[Divide by 0 Error] add eig check (PaddlePaddle#49971)

* [Divide by 0 Error] add eig check

* [Divide by 0 Error] eig check migrate to c++

* [Divide by 0 Error] Fix class name error

paddle/phi/kernels/cpu/eig_kernel.cc

@@ -31,6 +31,11 @@ void EigKernel(const Context& dev_ctx,
     int batch_count = BatchCount(x);
     int order = x.dims()[x.dims().size() - 1];
 
+    PADDLE_ENFORCE_LT(0,
+                      order,
+                      errors::InvalidArgument(
+                          "The order of Input(X) should be greater than 0."));
+
     DenseTensor real_w;
     DenseTensor real_v;
 

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

@@ -0,0 +1,34 @@
+#  Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import numpy as np
+
+import paddle
+
+
+class TestEigAPIError(unittest.TestCase):
+    def test_errors(self):
+        # The size of input in Eig should not be 0.
+        def test_0_size():
+            array = np.array([], dtype=np.float32)
+            x = paddle.to_tensor(np.reshape(array, [0, 0]), dtype='float32')
+            paddle.linalg.eig(x)
+
+        self.assertRaises(ValueError, test_0_size)
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/tensor/linalg.py

@@ -2323,6 +2323,7 @@ def eig(x, name=None):
             #       [ (16.50471283351188+0j)  , (-5.5034820550763515+0j) ,
             #         (-0.21026087843552282+0j)])
     """
+
     if in_dygraph_mode():
         return _C_ops.eig(x)
     else: