fix(PatchTST): Wrong dropout used for PretainHead (#31117)

* fix(PatchTST): Wrong dropout used for PretainHead

* feat(PatchTST): remove unused config.dropout

---------
Co-authored-by: Strobel Maximilian (IFAG PSS SIS SCE ACM) <Maximilian.Strobel@infineon.com>

src/transformers/models/patchtst/configuration_patchtst.py

@@ -67,8 +67,6 @@ class PatchTSTConfig(PretrainedConfig):
             A value added to the denominator for numerical stability of normalization.
         attention_dropout (`float`, *optional*, defaults to 0.0):
             The dropout probability for the attention probabilities.
-        dropout (`float`, *optional*, defaults to 0.0):
-            The dropout probability for all fully connected layers in the Transformer.
         positional_dropout (`float`, *optional*, defaults to 0.0):
             The dropout probability in the positional embedding layer.
         path_dropout (`float`, *optional*, defaults to 0.0):
@@ -167,7 +165,6 @@ class PatchTSTConfig(PretrainedConfig):
         norm_type: str = "batchnorm",
         norm_eps: float = 1e-05,
         attention_dropout: float = 0.0,
-        dropout: float = 0.0,
         positional_dropout: float = 0.0,
         path_dropout: float = 0.0,
         ff_dropout: float = 0.0,
@@ -209,7 +206,6 @@ class PatchTSTConfig(PretrainedConfig):
         self.num_attention_heads = num_attention_heads
         self.ffn_dim = ffn_dim
         self.num_hidden_layers = num_hidden_layers
-        self.dropout = dropout
         self.attention_dropout = attention_dropout
         self.share_embedding = share_embedding
         self.channel_attention = channel_attention

src/transformers/models/patchtst/modeling_patchtst.py

@@ -1262,7 +1262,7 @@ class PatchTSTMaskPretrainHead(nn.Module):
 
     def __init__(self, config: PatchTSTConfig):
         super().__init__()
-        self.dropout = nn.Dropout(config.dropout)
+        self.dropout = nn.Dropout(config.head_dropout) if config.head_dropout > 0 else nn.Identity()
         self.linear = nn.Linear(config.d_model, config.patch_length)
         self.use_cls_token = config.use_cls_token