diff --git a/python/oneflow/utils/data/sampler.py b/python/oneflow/utils/data/sampler.py
index 7ff1915f00d..7a53b813d4d 100644
--- a/python/oneflow/utils/data/sampler.py
+++ b/python/oneflow/utils/data/sampler.py
@@ -141,34 +141,24 @@ def __iter__(self):
         n = len(self.data_source)
         if self.generator is None:
             generator = flow.Generator()
-            generator.manual_seed(
-                # TODO: replace with flow.randint
-                flow.Tensor(1, dtype=flow.int64)
-                .uniform_(0, 999)
-                .numpy()
-                .item()
-            )
+            generator.manual_seed(np.random.randint(0, np.iinfo(np.int64).max))
+            # TODO: use Tensor.random_
+            # generator.manual_seed(
+            #     int(flow.empty((), dtype=flow.int64).random_().item())
+            # )
         else:
             generator = self.generator
         if self.replacement:
-            np.random.randint()
             for _ in range(self.num_samples // 32):
-                yield from np.random.randint(
-                    high=n, size=(32,), dtype=np.int64
+                yield from flow.randint(
+                    high=n, size=(32,), dtype=flow.int64, generator=generator
                 ).tolist()
-                # TODO: use flow.randint replace np.randint
-                # yield from flow.randint(
-                #     high=n, size=(32,), dtype=flow.int64, generator=generator
-                # ).tolist()
-            yield from np.random.randint(
-                high=n, size=(self.num_samples % 32,), dtype=np.int64
+            yield from flow.randint(
+                high=n,
+                size=(self.num_samples % 32,),
+                dtype=flow.int64,
+                generator=generator,
             ).tolist()
-            # yield from flow.randint(
-            #     high=n,
-            #     size=(self.num_samples % 32,),
-            #     dtype=flow.int64,
-            #     generator=generator,
-            # ).tolist()
         else:
             yield from flow.randperm(n, generator=generator).tolist()
 
diff --git a/python/oneflow/utils/vision/transforms/transforms.py b/python/oneflow/utils/vision/transforms/transforms.py
index b2def901ab7..f5320272dc3 100644
--- a/python/oneflow/utils/vision/transforms/transforms.py
+++ b/python/oneflow/utils/vision/transforms/transforms.py
@@ -586,11 +586,8 @@ def get_params(
         if w == tw and h == th:
             return 0, 0, h, w
 
-        # TODO:replace with flow.randint
-        # i = flow.randint(0, h - th + 1, size=(1, )).item()
-        # j = flow.randint(0, w - tw + 1, size=(1, )).item()
-        i = np.random.randint(low=0, high=h - th + 1, size=(1,), dtype=np.int32)
-        j = np.random.randint(low=0, high=w - tw + 1, size=(1,), dtype=np.int32)
+        i = flow.randint(0, h - th + 1, size=(1,)).item()
+        j = flow.randint(0, w - tw + 1, size=(1,)).item()
         return i, j, th, tw
 
     def __init__(
@@ -788,15 +785,8 @@ def get_params(
             h = int(round(math.sqrt(target_area / aspect_ratio)))
 
             if 0 < w <= width and 0 < h <= height:
-                # TODO:replace with flow.randint
-                # i = flow.randint(0, height - h + 1, size=(1,)).item()
-                # j = flow.randint(0, width - w + 1, size=(1,)).item()
-                i = np.random.randint(
-                    low=0, high=height - h + 1, size=(1,), dtype=np.int32
-                )
-                j = np.random.randint(
-                    low=0, high=width - w + 1, size=(1,), dtype=np.int32
-                )
+                i = flow.randint(0, height - h + 1, size=(1,)).item()
+                j = flow.randint(0, width - w + 1, size=(1,)).item()
                 return i, j, h, w
 
         # Fallback to central crop