refactor(mge/functional): move nvof to vision, compatible with old usage

GitOrigin-RevId: cd9d9b4f5a4c6a55daa6d477bce5ca308805417a

imperative/python/megengine/functional/nn.py

@@ -1409,36 +1409,6 @@ def conv1d(
     return output
 
 
-def nvof(src: Tensor, precision: int = 1) -> Tensor:
-    r"""
-    Implements NVIDIA Optical Flow SDK.
-
-    :src shape: input tensor with shape (n, t, h, w, c4).
-    :src dtype: uint8.
-    :param precision: 0:NV_OF_PERF_LEVEL_SLOW 1:NV_OF_PERF_LEVEL_MEDIUM 2:NV_OF_PERF_LEVEL_FAST.
-    :output shape: (n, t-1, h//4, w//4, c2).
-    :output dtype: int16.
-
-    .. code-block:: python
-
-        import numpy as np
-        from megengine import tensor
-        import megengine.functional as F
-
-        x = np.random.random_integers(0, 255, (1,2,224,244,4)).astype("uint8")
-        src = tensor(x)
-        result = F.nn.nvof(src, precision=1)
-        print(result.numpy())
-
-    """
-    assert src.ndim == 5 and src.shape[4] == 4
-
-    src = src.detach()
-
-    op = builtin.NvOf(precision=precision)
-    return apply(op, src)[0]
-
-
 def hswish(x):
     """
     Element-wise `x * relu6(x + 3) / 6`.
@@ -1492,6 +1462,7 @@ roi_align = deprecated_func("1.3", "megengine.functional.vision", "roi_align", T
 nms = deprecated_func("1.3", "megengine.functional.vision", "nms", True)
 resize = deprecated_func("1.3", "megengine.functional.vision", "resize", True)
 remap = deprecated_func("1.3", "megengine.functional.vision", "remap", True)
+nvof = deprecated_func("1.3", "megengine.functional.vision", "nvof", True)
 warp_affine = deprecated_func("1.3", "megengine.functional.vision", "warp_affine", True)
 warp_perspective = deprecated_func(
     "1.3", "megengine.functional.vision", "warp_perspective", True

imperative/python/megengine/functional/vision.py

@@ -574,3 +574,33 @@ def interpolate(
     if mode == "LINEAR":
         ret = reshape(ret, ret.shape[0:3])
     return ret
+
+
+def nvof(src: Tensor, precision: int = 1) -> Tensor:
+    r"""
+    Implements NVIDIA Optical Flow SDK.
+
+    :src shape: input tensor with shape (n, t, h, w, c4).
+    :src dtype: uint8.
+    :param precision: 0:NV_OF_PERF_LEVEL_SLOW 1:NV_OF_PERF_LEVEL_MEDIUM 2:NV_OF_PERF_LEVEL_FAST.
+    :output shape: (n, t-1, h//4, w//4, c2).
+    :output dtype: int16.
+
+    .. code-block:: python
+
+        import numpy as np
+        from megengine import tensor
+        import megengine.functional as F
+
+        x = np.random.random_integers(0, 255, (1,2,224,244,4)).astype("uint8")
+        src = tensor(x)
+        result = F.nn.nvof(src, precision=1)
+        print(result.numpy())
+
+    """
+    assert src.ndim == 5 and src.shape[4] == 4
+
+    src = src.detach()
+
+    op = builtin.NvOf(precision=precision)
+    return apply(op, src)[0]