[Improvement] Remove dependency package warnings

demo/demo_spatiotemporal_det.py

@@ -3,7 +3,6 @@
 import os
 import os.path as osp
 import shutil
-import warnings
 
 import cv2
 import mmcv
@@ -13,11 +12,20 @@
 from tqdm import tqdm
 
 from mmaction.models import build_detector
+from mmaction.utils import import_module_error_func
 
 try:
     from mmdet.apis import inference_detector, init_detector
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use demo_spatiotempoal_det')
+
+    @import_module_error_func('mmdet')
+    def inference_detector(*args, **kwargs):
+        pass
+
+    @import_module_error_func('mmdet')
+    def init_detector(*args, **kwargs):
+        pass
+
 
 try:
     import moviepy.editor as mpy

docs/changelog.md

@@ -18,7 +18,6 @@
 
 - Refactor EvalHook ([#395](https://github.com/open-mmlab/mmaction2/pull/395))
 - Refactor AVA hook ([#567](https://github.com/open-mmlab/mmaction2/pull/567))
-- Refactor unit test structure ([#433](https://github.com/open-mmlab/mmaction2/pull/433))
 - Add repo citation ([#545](https://github.com/open-mmlab/mmaction2/pull/545))
 - Add dataset size of Kinetics400 ([#503](https://github.com/open-mmlab/mmaction2/pull/503))
 - Add lazy operation docs ([#504](https://github.com/open-mmlab/mmaction2/pull/504))
@@ -31,6 +30,7 @@
 - Add config tag in dataset README ([#540](https://github.com/open-mmlab/mmaction2/pull/540))
 - Add solution for markdownlint installation issue ([#497](https://github.com/open-mmlab/mmaction2/pull/497))
 - Add dataset overview in readthedocs ([#548](https://github.com/open-mmlab/mmaction2/pull/548))
+- Modify the trigger mode of the warnings of missing mmdet ([583](https://github.com/open-mmlab/mmaction2/pull/583))
 - Refactor config structure ([#488](https://github.com/open-mmlab/mmaction2/pull/488), [#572](https://github.com/open-mmlab/mmaction2/pull/572))
 - Refactor unittest structure ([#433](https://github.com/open-mmlab/mmaction2/pull/433))
 

mmaction/core/bbox/assigners/max_iou_assigner_ava.py

@@ -1,14 +1,12 @@
-import warnings
-
 import torch
 
+from mmaction.utils import import_module_error_class
+
 try:
     from mmdet.core.bbox import AssignResult, MaxIoUAssigner
     from mmdet.core.bbox.builder import BBOX_ASSIGNERS
     mmdet_imported = True
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use AssignResult, MaxIoUAssigner '
-                  'and BBOX_ASSIGNERS')
     mmdet_imported = False
 
 if mmdet_imported:
@@ -135,5 +133,6 @@ def assign_wrt_overlaps(self, overlaps, gt_labels=None):
 
 else:
     # define an empty class, so that can be imported
+    @import_module_error_class('mmdet')
     class MaxIoUAssignerAVA:
         pass

mmaction/core/evaluation/recall.py

@@ -1,12 +1,15 @@
-import warnings
-
 import numpy as np
 import torch
 
+from mmaction.utils import import_module_error_func
+
 try:
     from mmdet.core import bbox_overlaps
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use bbox_overlaps')
+
+    @import_module_error_func('mmdet')
+    def bbox_overlaps(*args, **kwargs):
+        pass
 
 
 def _recalls(all_ious, proposal_nums, thrs):

mmaction/models/backbones/resnet3d.py

@@ -1,5 +1,3 @@
-import warnings
-
 import torch.nn as nn
 import torch.utils.checkpoint as cp
 from mmcv.cnn import (ConvModule, NonLocal3d, build_activation_layer,
@@ -15,7 +13,6 @@
     from mmdet.models.builder import SHARED_HEADS as MMDET_SHARED_HEADS
     mmdet_imported = True
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use MMDET_SHARED_HEADS')
     mmdet_imported = False
 
 

mmaction/models/backbones/resnet3d_slowfast.py

@@ -1,5 +1,3 @@
-import warnings
-
 import torch
 import torch.nn as nn
 from mmcv.cnn import ConvModule, kaiming_init
@@ -14,7 +12,6 @@
     from mmdet.models import BACKBONES as MMDET_BACKBONES
     mmdet_imported = True
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use MMDET_BACKBONES')
     mmdet_imported = False
 
 

mmaction/models/backbones/resnet3d_slowonly.py

@@ -1,13 +1,10 @@
-import warnings
-
 from ..registry import BACKBONES
 from .resnet3d_slowfast import ResNet3dPathway
 
 try:
     from mmdet.models.builder import BACKBONES as MMDET_BACKBONES
     mmdet_imported = True
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use MMDET_BACKBONES')
     mmdet_imported = False
 
 

mmaction/models/backbones/resnet_tin.py

@@ -1,15 +1,17 @@
-import warnings
-
 import torch
 import torch.nn as nn
 
+from mmaction.utils import import_module_error_func
 from ..registry import BACKBONES
 from .resnet_tsm import ResNetTSM
 
 try:
     from mmcv.ops import tin_shift
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmcv-full to support "tin_shift"')
+
+    @import_module_error_func('mmcv-full')
+    def tin_shift(*args, **kwargs):
+        pass
 
 
 def linear_sampler(data, offset):

mmaction/models/builder.py

@@ -1,18 +1,16 @@
-import warnings
-
 import torch.nn as nn
 from mmcv.utils import Registry, build_from_cfg
 
