[Zero-Dim] support input 0D Tensor for unique

paddle/phi/infermeta/unary.cc

@@ -4596,17 +4596,26 @@ void UniqueRawInferMeta(const MetaTensor& x,
                         MetaTensor* index,
                         MetaTensor* counts) {
   if (!is_sorted) {
-    PADDLE_ENFORCE_EQ(
-        x.dims().size(),
-        1,
-        phi::errors::InvalidArgument("The Input(X) should be 1-D Tensor, "
-                                     "But now the dims of Input(X) is %d.",
-                                     x.dims().size()));
+    PADDLE_ENFORCE_EQ(x.dims().size() == 1 || x.dims().size() == 0,
+                      true,
+                      phi::errors::InvalidArgument(
+                          "The Input(X) should be 0-D or 1-D Tensor, "
+                          "But now the dims of Input(X) is %d.",
+                          x.dims().size()));
     out->set_dims(phi::make_ddim({-1}));
     index->set_dims(x.dims());
     return;
   }
 
+  if (x.dims().size() == 0) {
+    PADDLE_ENFORCE_EQ(axis.empty(),
+                      true,
+                      phi::errors::InvalidArgument(
+                          "The Input(X) with 0-D Tensor, axis must be None"
+                          "But now the axis is %d.",
+                          axis[0]));
+  }
+
   if (axis.empty()) {
     out->set_dims(phi::make_ddim({-1}));
     if (return_inverse) {

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

@@ -2430,6 +2430,29 @@ def test_one_hot_label(self):
         self.assertEqual(one_hot_label.shape, [4])
         self.assertEqual(one_hot_label.numpy()[2], 1)
 
+    def test_unique(self):
+        places = ['cpu']
+        if paddle.is_compiled_with_cuda():
+            places.append('gpu')
+        for place in places:
+            paddle.set_device(place)
+            x = paddle.rand([])
+            y, index, inverse, counts = paddle.unique(
+                x,
+                return_index=True,
+                return_inverse=True,
+                return_counts=True,
+            )
+
+            self.assertEqual(y, x)
+            self.assertEqual(index, 0)
+            self.assertEqual(inverse, 0)
+            self.assertEqual(counts, 1)
+            self.assertEqual(y.shape, [1])
+            self.assertEqual(index.shape, [1])
+            self.assertEqual(inverse.shape, [1])
+            self.assertEqual(counts.shape, [1])
+
 
 class TestNoBackwardAPIStatic(unittest.TestCase):
     def setUp(self):
@@ -2632,6 +2655,23 @@ def test_one_hot_label(self):
         self.assertEqual(res[0].shape, (4,))
         self.assertEqual(res[0][2], 1)
 
+    def test_unique(self):
+        x = paddle.rand([])
+        y, index, inverse, counts = paddle.unique(
+            x, return_index=True, return_inverse=True, return_counts=True
+        )
+
+        prog = paddle.static.default_main_program()
+        res = self.exe.run(prog, fetch_list=[y, index, inverse, counts])
+        self.assertEqual(y, x)
+        self.assertEqual(index, 0)
+        self.assertEqual(inverse, 0)
+        self.assertEqual(counts, 1)
+        self.assertEqual(res[0].shape, (1,))
+        self.assertEqual(res[1].shape, (1,))
+        self.assertEqual(res[2].shape, (1,))
+        self.assertEqual(res[3].shape, (1,))
+
 
 if __name__ == "__main__":
     unittest.main()