diff --git a/paddle/fluid/pybind/eager_properties.cc b/paddle/fluid/pybind/eager_properties.cc
index fa926618bdf8db..ba857e9cdbfbdb 100644
--- a/paddle/fluid/pybind/eager_properties.cc
+++ b/paddle/fluid/pybind/eager_properties.cc
@@ -35,6 +35,8 @@ limitations under the License. */
 
 #pragma GCC diagnostic ignored "-Wwrite-strings"
 
+COMMON_DECLARE_bool(enable_pir_api);
+
 namespace paddle {
 namespace pybind {
 
@@ -847,25 +849,47 @@ Tensor's data type.
 )DOC");
 PyObject* tensor_properties_get_dtype(TensorObject* self, void* closure) {
   EAGER_TRY
-  if (!self->tensor.defined()) {
-    // be same to old dygraph
-    return ToPyObject(framework::proto::VarType::FP32);
-  }
-  if (egr::IsVariableCompatTensor(self->tensor)) {
-    auto* var_tensor = static_cast<const egr::VariableCompatTensor*>(
-        self->tensor.impl().get());
-    if (var_tensor->IsType<paddle::framework::Vocab>()) {
-      return ToPyObject(framework::proto::VarType::RAW);
-    } else if (var_tensor->IsType<paddle::framework::Strings>()) {
-      return ToPyObject(framework::proto::VarType::STRING);
+  if (FLAGS_enable_pir_api) {
+    if (!self->tensor.defined()) {
+      // be same to old dygraph
+      return ToPyObject(phi::DataType::FLOAT32);
+    }
+    if (egr::IsVariableCompatTensor(self->tensor)) {
+      auto* var_tensor = static_cast<const egr::VariableCompatTensor*>(
+          self->tensor.impl().get());
+      if (var_tensor->IsType<paddle::framework::Vocab>()) {
+        return ToPyObject(phi::DataType::UNDEFINED);
+      } else if (var_tensor->IsType<paddle::framework::Strings>()) {
+        return ToPyObject(phi::DataType::PSTRING);
+      } else {
+        PADDLE_THROW(paddle::platform::errors::Unavailable(
+            "VariableCompatTensor only support get shape from Vocab or "
+            "Strings."));
+      }
     } else {
-      PADDLE_THROW(paddle::platform::errors::Unavailable(
-          "VariableCompatTensor only support get shape from Vocab or "
-          "Strings."));
+      return ToPyObject(self->tensor.type());
     }
   } else {
-    return ToPyObject(
-        paddle::framework::TransToProtoVarType(self->tensor.type()));
+    if (!self->tensor.defined()) {
+      // be same to old dygraph
+      return ToPyObject(framework::proto::VarType::FP32);
+    }
+    if (egr::IsVariableCompatTensor(self->tensor)) {
+      auto* var_tensor = static_cast<const egr::VariableCompatTensor*>(
+          self->tensor.impl().get());
+      if (var_tensor->IsType<paddle::framework::Vocab>()) {
+        return ToPyObject(framework::proto::VarType::RAW);
+      } else if (var_tensor->IsType<paddle::framework::Strings>()) {
+        return ToPyObject(framework::proto::VarType::STRING);
+      } else {
+        PADDLE_THROW(paddle::platform::errors::Unavailable(
+            "VariableCompatTensor only support get shape from Vocab or "
+            "Strings."));
+      }
+    } else {
+      return ToPyObject(
+          paddle::framework::TransToProtoVarType(self->tensor.type()));
+    }
   }
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
diff --git a/paddle/fluid/pybind/eager_utils.cc b/paddle/fluid/pybind/eager_utils.cc
index 851e498bac8b3a..aba7c99662bbee 100644
--- a/paddle/fluid/pybind/eager_utils.cc
+++ b/paddle/fluid/pybind/eager_utils.cc
@@ -1077,6 +1077,12 @@ PyObject* ToPyObject(const phi::DenseTensor* value) {
   return obj.ptr();
 }
 