+from mmaction.utils import import_module_error_func
 from .registry import BACKBONES, HEADS, LOCALIZERS, LOSSES, NECKS, RECOGNIZERS
 
 try:
     from mmdet.models.builder import DETECTORS, build_detector
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use DETECTORS, build_detector')
-
     # Define an empty registry and building func, so that can import
     DETECTORS = Registry('detector')
 
+    @import_module_error_func('mmdet')
     def build_detector(cfg, train_cfg, test_cfg):
         pass
 

mmaction/models/heads/bbox_head.py

@@ -1,5 +1,3 @@
-import warnings
-
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -10,7 +8,6 @@
     from mmdet.models.builder import HEADS as MMDET_HEADS
     mmdet_imported = True
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use MMDET_HEADS')
     mmdet_imported = False
 
 

mmaction/models/heads/roi_head.py

@@ -1,17 +1,14 @@
-import warnings
-
 import numpy as np
 
 from mmaction.core.bbox import bbox2result
+from mmaction.utils import import_module_error_class
 
 try:
     from mmdet.core.bbox import bbox2roi
     from mmdet.models import HEADS as MMDET_HEADS
     from mmdet.models.roi_heads import StandardRoIHead
     mmdet_imported = True
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use bbox2roi, MMDET_HEADS '
-                  'and StandardRoIHead')
     mmdet_imported = False
 
 if mmdet_imported:
@@ -86,5 +83,6 @@ def simple_test_bboxes(self,
             return det_bboxes, det_labels
 else:
     # Just define an empty class, so that __init__ can import it.
+    @import_module_error_class('mmdet')
     class AVARoIHead:
         pass

mmaction/models/roi_extractors/single_straight3d.py

@@ -1,18 +1,25 @@
-import warnings
-
 import torch
 import torch.nn as nn
 
+from mmaction.utils import import_module_error_class
+
 try:
     from mmcv.ops import RoIAlign, RoIPool
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmcv-full to use RoIAlign and RoIPool')
+
+    @import_module_error_class('mmcv-full')
+    class RoIAlign(nn.Module):
+        pass
+
+    @import_module_error_class('mmcv-full')
+    class RoIPool(nn.Module):
+        pass
+
 
 try:
     from mmdet.models import ROI_EXTRACTORS
     mmdet_imported = True
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use ROI_EXTRACTORS')
     mmdet_imported = False
 
 

mmaction/utils/__init__.py

@@ -1,10 +1,12 @@
 from .collect_env import collect_env
+from .decorators import import_module_error_class, import_module_error_func
 from .gradcam_utils import GradCAM
 from .logger import get_root_logger
 from .misc import get_random_string, get_shm_dir, get_thread_id
 from .precise_bn import PreciseBNHook
 
 __all__ = [
     'get_root_logger', 'collect_env', 'get_random_string', 'get_thread_id',
-    'get_shm_dir', 'GradCAM', 'PreciseBNHook'
+    'get_shm_dir', 'GradCAM', 'PreciseBNHook', 'import_module_error_class',
+    'import_module_error_func'
 ]

mmaction/utils/decorators.py

@@ -0,0 +1,33 @@
+from types import MethodType
+
+
+def import_module_error_func(module_name):
+    """When a function is imported incorrectly due to a missing module, raise
+    an import error when the function is called."""
+
+    def decorate(func):
+
+        def new_func(*args, **kwargs):
+            raise ImportError(
+                f'Please install {module_name} to use {func.__name__}.')
+            return func(*args, **kwargs)
+
+        return new_func
+
+    return decorate
+
+
+def import_module_error_class(module_name):
+    """When a class is imported incorrectly due to a missing module, raise an
+    import error when the class is instantiated."""
+
+    def decorate(cls):
+
+        def import_error_init(*args, **kwargs):
+            raise ImportError(
+                f'Please install {module_name} to use {cls.__name__}.')
+
+        cls.__init__ = MethodType(import_error_init, cls)
+        return cls
+
+    return decorate

tests/test_utils/test_bbox.py

@@ -1,17 +1,24 @@
 import os.path as osp
-import warnings
 from abc import abstractproperty
 
 import numpy as np
 import torch
 
 from mmaction.core.bbox import bbox2result, bbox_target
 from mmaction.datasets import AVADataset
+from mmaction.utils import import_module_error_func
 
 try:
     from mmdet.core.bbox import build_assigner, build_sampler
 except (ImportError, ModuleNotFoundError):
-    warnings.warn('Please install mmdet to use build_assigner, build_sampler')
+
+    @import_module_error_func('mmdet')
+    def build_assigner(*args, **kwargs):
+        pass
+
+    @import_module_error_func('mmdet')
+    def build_sampler(*args, **kwargs):
+        pass
 
 
 def test_assigner_sampler():

tests/test_utils/test_decorator.py

@@ -0,0 +1,32 @@
+import pytest
+
+from mmaction.utils import import_module_error_class, import_module_error_func
+
+
+def test_import_module_error_class():
+
+    @import_module_error_class('mmdet')
+    class ExampleClass:
+        pass
+
+    with pytest.raises(ImportError):
+        ExampleClass()
+
+    @import_module_error_class('mmdet')
+    class ExampleClass:
+
+        def __init__(self, a, b=3):
+            self.c = a + b
+
+    with pytest.raises(ImportError):
+        ExampleClass(4)
+
+
+def test_import_module_error_func():
+
+    @import_module_error_func('_add')
+    def ExampleFunc(a, b):
+        return a + b
+
+    with pytest.raises(ImportError):
+        ExampleFunc(3, 4)