hotfix(nyz): fix qacd model style

ding/model/template/qacd.py

@@ -2,11 +2,11 @@ from typing import Union, Dict, Optional
 import torch
 import torch.nn as nn
 
-from ding.utils import SequenceType, squeeze, MODEL_REGISTRY
 from ding.utils import SequenceType, squeeze, MODEL_REGISTRY
 from ..common import ReparameterizationHead, RegressionHead, DiscreteHead, MultiHead, \
     FCEncoder, ConvEncoder
 
+
 @MODEL_REGISTRY.register('qacd')
 class QACD(nn.Module):
     r"""
@@ -62,27 +62,22 @@ class QACD(nn.Module):
             )
 
         self.actor_encoder = encoder_cls(
-                obs_shape, encoder_hidden_size_list, activation=activation, norm_type=norm_type
-            )
+            obs_shape, encoder_hidden_size_list, activation=activation, norm_type=norm_type
+        )
         self.critic_encoder = encoder_cls(
-                obs_shape, encoder_hidden_size_list, activation=activation, norm_type=norm_type
-            )
+            obs_shape, encoder_hidden_size_list, activation=activation, norm_type=norm_type
+        )
 
         self.critic_head = RegressionHead(
-            critic_head_hidden_size,action_shape,critic_head_layer_num,activation=activation,norm_type=norm_type
+            critic_head_hidden_size, action_shape, critic_head_layer_num, activation=activation, norm_type=norm_type
         )
         self.actor_head = DiscreteHead(
-            actor_head_hidden_size,
-            action_shape,
-            actor_head_layer_num,
-            activation=activation,
-            norm_type=norm_type
+            actor_head_hidden_size, action_shape, actor_head_layer_num, activation=activation, norm_type=norm_type
         )
         self.actor = [self.actor_encoder, self.actor_head]
         self.critic = [self.critic_encoder, self.critic_head]
         self.actor = nn.ModuleList(self.actor)
         self.critic = nn.ModuleList(self.critic)
-        
 
     def forward(self, inputs: Union[torch.Tensor, Dict], mode: str) -> Dict:
         r"""