Workaround for mulithread test

tools/pnnx/tests/numpy/test_convnext_tiny.py

@@ -18,7 +18,7 @@ def test():
     x = torch.rand(1, 3, 224, 224)
 
     np = x.numpy()
-    npy.save("input1.npy", np)
+    npy.save("test_convnext_tiny_input1.npy", np)
 
     a = net(x)
 
@@ -28,7 +28,7 @@ def test():
 
     # torchscript to pnnx
     import os
-    os.system("../../src/pnnx test_convnext_tiny.pt input=input1.npy")
+    os.system("../../src/pnnx test_convnext_tiny.pt input=test_convnext_tiny_input1.npy")
 
     # pnnx inference
     import test_convnext_tiny_pnnx

tools/pnnx/tests/numpy/test_convnext_tiny_endian.py

@@ -19,17 +19,17 @@ def test():
 
     np = x.numpy()
     r_np = np.astype('>f4')
-    npy.save("input1.npy", r_np)
+    npy.save("test_convnext_tiny_endian_input1.npy", r_np)
 
     a = net(x)
 
     # export torchscript
     mod = torch.jit.trace(net, x)
-    mod.save("test_convnext_tiny.pt")
+    mod.save("test_convnext_tiny_endian.pt")
 
     # torchscript to pnnx
     import os
-    os.system("../../src/pnnx test_convnext_tiny.pt input=input1.npy")
+    os.system("../../src/pnnx test_convnext_tiny_endian.pt input=test_convnext_tiny_endian_input1.npy")
 
     # pnnx inference
     import test_convnext_tiny_pnnx

tools/pnnx/tests/numpy/test_convnext_tiny_fortran_array.py

@@ -19,17 +19,17 @@ def test():
 
     np = x.numpy()
     f_np = npy.asfortranarray(np);
-    npy.save("input1.npy", f_np)
+    npy.save("test_convnext_tiny_fortran_array_input1.npy", f_np)
 
     a = net(x)
 
     # export torchscript
     mod = torch.jit.trace(net, x)
-    mod.save("test_convnext_tiny.pt")
+    mod.save("test_convnext_tiny_fortran_array.pt")
 
     # torchscript to pnnx
     import os
-    os.system("../../src/pnnx test_convnext_tiny.pt input=input1.npy")
+    os.system("../../src/pnnx test_convnext_tiny_fortran_array.pt input=test_convnext_tiny_fortran_array_input1.npy")
 
     # pnnx inference
     import test_convnext_tiny_pnnx

tools/pnnx/tests/numpy/test_nn_Conv3d.py

@@ -47,7 +47,7 @@ def test():
     torch.manual_seed(0)
     x = torch.rand(1, 12, 48, 48, 64)
     np = x.numpy()
-    npy.save("input1.npy", np)
+    npy.save("test_nn_Conv3d_input1.npy", np)
 
     a = net(x)
 
@@ -57,7 +57,7 @@ def test():
 
     # torchscript to pnnx
     import os
-    os.system("../../src/pnnx test_nn_Conv3d.pt input=input1.npy")
+    os.system("../../src/pnnx test_nn_Conv3d.pt input=test_nn_Conv3d_input1.npy")
 
     # pnnx inference
     import test_nn_Conv3d_pnnx

tools/pnnx/tests/numpy/test_pnnx_fuse_multiheadattention.py

@@ -483,9 +483,9 @@ def test():
     ny = y.numpy()
     nz = z.numpy()
 
-    npy.save("x.npy", nx)
-    npy.save("y.npy", ny)
-    npy.save("z.npy", nz)
+    npy.save("test_pnnx_fuse_multiheadattention_x.npy", nx)
+    npy.save("test_pnnx_fuse_multiheadattention_y.npy", ny)
+    npy.save("test_pnnx_fuse_multiheadattention_z.npy", nz)
 
     a = net(x, y, z)
 
@@ -495,7 +495,7 @@ def test():
 
     # torchscript to pnnx
     import os
-    os.system("../../src/pnnx test_pnnx_fuse_multiheadattention.pt input=x.npy,y.npy,z.npy")
+    os.system("../../src/pnnx test_pnnx_fuse_multiheadattention.pt input=test_pnnx_fuse_multiheadattention_x.npy,test_pnnx_fuse_multiheadattention_y.npy,test_pnnx_fuse_multiheadattention_z.npy")
 
     # pnnx inference
     import test_pnnx_fuse_multiheadattention_pnnx