+PyObject* ToPyObject(const phi::DataType& dtype) {
+  auto obj = ::pybind11::cast(dtype);
+  obj.inc_ref();
+  return obj.ptr();
+}
+
 PyObject* ToPyObject(const pir::Value& value) {
   auto obj = ::pybind11::cast(value);
   obj.inc_ref();
@@ -2410,9 +2416,11 @@ paddle::DataType CastPyArg2DataType(PyObject* obj,
   if (obj == Py_None) {
     return phi::DataType::UNDEFINED;
   }
-
-  framework::proto::VarType::Type type = CastPyArg2ProtoType(obj, arg_pos);
-  return framework::TransToPhiDataType(type);
+  if (PyObject_TypeCheck(obj, g_vartype_pytype)) {
+    framework::proto::VarType::Type type = CastPyArg2ProtoType(obj, arg_pos);
+    return framework::TransToPhiDataType(type);
+  }
+  return CastPyArg2DataTypeDirectly(obj, op_type, arg_pos);
 }
 
 paddle::Tensor PyTensorHook::operator()(const paddle::Tensor& var) {
diff --git a/paddle/fluid/pybind/eager_utils.h b/paddle/fluid/pybind/eager_utils.h
index 2511ddb57dbb5b..e56741aa90776a 100644
--- a/paddle/fluid/pybind/eager_utils.h
+++ b/paddle/fluid/pybind/eager_utils.h
@@ -148,6 +148,7 @@ PyObject* ToPyObject(const phi::distributed::Placements& value);
 PyObject* ToPyObject(const phi::SelectedRows* value);
 PyObject* ToPyObject(const paddle::framework::proto::VarType::Type& dtype);
 PyObject* ToPyObject(const paddle::framework::proto::VarType& type);
+PyObject* ToPyObject(const phi::DataType& type);
 PyObject* ToPyObject(const void* value);
 PyObject* ToPyObject(const std::unordered_map<int, int>& value);
 PyObject* ToPyObject(
diff --git a/paddle/fluid/pybind/op_function_common.cc b/paddle/fluid/pybind/op_function_common.cc
index 5d7977ce5c4422..f8f1424ded2432 100644
--- a/paddle/fluid/pybind/op_function_common.cc
+++ b/paddle/fluid/pybind/op_function_common.cc
@@ -64,6 +64,7 @@ class OpAttrTypeMap {
 };
 
 extern PyTypeObject* g_vartype_pytype;
+extern PyTypeObject* g_data_type_pytype;
 extern PyTypeObject* g_blockdesc_pytype;
 extern PyTypeObject* p_tensor_type;
 
@@ -72,6 +73,7 @@ bool PyObject_CheckBool(PyObject** obj) { return PyBool_Check(*obj); }
 bool PyObject_CheckLongOrToLong(PyObject** obj) {
   if ((PyLong_Check(*obj) && !PyBool_Check(*obj)) ||
       PyObject_TypeCheck(*obj, g_vartype_pytype) ||        // NOLINT
+      PyObject_TypeCheck(*obj, g_data_type_pytype) ||      // NOLINT
       (PyObject_TypeCheck(*obj, p_tensor_type) &&          // NOLINT
        (((TensorObject*)(*obj))->tensor.numel() == 1))) {  // NOLINT
     return true;
diff --git a/python/paddle/base/dygraph/math_op_patch.py b/python/paddle/base/dygraph/math_op_patch.py
index 3f7b7a40ffa461..916dedea28418e 100644
--- a/python/paddle/base/dygraph/math_op_patch.py
+++ b/python/paddle/base/dygraph/math_op_patch.py
@@ -87,7 +87,7 @@ def astype(self, dtype):
                 >>> print("new tensor's dtype is: {}".format(new_tensor.dtype))
                 new tensor's dtype is: paddle.float32
         """
-        if not isinstance(dtype, core.VarDesc.VarType):
+        if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
             dtype = convert_np_dtype_to_dtype_(dtype)
         return _C_ops.cast(self, dtype)
 
diff --git a/python/paddle/base/dygraph/tensor_patch_methods.py b/python/paddle/base/dygraph/tensor_patch_methods.py
index 275ab3a232d96c..e5e6fda5bc5969 100644
--- a/python/paddle/base/dygraph/tensor_patch_methods.py
+++ b/python/paddle/base/dygraph/tensor_patch_methods.py
@@ -188,13 +188,12 @@ def set_value(self, value):
                 ...     linear.weight.set_value(custom_weight)  # change existing weight
                 ...     out = linear(t)  # call with different weight
         """
-        base_tensor = core.eager.Tensor
         assert isinstance(
-            value, (np.ndarray, base_tensor, dict, str)
+            value, (np.ndarray, paddle.Tensor, dict, str)
         ), "Variable set_value function, arguments type only support Variable, numpy, Tensor, dict, string."
         if self.is_dist():
             assert isinstance(
-                value, (np.ndarray, base_tensor)
+                value, (np.ndarray, paddle.Tensor)
             ), "For set_value function of dist tensor, arguments type only support numpy or Tensor."
 
