diff --git a/paddle/phi/kernels/cpu/stack_kernel.cc b/paddle/phi/kernels/cpu/stack_kernel.cc
index a9c428c68047d..cd43c32dfecc8 100644
--- a/paddle/phi/kernels/cpu/stack_kernel.cc
+++ b/paddle/phi/kernels/cpu/stack_kernel.cc
@@ -25,6 +25,15 @@ void StackKernel(const Context& dev_ctx,
                  int axis,
                  DenseTensor* out) {
   if (axis < 0) axis += (x[0]->dims().size() + 1);
+
+  auto x_dims = x[0]->dims();
+  for (int i = 0; i < x_dims.size(); i++) {
+    PADDLE_ENFORCE_GT(x_dims[i],
+                      0,
+                      phi::errors::InvalidArgument(
+                          "The dims of Input(X) should be greater than 0"));
+  }
+
   int n = static_cast<int>(x.size());
   T* y_data = dev_ctx.template Alloc<T>(out);
   std::vector<const T*> x_datas(n);
diff --git a/paddle/phi/kernels/funcs/stack_and_unstack.h b/paddle/phi/kernels/funcs/stack_and_unstack.h
index 0b2b5443383a9..d82cbd523f8fb 100644
--- a/paddle/phi/kernels/funcs/stack_and_unstack.h
+++ b/paddle/phi/kernels/funcs/stack_and_unstack.h
@@ -77,11 +77,12 @@ void StackRawKernel(const Context& ctx,
 
   // Split x dim from axis to matrix of shape [x_row, x_col], and the output
   // tensor's shape is [x_row, out_col].
-  int64_t x_row = 1;
+  int64_t x_row = 1, x_row_bak = 1;
   for (int i = 0; i < axis; ++i) {
     x_row *= x[0]->dims()[i];
   }
-  int64_t x_col = x[0]->numel() / x_row;
+  x_row_bak = x_row == 0 ? 1 : x_row;
+  int64_t x_col = x[0]->numel() / x_row_bak;
   int64_t out_col = x_col * num;
 
   if (out->numel() < std::numeric_limits<int32_t>::max()) {
diff --git a/python/paddle/fluid/tests/unittests/distribution/test_distribution_beta.py b/python/paddle/fluid/tests/unittests/distribution/test_distribution_beta.py
index cdff723a11b9d..a130d76e1e0d7 100644
--- a/python/paddle/fluid/tests/unittests/distribution/test_distribution_beta.py
+++ b/python/paddle/fluid/tests/unittests/distribution/test_distribution_beta.py
@@ -113,6 +113,12 @@ def test_sample_shape(self):
                 == case.get('expect')
             )
 
+    def test_errors(self):
+        with self.assertRaises(ValueError):
+            array = np.array([], dtype=np.float32)
+            x = paddle.to_tensor(np.reshape(array, [0]), dtype='int32')
+            paddle.distribution.Beta(alpha=x, beta=x)
+
 
 if __name__ == '__main__':
     unittest.main()