fix errors for prompt tuning and bitfit

jxhe · jxhe · commit a45ccf4f879e · 2022-03-17T20:41:11.000-04:00
diff --git a/src/transformers/models/bart/modeling_bart.py b/src/transformers/models/bart/modeling_bart.py
@@ -182,8 +182,8 @@ def __init__(
                                                  bottleneck=self.config.attn_bn,
                                                  adapter_layernorm_option="in",
                                                  )
-        elif self.attn_mode != 'none':
-            raise ValueError("att_mode not supported")
+        # elif self.attn_mode != 'none':
+        #     raise ValueError("att_mode not supported")
 
     def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):
         return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous()
diff --git a/src/transformers/models/mbart/modeling_mbart.py b/src/transformers/models/mbart/modeling_mbart.py
@@ -185,8 +185,8 @@ def __init__(
                                                  bottleneck=self.config.attn_bn,
                                                  adapter_layernorm_option="in",
                                                  )
-        elif self.attn_mode != 'none':
-                raise ValueError("att_mode not supported")
+        # elif self.attn_mode != 'none':
+        #         raise ValueError("att_mode not supported")
 
 
     def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):

Original file line number	Diff line number	Diff line change
`@@ -185,8 +185,8 @@ def __init__(`
`185`	`185`	`bottleneck=self.config.attn_bn,`
`186`	`186`	`adapter_layernorm_option="in",`
`187`	`187`	`)`
`188`		`- elif self.attn_mode != 'none':`
`189`		`- raise ValueError("att_mode not supported")`
	`188`	`+ # elif self.attn_mode != 'none':`
	`189`	`+ # raise ValueError("att_mode not supported")`
`190`	`190`
`191`	`191`
`192`	`192`	`def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int):`