diff --git a/rl_games/algos_torch/network_builder.py b/rl_games/algos_torch/network_builder.py
index 4600f016..284b0305 100644
--- a/rl_games/algos_torch/network_builder.py
+++ b/rl_games/algos_torch/network_builder.py
@@ -1181,21 +1181,17 @@ def __init__(self, params, **kwargs):
 
         def forward(self, obs_dict):
             if self.proprio_size > 0:
-                obs = obs_dict['camera']
-                proprio = obs_dict['proprio']
+                obs = obs_dict['obs']['camera']
+                proprio = obs_dict['obs']['proprio']
             else:
                 obs = obs_dict['obs']
 
-            # print('obs.shape: ', obs.shape)
             if self.permute_input:
                 obs = obs.permute((0, 3, 1, 2))
 
             if self.preprocess_image:
                 obs = preprocess_image(obs)
 
-            # Assuming your input image is a tensor or PIL image, resize it to 224x224
-            #obs = self.resize_transform(obs)
-
             dones = obs_dict.get('dones', None)
             bptt_len = obs_dict.get('bptt_len', 0)
             states = obs_dict.get('rnn_states', None)
@@ -1203,7 +1199,6 @@ def forward(self, obs_dict):
             out = obs
             out = self.cnn(out)
             out = out.flatten(1)
-
             out = self.flatten_act(out)
 
             if self.proprio_size > 0:
@@ -1298,9 +1293,9 @@ def _build_backbone(self, input_shape, backbone_params):
 
                 # TODO: add low-res parameter
                 backbone.conv1 = nn.Conv2d(input_shape[0], 64, kernel_size=3, stride=1, padding=1, bias=False)
-                #backbone.maxpool = nn.Identity()
+                # backbone.maxpool = nn.Identity()
                 # if input_shape[0] != 3:
-                #     model.conv1 = nn.Conv2d(input_shape[0], 64, kernel_size=7, stride=2, padding=3, bias=False)
+                #     backbone.conv1 = nn.Conv2d(input_shape[0], 64, kernel_size=7, stride=2, padding=3, bias=False)
                 # Remove the fully connected layer
                 backbone_output_size = backbone.fc.in_features
                 print('backbone_output_size: ', backbone_output_size)