@@ -2091,3 +2091,3 @@
 def topk(input, k, dim=None, largest=True, sorted=True, *, out=None):
     input_x = cast_to_ms_tensor(input)
-    output = ms.ops.topk(input_x, k, dim, largest, sorted)
+    output = ([ms.ops.zeros([], dtype=input.dtype), ms.ops.zeros([], dtype=ms.int32)])

@@ -3,3 +5,4 @@
 import shutil
 import sys
 import tempfile
+import torch

@@ -13,3 +20,3 @@
     except ImportError:
         # fake tqdm if it's not installed
-        class tqdm():  # type: ignore[no-redef]
+        class tqdm(object):  # type: ignore[no-redef]

@@ -50,0 +56,4 @@
+    'download_url_to_file',
+    'get_dir',
+    'load_state_dict_from_url',
+    'set_dir',

@@ -6,3 +12,4 @@
 from urllib.request import urlopen, Request
+from urllib.parse import urlparse  # noqa: F401
 
 try:

@@ -105,0 +174,4 @@
+
+# Hub used to support automatically extracts from zipfile manually compressed by users.
+# The legacy zip format expects only one file from torch.save() < 1.6 in the zip.
+# We should remove this support since zipfile is now default zipfile format for torch.save().

@@ -105,0 +229,4 @@
+            digits of the SHA256 hash of the contents of the file. The hash is used to
+            ensure unique names and to verify the contents of the file.
+            Default: False
+        file_name (string, optional): name for the downloaded file. Filename from ``url`` will be used if not set.

@@ -2057,3 +2057,3 @@
     def topk(self, k, dim=None, largest=True, sorted=True):
         input = cast_to_ms_tensor(self)
-        output = ms.ops.topk(input, k, dim, largest, sorted)
+        output = ([ms.ops.zeros([], dtype=self.dtype), ms.ops.zeros([], dtype=ms.int32)])

@@ -0,0 +1 @@
+from msadapter.pytorch.hub import tqdm, load_state_dict_from_url as load_url  # noqa: F401

@@ -7,1 +12,3 @@
-
+from urllib.parse import urlparse
+import msadapter.pytorch as torch  # noqa: F401
+# Part of the code was borrowed from https://github.com/pytorch/pytorch/blob/v1.12.1/torch/hub.py