innerproduct allow 1 height gemm (#4730)

src/layer/arm/innerproduct_arm.cpp

@@ -177,7 +177,7 @@ int InnerProduct_arm::forward(const Mat& bottom_blob, Mat& top_blob, const Optio
 
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -889,7 +889,7 @@ int InnerProduct_arm::forward_bf16s(const Mat& bottom_blob, Mat& top_blob, const
 {
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -1295,7 +1295,7 @@ int InnerProduct_arm::forward_int8_arm(const Mat& bottom_blob, Mat& top_blob, co
         quantize_to_int8(bottom_blob, bottom_blob_int8, bottom_blob_int8_scales, opt_q);
     }
 
-    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input && bottom_blob_int8.h * bottom_blob_int8.elempack > 1)
+    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input)
     {
         // gemm
         Mat bottom_blob_int8_unpacked;

src/layer/arm/innerproduct_arm_asimdhp.cpp

@@ -53,7 +53,7 @@ int InnerProduct_arm::forward_fp16sa(const Mat& bottom_blob, Mat& top_blob, cons
 {
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;

src/layer/arm/innerproduct_arm_vfpv4.cpp

@@ -53,7 +53,7 @@ int InnerProduct_arm::forward_fp16s(const Mat& bottom_blob, Mat& top_blob, const
 {
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;

src/layer/innerproduct.cpp

@@ -115,7 +115,7 @@ int InnerProduct::forward(const Mat& bottom_blob, Mat& top_blob, const Option& o
     size_t elemsize = bottom_blob.elemsize;
     int size = w * h;
 
-    if (bottom_blob.dims == 2 && w == num_input && h > 1)
+    if (bottom_blob.dims == 2 && w == num_input)
     {
         // gemm
         top_blob.create(num_output, h, elemsize, opt.blob_allocator);
@@ -201,7 +201,7 @@ int InnerProduct::forward_int8(const Mat& bottom_blob, Mat& top_blob, const Opti
         quantize_to_int8(bottom_blob, bottom_blob_int8, bottom_blob_int8_scales, opt_g);
     }
 
-    if (bottom_blob.dims == 2 && w == num_input && h > 1)
+    if (bottom_blob.dims == 2 && w == num_input)
     {
         // gemm
         top_blob.create(num_output, h, 4u, opt.blob_allocator);

src/layer/loongarch/innerproduct_loongarch.cpp

@@ -137,7 +137,7 @@ int InnerProduct_loongarch::forward(const Mat& bottom_blob, Mat& top_blob, const
 
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -667,7 +667,7 @@ int InnerProduct_loongarch::forward_fp16s(const Mat& bottom_blob, Mat& top_blob,
 {
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -1168,7 +1168,7 @@ int InnerProduct_loongarch::forward_int8_loongarch(const Mat& bottom_blob, Mat&
         quantize_to_int8(bottom_blob, bottom_blob_int8, bottom_blob_int8_scales, opt_q);
     }
 
-    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input && bottom_blob_int8.h * bottom_blob_int8.elempack > 1)
+    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input)
     {
         // gemm
         Mat bottom_blob_int8_unpacked;

src/layer/mips/innerproduct_mips.cpp

@@ -137,7 +137,7 @@ int InnerProduct_mips::forward(const Mat& bottom_blob, Mat& top_blob, const Opti
 
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -667,7 +667,7 @@ int InnerProduct_mips::forward_fp16s(const Mat& bottom_blob, Mat& top_blob, cons
 {
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -1168,7 +1168,7 @@ int InnerProduct_mips::forward_int8_mips(const Mat& bottom_blob, Mat& top_blob,
         quantize_to_int8(bottom_blob, bottom_blob_int8, bottom_blob_int8_scales, opt_q);
     }
 
-    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input && bottom_blob_int8.h * bottom_blob_int8.elempack > 1)
+    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input)
     {
         // gemm
         Mat bottom_blob_int8_unpacked;

src/layer/riscv/innerproduct_riscv.cpp

@@ -173,7 +173,7 @@ int InnerProduct_riscv::forward(const Mat& bottom_blob, Mat& top_blob, const Opt
 
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -577,7 +577,7 @@ int InnerProduct_riscv::forward_fp16s(const Mat& bottom_blob, Mat& top_blob, con
 
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -839,7 +839,7 @@ int InnerProduct_riscv::forward_fp16sa(const Mat& bottom_blob, Mat& top_blob, co
 
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;

src/layer/vulkan/innerproduct_vulkan.cpp

@@ -79,7 +79,7 @@ int InnerProduct_vulkan::create_pipeline(const Option& _opt)
         convert_packing(bias_data, bias_data_packed, out_elempack, opt);
     }
 
