fix(mge/utils): fix module_status error

GitOrigin-RevId: 9e004d98a17e408fd63b162f4f8fe868aaad57bd

imperative/python/megengine/utils/module_stats.py

@@ -443,7 +443,7 @@ def module_stats(
             if isinstance(x, np.ndarray):
                 return Tensor(x)
             elif isinstance(x, collections.abc.Mapping):
-                return {k: load_tensor(x) for k, v in x.items()}
+                return {k: load_tensor(v) for k, v in x.items()}
             elif isinstance(x, tuple) and hasattr(x, "_fields"):  # nametuple
                 return type(x)(*(load_tensor(value) for value in x))
             elif isinstance(x, collections.abc.Sequence):

imperative/python/test/unit/utils/test_module_stats.py

+import collections
 import math
 from copy import deepcopy
 
@@ -27,6 +28,31 @@ def test_module_stats():
     assert (total_stats.flops, total_stats.act_dims) == (gt_flops, gt_acts,)
 
 
+@pytest.mark.skipif(
+    use_symbolic_shape(), reason="This test do not support symbolic shape.",
+)
+def test_other_input_module_state():
+    a = [1, 2]
+    b = {"1": 1, "2": 2}
+    nt = collections.namedtuple("nt", ["n", "t"])
+    _nt = nt(n=1, t=2)
+    net = FakeNet()
+    net(a)
+    net(b)
+    net(_nt)
+
+
+class FakeNet(M.Module):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x):
+        assert isinstance(
+            x,
+            (np.ndarray, collections.abc.Mapping, collections.abc.Sequence, mge.Tensor),
+        ) or (isinstance(x, tuple) and hasattr(x, "_fields"))
+
+
 class BasicBlock(M.Module):
     expansion = 1