.workers_per_gpu,
-        dist=distributed,
-        shuffle=False)
+    data_loader = build_dataloader(dataset, **test_loader_cfg)
 
     # build the model and load checkpoint
     cfg.model.train_cfg = None