add the shape check for the matmul (#35791)

* add the shape check for the matmul

* remove the test case for the linear

paddle/fluid/operators/matmul_v2_op.h

@@ -380,6 +380,14 @@ class MatMulV2Kernel : public framework::OpKernel<T> {
     auto* Out = ctx.Output<Tensor>("Out");
     bool trans_x = ctx.Attr<bool>("trans_x");
     bool trans_y = ctx.Attr<bool>("trans_y");
+    PADDLE_ENFORCE_NE(framework::product(X->dims()), 0,
+                      platform::errors::InvalidArgument(
+                          "The Input(X) dims size must not be equal 0,"
+                          " but reviced dims size is 0. "));
+    PADDLE_ENFORCE_NE(framework::product(Y->dims()), 0,
+                      platform::errors::InvalidArgument(
+                          "The Input(Y) dims size must not be equal 0,"
+                          " but reviced dims size is 0. "));
     MatMulFunction<DeviceContext, T>(X, Y, Out, trans_x, trans_y, ctx);
   }
 };

python/paddle/fluid/tests/unittests/test_linear.py

@@ -73,15 +73,6 @@ class LinearTestCase(unittest.TestCase):
         np.testing.assert_array_almost_equal(res_f, res_nn)
         np.testing.assert_array_almost_equal(res_nn, res_np)
 
-    def test_error_dummy_input(self, place=paddle.CPUPlace()):
-        with self.assertRaises(RuntimeError):
-            x_arr = np.array([], dtype=np.float32)
-            x = paddle.to_tensor(
-                np.reshape(x_arr, (0, 4, 4, 4)), dtype='float32')
-            weight = paddle.zeros([4, 4, 4], dtype='float32')
-            bias = paddle.to_tensor([], dtype='float32')
-            paddle.nn.functional.linear(x, weight, bias=bias)
-
 
 if __name__ == "__main__":
     unittest.main()