diff --git a/maskrcnn_benchmark/modeling/language_backbone/modeling_bert_new.py b/maskrcnn_benchmark/modeling/language_backbone/modeling_bert_new.py
index 5a1e8f4..3cbcc2a 100644
--- a/maskrcnn_benchmark/modeling/language_backbone/modeling_bert_new.py
+++ b/maskrcnn_benchmark/modeling/language_backbone/modeling_bert_new.py
@@ -136,10 +136,10 @@ class MaskedCrossAttention(nn.Module):
         norm_kv = False,
         share_kv=False,
         cfg=None,
-        spare_forward=False, 
+        spase_forward=False, 
     ):
         super().__init__()
-        self.spare_forward=spare_forward
+        self.spase_forward=spase_forward
         self.scale = dim_head ** -0.5
         self.heads = heads
         self.share_kv=share_kv
@@ -189,7 +189,7 @@ class MaskedCrossAttention(nn.Module):
         vision, # (batch, vision, dim)
         attention_mask = None, # (batch, vision, text)
     ):
-        if self.spare_forward:
+        if self.spase_forward:
             batch_size = x.shape[0]
             x, vision, attention_mask = self._construct_sparse_inputs(x, vision, attention_mask)
 
@@ -233,7 +233,7 @@ class MaskedCrossAttention(nn.Module):
         out = einsum('... i j, ... j d -> ... i d', attn, v)
         out = rearrange(out, 'b h n d -> b n (h d)')
 
-        if self.spare_forward:
+        if self.spase_forward:
             assert out.shape[1]==1
             out = rearrange(out, '(b t) n d -> b t (n d)', b=batch_size)
 
@@ -265,7 +265,7 @@ class GatedCrossAttentionBlock(nn.Module):
         enable_ffn = True
     ):
         super().__init__()
-        self.attn = MaskedCrossAttention(input_dim = dim, dim_head = dim_head, heads = heads, share_kv=share_kv, cfg=cfg, norm_kv=True, spare_forward=True)
+        self.attn = MaskedCrossAttention(input_dim = dim, dim_head = dim_head, heads = heads, share_kv=share_kv, cfg=cfg, norm_kv=True, spase_forward=True)
         if cfg.VISION_QUERY.FIX_ATTN_GATE == -1.0:
             if cfg.VISION_QUERY.CONDITION_GATE:
                 if cfg.VISION_QUERY.NONLINEAR_GATE:
@@ -387,7 +387,7 @@ class PreSelectBlock(nn.Module):
         cfg=None,
     ):
         super().__init__()
-        self.image_condition = MaskedCrossAttention(input_dim = dim, output_dim = out_dim, dim_head = dim_head, heads = heads, norm_kv=True, share_kv=share_kv, cfg=cfg, spare_forward=False)
+        self.image_condition = MaskedCrossAttention(input_dim = dim, output_dim = out_dim, dim_head = dim_head, heads = heads, norm_kv=True, share_kv=share_kv, cfg=cfg, spase_forward=False)
         self.ff = FeedForward(out_dim, mult = ff_mult)
 
         if dim != out_dim: