@@ -0,0 +66,4 @@
+
+        self.exp_avg = cast_to_float32(self.exp_avg)
+        self.exp_avg_sq = cast_to_float32(self.exp_avg_sq)
+        self.max_exp_avg_sq = cast_to_float32(self.max_exp_avg_sq)

@@ -0,0 +107,4 @@
+        if grads is None:
+            grads = []
+            for param_group in self.param_groups:
+                for param in param_group['params']:

@@ -453,2 +456,3 @@
 
-    output = ms.ops.linspace(start, end, steps)
+    # TODO: ms.ops.linspace has some bug now.
+    # output = ms.ops.linspace(start, end, steps)

@@ -0,0 +8,4 @@
+
+op_mul = P.Mul()
+op_pow = P.Pow()
+op_sqrt = P.Sqrt()

@@ -458,1 +461,3 @@
-    output = ms.ops.linspace(start, end, steps)
+    # TODO: ms.ops.linspace has some bug on Ascend now.
+    if is_under_ascend_context():
+        num = int(steps)

@@ -1250,6 +1250,9 @@ class Tensor(StubTensor, metaclass=_TensorMeta):
             if dtype == mindtorch_dtype.bfloat16:
                 return tensor(out.astype(np.float32), dtype=dtype).reshape(target_shape)
             return tensor(out).reshape(target_shape)
+        if isinstance(shape[0], (tuple, list)):

@@ -45,2 +46,4 @@
         )
     return run_function(end + 1, len(functions) - 1, functions)(input)
+
+def detach_variable(inputs):

@@ -45,2 +46,4 @@
         )
     return run_function(end + 1, len(functions) - 1, functions)(input)
+
+def detach_variable(inputs):

@@ -45,2 +46,4 @@
         )
     return run_function(end + 1, len(functions) - 1, functions)(input)
+
+def detach_variable(inputs):