Fix safety-bug of functional.linear (#34696)

* Fix safety-bug of functional.linear

* Fix safety-bug of functional.linear

* Fix safety-bug of functional.linear

* Fix safety-bug of functional.linear

paddle/fluid/operators/math/blas_impl.h

@@ -1041,6 +1041,12 @@ void Blas<platform::CPUDeviceContext>::BatchedGEMM(
     CBLAS_TRANSPOSE transA, CBLAS_TRANSPOSE transB, int M, int N, int K,
     T alpha, const T *A, const T *B, T beta, T *C, int batchCount,
     int64_t strideA, int64_t strideB) const {
+  PADDLE_ENFORCE_NOT_NULL(
+      A, platform::errors::InvalidArgument("Pointer A should not be null."));
+  PADDLE_ENFORCE_NOT_NULL(
+      B, platform::errors::InvalidArgument("Pointer B should not be null."));
+  PADDLE_ENFORCE_NOT_NULL(
+      C, platform::errors::InvalidArgument("Pointer C should not be null."));
 #ifdef PADDLE_WITH_MKLML
   int lda = (transA == CblasNoTrans) ? K : M;
   int ldb = (transB == CblasNoTrans) ? N : K;

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

@@ -73,6 +73,15 @@ 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(ValueError):
+            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()