Update patched_mha_with_cache.py

GPT_SoVITS/AR/modules/patched_mha_with_cache.py

@@ -12,33 +12,33 @@ import torch
 
 
 def multi_head_attention_forward_patched(
-    query: Tensor,
+    query,
-    key: Tensor,
+    key,
-    value: Tensor,
+    value,
-    embed_dim_to_check: int,
+    embed_dim_to_check,
-    num_heads: int,
+    num_heads,
-    in_proj_weight: Optional[Tensor],
+    in_proj_weight,
-    in_proj_bias: Optional[Tensor],
+    in_proj_bias,
-    bias_k: Optional[Tensor],
+    bias_k,
-    bias_v: Optional[Tensor],
+    bias_v,
-    add_zero_attn: bool,
+    add_zero_attn,
     dropout_p: float,
-    out_proj_weight: Tensor,
+    out_proj_weight,
-    out_proj_bias: Optional[Tensor],
+    out_proj_bias,
-    training: bool = True,
+    training = True,
-    key_padding_mask: Optional[Tensor] = None,
+    key_padding_mask = None,
-    need_weights: bool = True,
+    need_weights = True,
-    attn_mask: Optional[Tensor] = None,
+    attn_mask = None,
-    use_separate_proj_weight: bool = False,
+    use_separate_proj_weight = False,
-    q_proj_weight: Optional[Tensor] = None,
+    q_proj_weight = None,
-    k_proj_weight: Optional[Tensor] = None,
+    k_proj_weight = None,
-    v_proj_weight: Optional[Tensor] = None,
+    v_proj_weight = None,
-    static_k: Optional[Tensor] = None,
+    static_k = None,
-    static_v: Optional[Tensor] = None,
+    static_v = None,
-    average_attn_weights: bool = True,
+    average_attn_weights = True,
-    is_causal: bool = False,
+    is_causal = False,
     cache=None,
-) -> Tuple[Tensor, Optional[Tensor]]:
+):
     r"""
     Args:
         query, key, value: map a query and a set of key-value pairs to an output.