         if isinstance(value, (dict, str)):
@@ -214,8 +213,10 @@ def set_value(self, value):
                 self.name, self.shape, value.shape
             )
 
-            if isinstance(value, base_tensor):
+            if isinstance(value, paddle.Tensor):
                 dtype = value.dtype
+            elif paddle.framework.use_pir_api():
+                dtype = paddle.pir.core.convert_np_dtype_to_dtype_(value.dtype)
             else:
                 dtype = convert_np_dtype_to_dtype_(value.dtype)
 
diff --git a/python/paddle/base/framework.py b/python/paddle/base/framework.py
index a306004bca62a8..1d3bbd28873c2e 100644
--- a/python/paddle/base/framework.py
+++ b/python/paddle/base/framework.py
@@ -1262,7 +1262,7 @@ def convert_np_dtype_to_dtype_(np_dtype):
         core.VarDesc.VarType / core.DataType : The data type in Paddle.
 
     """
-    if in_pir_mode():
+    if use_pir_api():
         return pir.core.convert_np_dtype_to_dtype_(np_dtype)
 
     # Convert the data type string to numpy data type.
@@ -1350,11 +1350,15 @@ def _create_tensor(
     **kwargs,
 ):
     if dtype is not None:
-        if not isinstance(dtype, core.VarDesc.VarType):
+        if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
             dtype = convert_np_dtype_to_dtype_(dtype)
+        if isinstance(dtype, core.DataType):
+            dtype = paddle_type_to_proto_type[dtype]
+    else:
+        dtype = core.VarDesc.VarType.FP32
 
     eager_tensor = core.eager.Tensor(
-        dtype if dtype else core.VarDesc.VarType.FP32,
+        dtype,
         list(shape) if shape else [],
         name,
         type if type else core.VarDesc.VarType.LOD_TENSOR,
@@ -7588,8 +7592,12 @@ def __init__(self, shape, dtype, **kwargs):
                 )
 
         if dtype is not None:
-            if not isinstance(dtype, core.VarDesc.VarType):
+            if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
                 dtype = convert_np_dtype_to_dtype_(dtype)
+            if isinstance(dtype, core.DataType):
+                dtype = paddle_type_to_proto_type[dtype]
+        else:
+            dtype = core.VarDesc.VarType.FP32
 
         name = kwargs.get('name', unique_name.generate('_eager_param_base'))
 
@@ -7597,7 +7605,7 @@ def __init__(self, shape, dtype, **kwargs):
             shape = shape.numpy()
 
         super().__init__(
-            dtype if dtype else core.VarDesc.VarType.FP32,
+            dtype,
             list(shape) if shape else [],
             name,
             core.VarDesc.VarType.LOD_TENSOR,
diff --git a/python/paddle/framework/dtype.py b/python/paddle/framework/dtype.py
index 1183d80d035308..aeb93681730dfa 100644
--- a/python/paddle/framework/dtype.py
+++ b/python/paddle/framework/dtype.py
@@ -12,32 +12,130 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import paddle
+
+from ..base import framework
 from ..base.core import (
+    DataType,
     VarDesc,
     finfo as core_finfo,
     iinfo as core_iinfo,
 )
 from ..base.data_feeder import _NUMPY_DTYPE_2_PADDLE_DTYPE
 
-dtype = VarDesc.VarType
-dtype.__qualname__ = "dtype"
-dtype.__module__ = "paddle"
-
-uint8 = VarDesc.VarType.UINT8
-int8 = VarDesc.VarType.INT8
-int16 = VarDesc.VarType.INT16
-int32 = VarDesc.VarType.INT32
-int64 = VarDesc.VarType.INT64
-
-float32 = VarDesc.VarType.FP32
-float64 = VarDesc.VarType.FP64
-float16 = VarDesc.VarType.FP16
-bfloat16 = VarDesc.VarType.BF16
-
-complex64 = VarDesc.VarType.COMPLEX64
-complex128 = VarDesc.VarType.COMPLEX128
 