-    if (shape.dims == 2 && shape.w == num_input && shape.h > 1)
+    if (shape.dims == 2 && shape.w == num_input)
     {
         // gemm
         int elempack = opt.use_shader_pack8 && shape.h % 8 == 0 ? 8 : shape.h % 4 == 0 ? 4 : 1;
@@ -427,7 +427,7 @@ int InnerProduct_vulkan::forward(const VkMat& bottom_blob, VkMat& top_blob, VkCo
     int in_elempack = opt.use_shader_pack8 && num_input % 8 == 0 ? 8 : num_input % 4 == 0 ? 4 : 1;
     int out_elempack = opt.use_shader_pack8 && num_output % 8 == 0 ? 8 : num_output % 4 == 0 ? 4 : 1;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -587,7 +587,7 @@ int InnerProduct_vulkan::forward(const VkImageMat& bottom_blob, VkImageMat& top_
     int in_elempack = opt.use_shader_pack8 && num_input % 8 == 0 ? 8 : num_input % 4 == 0 ? 4 : 1;
     int out_elempack = opt.use_shader_pack8 && num_output % 8 == 0 ? 8 : num_output % 4 == 0 ? 4 : 1;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;

src/layer/x86/innerproduct_x86.cpp

@@ -118,7 +118,7 @@ int InnerProduct_x86::forward(const Mat& bottom_blob, Mat& top_blob, const Optio
 
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -190,7 +190,7 @@ int InnerProduct_x86::forward_fp16s(const Mat& bottom_blob, Mat& top_blob, const
 {
     const int num_input = weight_data_size / num_output;
 
-    if (bottom_blob.dims == 2 && bottom_blob.w == num_input && bottom_blob.h * bottom_blob.elempack > 1)
+    if (bottom_blob.dims == 2 && bottom_blob.w == num_input)
     {
         // gemm
         int h = bottom_blob.h;
@@ -309,7 +309,7 @@ int InnerProduct_x86::forward_int8_x86(const Mat& bottom_blob, Mat& top_blob, co
         quantize_to_int8(bottom_blob, bottom_blob_int8, bottom_blob_int8_scales, opt_q);
     }
 
-    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input && bottom_blob_int8.h * bottom_blob_int8.elempack > 1)
+    if (bottom_blob_int8.dims == 2 && bottom_blob_int8.w == num_input)
     {
         // gemm
         Mat bottom_blob_int8_unpacked;

tests/test_innerproduct.cpp

@@ -179,6 +179,8 @@ static int test_innerproduct_gemm(const ncnn::Mat& a, int outch, int bias)
 static int test_innerproduct_4()
 {
     return 0
+           || test_innerproduct_gemm(RandomMat(1, 1), 1, 1)
+           || test_innerproduct_gemm(RandomMat(48, 1), 11, 1)
            || test_innerproduct_gemm(RandomMat(1, 5), 1, 1)
            || test_innerproduct_gemm(RandomMat(3, 2), 2, 0)
            || test_innerproduct_gemm(RandomMat(9, 8), 7, 1)

tools/pnnx/tests/ncnn/test_nn_Linear.py

@@ -23,7 +23,7 @@ class Model(nn.Module):
         self.linear_0 = nn.Linear(in_features=64, out_features=16, bias=False)
         self.linear_1 = nn.Linear(in_features=16, out_features=3, bias=True)
 
-    def forward(self, x, y, z):
+    def forward(self, x, y, z, w):
         x = self.linear_0(x)
         x = self.linear_1(x)
 
@@ -33,7 +33,10 @@ class Model(nn.Module):
         z = self.linear_0(z)
         z = self.linear_1(z)
         z = F.relu(z)
-        return x, y, z
+
+        w = self.linear_0(w)
+        w = self.linear_1(w)
+        return x, y, z, w
 
 def test():
     net = Model().half().float()
@@ -43,22 +46,26 @@ def test():
     x = torch.rand(64)
     y = torch.rand(12, 64)
     z = torch.rand(1, 3, 12, 64)
+    w = torch.rand(1, 64)
 
-    a0, a1, a2 = net(x, y, z)
+    a = net(x, y, z, w)
 
     # export torchscript
-    mod = torch.jit.trace(net, (x, y, z))
+    mod = torch.jit.trace(net, (x, y, z, w))
     mod.save("test_nn_Linear.pt")
 
     # torchscript to pnnx
     import os
-    os.system("../../src/pnnx test_nn_Linear.pt inputshape=[64],[12,64],[1,3,12,64]")
+    os.system("../../src/pnnx test_nn_Linear.pt inputshape=[64],[12,64],[1,3,12,64],[1,64]")
 
     # ncnn inference
     import test_nn_Linear_ncnn
-    b0, b1, b2 = test_nn_Linear_ncnn.test_inference()
+    b = test_nn_Linear_ncnn.test_inference()
 
-    return torch.allclose(a0, b0, 1e-4, 1e-4) and torch.allclose(a1, b1, 1e-4, 1e-4) and torch.allclose(a2, b2, 1e-4, 1e-4)
+    for a0, b0 in zip(a, b):
+        if not torch.allclose(a0, b0, 1e-4, 1e-4):
+            return False
+    return True
 
 if __name__ == "__main__":
     if test():