Merge pull request #123 from aclex/mobilenetv3_fix_feature_extraction

Merge changes in feature extraction interface to MobileNetV3

Author: rwightman

timm/models/mobilenetv3.py

@@ -148,7 +148,7 @@ class MobileNetV3Features(nn.Module):
     and object detection models.
     """
 
-    def __init__(self, block_args, out_indices=(0, 1, 2, 3, 4), feature_location='pre_pwl',
+    def __init__(self, block_args, out_indices=(0, 1, 2, 3, 4), feature_location='bottleneck',
                  in_chans=3, stem_size=16, channel_multiplier=1.0, output_stride=32, pad_type='',
                  act_layer=nn.ReLU, drop_rate=0., drop_path_rate=0., se_kwargs=None,
                  norm_layer=nn.BatchNorm2d, norm_kwargs=None):
@@ -174,34 +174,47 @@ def __init__(self, block_args, out_indices=(0, 1, 2, 3, 4), feature_location='pr
             channel_multiplier, 8, None, output_stride, pad_type, act_layer, se_kwargs,
             norm_layer, norm_kwargs, drop_path_rate, feature_location=feature_location, verbose=_DEBUG)
         self.blocks = nn.Sequential(*builder(self._in_chs, block_args))
-        self.feature_info = builder.features  # builder provides info about feature channels for each block
+        self._feature_info = builder.features  # builder provides info about feature channels for each block
+        self._stage_to_feature_idx = {
+            v['stage_idx']: fi for fi, v in self._feature_info.items() if fi in self.out_indices}
         self._in_chs = builder.in_chs
 
         efficientnet_init_weights(self)
         if _DEBUG:
-            for k, v in self.feature_info.items():
+            for k, v in self._feature_info.items():
                 print('Feature idx: {}: Name: {}, Channels: {}'.format(k, v['name'], v['num_chs']))
 
         # Register feature extraction hooks with FeatureHooks helper
-        hook_type = 'forward_pre' if feature_location == 'pre_pwl' else 'forward'
-        hooks = [dict(name=self.feature_info[idx]['name'], type=hook_type) for idx in out_indices]
-        self.feature_hooks = FeatureHooks(hooks, self.named_modules())
+        self.feature_hooks = None
+        if feature_location != 'bottleneck':
+            hooks = [dict(
+                name=self._feature_info[idx]['module'],
+                type=self._feature_info[idx]['hook_type']) for idx in out_indices]
+            self.feature_hooks = FeatureHooks(hooks, self.named_modules())
 
     def feature_channels(self, idx=None):
         """ Feature Channel Shortcut
         Returns feature channel count for each output index if idx == None. If idx is an integer, will
         return feature channel count for that feature block index (independent of out_indices setting).
         """
         if isinstance(idx, int):
-            return self.feature_info[idx]['num_chs']
-        return [self.feature_info[i]['num_chs'] for i in self.out_indices]
+            return self._feature_info[idx]['num_chs']
+        return [self._feature_info[i]['num_chs'] for i in self.out_indices]
 
     def forward(self, x):
         x = self.conv_stem(x)
         x = self.bn1(x)
         x = self.act1(x)
-        self.blocks(x)
-        return self.feature_hooks.get_output(x.device)
+        if self.feature_hooks is None:
+            features = []
+            for i, b in enumerate(self.blocks):
+                x = b(x)
+                if i in self._stage_to_feature_idx:
+                    features.append(x)
+            return features
+        else:
+            self.blocks(x)
+            return self.feature_hooks.get_output(x.device)
 
 
 def _create_model(model_kwargs, default_cfg, pretrained=False):