[bart] rename self-attention -> attention (#6708)

src/transformers/modeling_bart.py

@@ -225,11 +225,7 @@ class EncoderLayer(nn.Module):
     def __init__(self, config: BartConfig):
         super().__init__()
         self.embed_dim = config.d_model
-        self.self_attn = SelfAttention(
-            self.embed_dim,
-            config.encoder_attention_heads,
-            dropout=config.attention_dropout,
-        )
+        self.self_attn = Attention(self.embed_dim, config.encoder_attention_heads, dropout=config.attention_dropout)
         self.normalize_before = config.normalize_before
         self.self_attn_layer_norm = LayerNorm(self.embed_dim)
         self.dropout = config.dropout
@@ -377,7 +373,8 @@ class DecoderLayer(nn.Module):
     def __init__(self, config: BartConfig):
         super().__init__()
         self.embed_dim = config.d_model
-        self.self_attn = SelfAttention(
+
+        self.self_attn = Attention(
             embed_dim=self.embed_dim,
             num_heads=config.decoder_attention_heads,
             dropout=config.attention_dropout,
@@ -388,7 +385,7 @@ class DecoderLayer(nn.Module):
         self.normalize_before = config.normalize_before
 
         self.self_attn_layer_norm = LayerNorm(self.embed_dim)
-        self.encoder_attn = SelfAttention(
+        self.encoder_attn = Attention(
             self.embed_dim,
             config.decoder_attention_heads,
             dropout=config.attention_dropout,
@@ -586,7 +583,7 @@ class BartDecoder(nn.Module):
             if use_cache:
                 next_decoder_cache.append(layer_past.copy())
 
-            if self.layer_norm and (idx == len(self.layers) - 1):  # last layer of mbart
+            if self.layer_norm and (idx == len(self.layers) - 1):  # if config.add_final_layer_norm (mBART)
                 x = self.layer_norm(x)
             if output_attentions:
                 all_self_attns += (layer_self_attn,)
@@ -616,7 +613,7 @@ def _reorder_buffer(attn_cache, new_order):
     return attn_cache
 
 
-class SelfAttention(nn.Module):
+class Attention(nn.Module):
     """Multi-headed attention from 'Attention Is All You Need' paper"""
 
     def __init__(