diff --git a/imperative/python/megengine/jit/tracing.py b/imperative/python/megengine/jit/tracing.py
index f24bfd74..c1662fbf 100644
--- a/imperative/python/megengine/jit/tracing.py
+++ b/imperative/python/megengine/jit/tracing.py
@@ -725,6 +725,12 @@ class trace:
             raise RuntimeError("trace is not set with profiling=True")
         return json.loads(self._profiler.get())
 
+    def trace(self, *args, **kwargs):
+        raise NotImplementedError(
+            "trace is deemed unbeneficial with the new "
+            "tracing mechanism. You should alwasy use __call__."
+        )
+
 
 class CompiledTensorProxy(RawTensor):
     """
diff --git a/imperative/python/megengine/module/module.py b/imperative/python/megengine/module/module.py
index 9b1dbc28..bf87be9d 100644
--- a/imperative/python/megengine/module/module.py
+++ b/imperative/python/megengine/module/module.py
@@ -174,7 +174,11 @@ class Module(metaclass=ABCMeta):
 
         if "requires_grad" in kwargs:
             del kwargs["requires_grad"]
-            warnings.warn("passing requires_grad has no effect currently")
+            warnings.warn(
+                "Tensor currently has no requires_grad attribute "
+                "so requires_grad argument is ignored here",
+                DeprecationWarning,
+            )
 
         def predicate(obj) -> bool:
             return _is_parameter(obj)
@@ -197,7 +201,11 @@ class Module(metaclass=ABCMeta):
 
         if "requires_grad" in kwargs:
             del kwargs["requires_grad"]
-            warnings.warn("passing requires_grad has no effect currently")
+            warnings.warn(
+                "Tensor currently has no requires_grad attribute "
+                "so requires_grad argument is ignored here",
+                DeprecationWarning,
+            )
 
         def predicate(obj) -> bool:
             return _is_parameter(obj)
@@ -339,6 +347,7 @@ class Module(metaclass=ABCMeta):
 
         self.apply(fn)
 
+    @deprecated(version="1.0")
     def replace_param(
         self, params: dict, start_pos: int, seen: Optional[Set[int]] = None
     ):
diff --git a/imperative/python/megengine/optimizer/optimizer.py b/imperative/python/megengine/optimizer/optimizer.py
index 90a51eeb..cf869cdf 100644
--- a/imperative/python/megengine/optimizer/optimizer.py
+++ b/imperative/python/megengine/optimizer/optimizer.py
@@ -16,6 +16,7 @@ from typing import Union
 import numpy as np
 
 from ..tensor import Parameter, Tensor
+from ..utils.deprecation import deprecated
 
 
 class _RequiredParameter:
@@ -149,8 +150,15 @@ class Optimizer(metaclass=ABCMeta):
             self._updates(group)
         return self
 
+    @deprecated(version="1.0", reason="use clear_grad instead")
+    def zero_grad(self):
+        for param_group in self.param_groups:
+            for param in param_group["params"]:
+                if param.grad is not None:
+                    param.grad.reset_zero()
+
     def clear_grad(self):
-        r"""Clear the grad buffer.
+        r"""Set the grad attribute to None for all parameters.
 
         """
         for param_group in self.param_groups:
@@ -224,3 +232,9 @@ class Optimizer(metaclass=ABCMeta):
                 "loaded state dict contains a state that doesn't match "
                 "the size of optimizer's state"
             )
+
+    def backward(self, loss):
+        raise NotImplementedError("use autodiff.GradManager instead")
+
+    def bcast_param(self):
+        raise NotImplementedError("use distributed.bcast_list_ instead")
diff --git a/imperative/python/megengine/tensor.py b/imperative/python/megengine/tensor.py
index 726236e3..a8eae821 100644
--- a/imperative/python/megengine/tensor.py
+++ b/imperative/python/megengine/tensor.py
@@ -13,6 +13,7 @@ import collections
 from .core import Tensor as _Tensor
 from .core.ops.builtin import Copy
 from .core.tensor.core import apply
+from .core.tensor.raw_tensor import as_device
 from .device import get_default_device
 from .utils.deprecation import deprecated
 
@@ -35,7 +36,8 @@ class Tensor(_Tensor):
     def reset_zero(self):
         self *= 0
 
-    def to(self, cn):
+    def to(self, device):
+        cn = as_device(device).to_c()
         return apply(Copy(comp_node=cn), self)[0]
 
     @property