From 1a14676b1570ab872ac7a7d1d467f19b7a41def6 Mon Sep 17 00:00:00 2001
From: tpoisonooo <khj.application@aliyun.com>
Date: Tue, 17 May 2022 16:30:23 +0800
Subject: [PATCH] fix(pytorch/ops/linear.py): bias maybe None

---
 csrc/backend_ops/ncnn/onnx2ncnn/onnx2ncnn.cpp |  2 +-
 mmdeploy/pytorch/ops/linear.py                | 19 +++++--------------
 2 files changed, 6 insertions(+), 15 deletions(-)

diff --git a/csrc/backend_ops/ncnn/onnx2ncnn/onnx2ncnn.cpp b/csrc/backend_ops/ncnn/onnx2ncnn/onnx2ncnn.cpp
index 0ea4e26d90..d78b883125 100644
--- a/csrc/backend_ops/ncnn/onnx2ncnn/onnx2ncnn.cpp
+++ b/csrc/backend_ops/ncnn/onnx2ncnn/onnx2ncnn.cpp
@@ -1304,7 +1304,7 @@ int main(int argc, char** argv) {
       }
       fprintf(pp, " 0=%d", axis);
     } else if (op == "Gelu") {
-      fprintf(pp, " 0=0");
+      fprintf(pp, " 0=1");
     } else if (op == "Gemm") {
       float alpha = get_node_attr_f(node, "alpha", 1.f);
       float beta = get_node_attr_f(node, "beta", 1.f);
diff --git a/mmdeploy/pytorch/ops/linear.py b/mmdeploy/pytorch/ops/linear.py
index 25e65b41f8..8cb997b400 100644
--- a/mmdeploy/pytorch/ops/linear.py
+++ b/mmdeploy/pytorch/ops/linear.py
@@ -13,14 +13,8 @@ def linear_no_bias(g, input, weight):
 
     PyTorch `nn.Linear` will be exported as ONNX node 'Gemm'.
     """
-    g.op(
-        'mmdeploy::Gemm',
-        input,
-        weight,
-        alpha_f=1.0,
-        beta_f=1.0,
-        transA_i=0,
-        transB_i=1)
+    return g.op(
+        'Gemm', input, weight, alpha_f=1.0, beta_f=1.0, transA_i=0, transB_i=1)
 
 
 @parse_args('v', 'v', 'v', 'f', 'f', 'i', 'i')
@@ -29,8 +23,8 @@ def linear_normal(g, input, weight, bias):
 
     PyTorch `nn.Linear` will be exported as ONNX node 'Gemm'.
     """
-    g.op(
-        'mmdeploy::Gemm',
+    return g.op(
+        'Gemm',
         input,
         weight,
         bias,
@@ -41,10 +35,7 @@ def linear_normal(g, input, weight, bias):
 
 
 @SYMBOLIC_REWRITER.register_symbolic(
-    'torch.nn.functional.linear',
-    is_pytorch=True,
-    # arg_descriptors=['v', 'v', 'v', 'f', 'f', 'i', 'i'],
-    backend=Backend.NCNN.value)
+    'linear', is_pytorch=True, backend=Backend.NCNN.value)
 def linear__ncnn(ctx, g, input, weight, bias):
     """Support export linear This rewrite enable export Gemm."""
     if bias is None: