diff --git a/mindspore/python/mindspore/common/tensor.py b/mindspore/python/mindspore/common/tensor.py
index 425fd377b80..24720ee8a6f 100644
--- a/mindspore/python/mindspore/common/tensor.py
+++ b/mindspore/python/mindspore/common/tensor.py
@@ -185,10 +185,10 @@ class Tensor(Tensor_):
     def _set_default_dtype(input_data, dtype):
         """Set tensor default dtype"""
         if isinstance(input_data, (float, list, tuple)):
-            if np.array(input_data).dtype == np.float64 or np.array(input_data).dtype == np.float32:
+            if np.array(input_data).dtype == np.float64:
                 return mstype.float32
-        elif isinstance(input_data, (int, list, tuple)):
-            if np.array(input_data).dtype == np.int64 or np.array(input_data).dtype == np.int32:
+        if isinstance(input_data, (int, list, tuple)):
+            if np.array(input_data).dtype == np.int32 or np.array(input_data).dtype == np.int64:
                 return mstype.int64
         return dtype
 
diff --git a/tests/st/ops/cpu/test_sparse_segment_mean_op.py b/tests/st/ops/cpu/test_sparse_segment_mean_op.py
index b10435d7589..18c83f64eca 100644
--- a/tests/st/ops/cpu/test_sparse_segment_mean_op.py
+++ b/tests/st/ops/cpu/test_sparse_segment_mean_op.py
@@ -58,7 +58,7 @@ def test_net(data_type, index_type, error):
     dim0 = x.shape[0]
     indices = np.random.randint(0, dim0, size=index_shape).astype(index_type)
     segment_ids = np.random.randint(0, 2 * dim0, size=index_shape).astype(index_type)
-    segment_ids = sorted(segment_ids)
+    segment_ids = np.array(sorted(segment_ids)).astype(index_type)
     np_out = sparse_segment_mean_numpy(x, indices, segment_ids)
 
     context.set_context(mode=context.PYNATIVE_MODE, device_target="CPU")
diff --git a/tests/st/ops/gpu/test_sparse_segment_mean_op.py b/tests/st/ops/gpu/test_sparse_segment_mean_op.py
index d5e13438d20..915bd681a5e 100644
--- a/tests/st/ops/gpu/test_sparse_segment_mean_op.py
+++ b/tests/st/ops/gpu/test_sparse_segment_mean_op.py
@@ -58,7 +58,7 @@ def test_net(data_type, index_type, error):
     dim0 = x.shape[0]
     indices = np.random.randint(0, dim0, size=index_shape).astype(index_type)
     segment_ids = np.random.randint(0, 2 * dim0, size=index_shape).astype(index_type)
-    segment_ids = sorted(segment_ids)
+    segment_ids = np.array(sorted(segment_ids)).astype(index_type)
     np_out = sparse_segment_mean_numpy(x, indices, segment_ids)
 
     context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")