Delete deprecated warning in FPN (open-mmlab#5311)

* deprecated warning in FPN

* modify doc string

* modify related files

Author: AronLin

configs/autoassign/autoassign_r50_fpn_8x2_1x_coco.py

@@ -22,7 +22,6 @@
         out_channels=256,
         start_level=1,
         add_extra_convs=True,
-        extra_convs_on_inputs=True,
         num_outs=5,
         relu_before_extra_convs=True,
         init_cfg=dict(type='Caffe2Xavier', layer='Conv2d')),

configs/fcos/fcos_r50_caffe_fpn_gn-head_1x_coco.py

@@ -20,8 +20,7 @@
         in_channels=[256, 512, 1024, 2048],
         out_channels=256,
         start_level=1,
-        add_extra_convs=True,
-        extra_convs_on_inputs=False,  # use P5
+        add_extra_convs='on_output',  # use P5
         num_outs=5,
         relu_before_extra_convs=True),
     bbox_head=dict(

configs/vfnet/vfnet_r50_fpn_1x_coco.py

@@ -20,8 +20,7 @@
         in_channels=[256, 512, 1024, 2048],
         out_channels=256,
         start_level=1,
-        add_extra_convs=True,
-        extra_convs_on_inputs=False,  # use P5
+        add_extra_convs='on_output',  # use P5
         num_outs=5,
         relu_before_extra_convs=True),
     bbox_head=dict(

mmdet/models/necks/fpn.py

@@ -1,5 +1,3 @@
-import warnings
-
 import torch.nn as nn
 import torch.nn.functional as F
 from mmcv.cnn import ConvModule
@@ -25,17 +23,13 @@ class FPN(BaseModule):
             build the feature pyramid. Default: -1, which means the last level.
         add_extra_convs (bool | str): If bool, it decides whether to add conv
             layers on top of the original feature maps. Default to False.
-            If True, its actual mode is specified by `extra_convs_on_inputs`.
+            If True, it is equivalent to `add_extra_convs='on_input'`.
             If str, it specifies the source feature map of the extra convs.
             Only the following options are allowed
 
             - 'on_input': Last feat map of neck inputs (i.e. backbone feature).
             - 'on_lateral':  Last feature map after lateral convs.
             - 'on_output': The last output feature map after fpn convs.
-        extra_convs_on_inputs (bool, deprecated): Whether to apply extra convs
-            on the original feature from the backbone. If True,
-            it is equivalent to `add_extra_convs='on_input'`. If False, it is
-            equivalent to set `add_extra_convs='on_output'`. Default to True.
         relu_before_extra_convs (bool): Whether to apply relu before the extra
             conv. Default: False.
         no_norm_on_lateral (bool): Whether to apply norm on lateral.
@@ -71,7 +65,6 @@ def __init__(self,
                  start_level=0,
                  end_level=-1,
                  add_extra_convs=False,
-                 extra_convs_on_inputs=True,
                  relu_before_extra_convs=False,
                  no_norm_on_lateral=False,
                  conv_cfg=None,
@@ -107,15 +100,7 @@ def __init__(self,
             # Extra_convs_source choices: 'on_input', 'on_lateral', 'on_output'
             assert add_extra_convs in ('on_input', 'on_lateral', 'on_output')
         elif add_extra_convs:  # True
-            if extra_convs_on_inputs:
-                # TODO: deprecate `extra_convs_on_inputs`
-                warnings.simplefilter('once')
-                warnings.warn(
-                    '"extra_convs_on_inputs" will be deprecated in v2.9.0,'
-                    'Please use "add_extra_convs"', DeprecationWarning)
-                self.add_extra_convs = 'on_input'
-            else:
-                self.add_extra_convs = 'on_output'
+            self.add_extra_convs = 'on_input'
 
         self.lateral_convs = nn.ModuleList()
         self.fpn_convs = nn.ModuleList()

mmdet/models/necks/pafpn.py

@@ -22,10 +22,15 @@ class PAFPN(FPN):
             build the feature pyramid. Default: 0.
         end_level (int): Index of the end input backbone level (exclusive) to
             build the feature pyramid. Default: -1, which means the last level.
-        add_extra_convs (bool): Whether to add conv layers on top of the
-            original feature maps. Default: False.
-        extra_convs_on_inputs (bool): Whether to apply extra conv on
-            the original feature from the backbone. Default: False.
+        add_extra_convs (bool | str): If bool, it decides whether to add conv
+            layers on top of the original feature maps. Default to False.
+            If True, it is equivalent to `add_extra_convs='on_input'`.
+            If str, it specifies the source feature map of the extra convs.
+            Only the following options are allowed
+
+            - 'on_input': Last feat map of neck inputs (i.e. backbone feature).
+            - 'on_lateral':  Last feature map after lateral convs.
+            - 'on_output': The last output feature map after fpn convs.
         relu_before_extra_convs (bool): Whether to apply relu before the extra
             conv. Default: False.
         no_norm_on_lateral (bool): Whether to apply norm on lateral.
@@ -44,7 +49,6 @@ def __init__(self,
                  start_level=0,
                  end_level=-1,
                  add_extra_convs=False,
-                 extra_convs_on_inputs=True,
                  relu_before_extra_convs=False,
                  no_norm_on_lateral=False,
                  conv_cfg=None,
@@ -59,7 +63,6 @@ def __init__(self,
             start_level,
             end_level,
             add_extra_convs,
-            extra_convs_on_inputs,
             relu_before_extra_convs,
             no_norm_on_lateral,
             conv_cfg,

tests/test_models/test_necks.py

@@ -169,38 +169,6 @@ def test_fpn():
         outs[i].shape[1] == out_channels
         outs[i].shape[2] == outs[i].shape[3] == s // (2**i)
 
-    # extra_convs_on_inputs=False is equal to extra convs source is 'on_output'
-    fpn_model = FPN(
-        in_channels=in_channels,
-        out_channels=out_channels,
-        add_extra_convs=True,
-        extra_convs_on_inputs=False,
-        start_level=1,
-        num_outs=5,
-    )
-    assert fpn_model.add_extra_convs == 'on_output'
-    outs = fpn_model(feats)
-    assert len(outs) == fpn_model.num_outs
-    for i in range(fpn_model.num_outs):
-        outs[i].shape[1] == out_channels
-        outs[i].shape[2] == outs[i].shape[3] == s // (2**i)
-
-    # extra_convs_on_inputs=True is equal to extra convs source is 'on_input'
-    fpn_model = FPN(
-        in_channels=in_channels,
-        out_channels=out_channels,
-        add_extra_convs=True,
-        extra_convs_on_inputs=True,
-        start_level=1,
-        num_outs=5,
-    )
-    assert fpn_model.add_extra_convs == 'on_input'
-    outs = fpn_model(feats)
-    assert len(outs) == fpn_model.num_outs
-    for i in range(fpn_model.num_outs):
-        outs[i].shape[1] == out_channels
-        outs[i].shape[2] == outs[i].shape[3] == s // (2**i)
-
 
 def test_channel_mapper():
     """Tests ChannelMapper."""