add mplugowl model

mmpretrain/models/multimodal/mplugowl/mplugowl.py

@@ -562,9 +562,9 @@ class MplugOwlVisualAbstractorAttention(BaseModel):
 
 
 class MplugOwlVisualAbstractorLayer(BaseModel):
-    def __init__(self,layer_idx, hidden_size=1024,num_attention_heads=16,intermediate_size=4096,attention_probs_dropout_prob=0.1,layer_norm_eps=1e-6,encoder_hidden_size=1024):
+    def __init__(self,layer_idx, hidden_size=1024,num_attention_heads=16,intermediate_size=4096,attention_probs_dropout_prob=0.1,layer_norm_eps=1e-6,encoder_hidden_size=1024,chunk_size_feed_forward=None):
         super().__init__()
-        self.chunk_size_feed_forward = None
+        self.chunk_size_feed_forward = chunk_size_feed_forward
         self.seq_len_dim = 1
 
         self.layer_idx = layer_idx
@@ -661,12 +661,11 @@ class MplugOwlVisualAbstractorEncoder(BaseModel):
 
 
 class MplugOwlVisualAbstractorModel(BaseModel):
-    def __init__(self, config: MplugOwlVisualAbstractorConfig, language_hidden_size):
-        super().__init__(config)
-        self.config = config
+    def __init__(self, language_hidden_size, num_hidden_layers=6, hidden_size=1024,num_attention_heads=16,intermediate_size=4096,attention_probs_dropout_prob=0.1,layer_norm_eps=1e-6,encoder_hidden_size=1024):
+        super().__init__()
 
-        self.encoder = MplugOwlVisualAbstractorEncoder(config)
-        self.visual_fc = torch.nn.Linear(config.hidden_size, language_hidden_size)
+        self.encoder = MplugOwlVisualAbstractorEncoder(num_hidden_layers, hidden_size,num_attention_heads,intermediate_size,attention_probs_dropout_prob,layer_norm_eps,encoder_hidden_size)
+        self.visual_fc = torch.nn.Linear(hidden_size, language_hidden_size)
         self.vit_eos = torch.nn.Parameter(torch.randn(1, 1, language_hidden_size))
         nn.init.trunc_normal_(self.vit_eos, mean=0.0, std=self.config.initializer_range)
         self.post_init()
@@ -824,8 +823,8 @@ class MplugOwlVisualAbstractorModel(BaseModel):
         )
 
 
-class MplugOwlModel(MplugOwlPreTrainedModel):
-    config_class = MplugOwlConfig
+@MODELS.register_module()
+class MplugOwlModel(BaseModel):
     main_input_name = "pixel_values"
 
     def __init__(self, config: MplugOwlConfig, *inputs, **kwargs):
@@ -1080,9 +1079,4 @@ def bloom_forward(
         attentions=all_self_attentions,
     )
 
-@MODELS.register_module()
-class mPLUGOwl(BaseModel):
-    def __init__(self,):
-        pass
-