-bool = VarDesc.VarType.BOOL
+def bind_vartype():
+    global dtype
+    global uint8
+    global int8
+    global int16
+    global int32
+    global int64
+    global float32
+    global float64
+    global float16
+    global bfloat16
+    global complex64
+    global complex128
+    global bool
+
+    dtype = VarDesc.VarType
+    dtype.__qualname__ = "dtype"
+    dtype.__module__ = "paddle"
+
+    uint8 = VarDesc.VarType.UINT8
+    int8 = VarDesc.VarType.INT8
+    int16 = VarDesc.VarType.INT16
+    int32 = VarDesc.VarType.INT32
+    int64 = VarDesc.VarType.INT64
+
+    float32 = VarDesc.VarType.FP32
+    float64 = VarDesc.VarType.FP64
+    float16 = VarDesc.VarType.FP16
+    bfloat16 = VarDesc.VarType.BF16
+
+    complex64 = VarDesc.VarType.COMPLEX64
+    complex128 = VarDesc.VarType.COMPLEX128
+
+    bool = VarDesc.VarType.BOOL
+
+    paddle.dtype = dtype
+    paddle.uint8 = uint8
+    paddle.int8 = int8
+    paddle.int16 = int16
+    paddle.int32 = int32
+    paddle.int64 = int64
+
+    paddle.float32 = float32
+    paddle.float64 = float64
+    paddle.float16 = float16
+    paddle.bfloat16 = bfloat16
+
+    paddle.complex64 = complex64
+    paddle.complex128 = complex128
+    paddle.bool = bool
+
+
+def bind_datatype():
+    global dtype
+    global uint8
+    global int8
+    global int16
+    global int32
+    global int64
+    global float32
+    global float64
+    global float16
+    global bfloat16
+    global complex64
+    global complex128
+    global bool
+
+    dtype = DataType
+    dtype.__qualname__ = "dtype"
+    dtype.__module__ = "paddle"
+
+    uint8 = DataType.UINT8
+    int8 = DataType.INT8
+    int16 = DataType.INT16
+    int32 = DataType.INT32
+    int64 = DataType.INT64
+
+    float32 = DataType.FLOAT32
+    float64 = DataType.FLOAT64
+    float16 = DataType.FLOAT16
+    bfloat16 = DataType.BFLOAT16
+
+    complex64 = DataType.COMPLEX64
+    complex128 = DataType.COMPLEX128
+
+    bool = DataType.BOOL
+
+    paddle.dtype = dtype
+    paddle.uint8 = uint8
+    paddle.int8 = int8
+    paddle.int16 = int16
+    paddle.int32 = int32
+    paddle.int64 = int64
+
+    paddle.float32 = float32
+    paddle.float64 = float64
+    paddle.float16 = float16
+    paddle.bfloat16 = bfloat16
+
+    paddle.complex64 = complex64
+    paddle.complex128 = complex128
+    paddle.bool = bool
+
+
+enable_pir_api = framework.get_flags("FLAGS_enable_pir_api")[
+    "FLAGS_enable_pir_api"
+]
+
+if enable_pir_api:
+    bind_datatype()
+else:
+    bind_vartype()
 
 
 def iinfo(dtype):
@@ -130,9 +228,7 @@ def finfo(dtype):
     """
     import paddle
 
-    if paddle.base.framework.in_pir_mode() and isinstance(
-        dtype, paddle.pir.core.DataType
-    ):
+    if isinstance(dtype, paddle.pir.core.DataType):
         dtype = paddle.base.framework.paddle_type_to_proto_type[dtype]
     elif dtype in _NUMPY_DTYPE_2_PADDLE_DTYPE:
         dtype = _NUMPY_DTYPE_2_PADDLE_DTYPE[dtype]
diff --git a/python/paddle/jit/pir_dy2static/parameter_recorder.py b/python/paddle/jit/pir_dy2static/parameter_recorder.py
index ef0440eaa981b7..646e810ffe3e47 100644
--- a/python/paddle/jit/pir_dy2static/parameter_recorder.py
+++ b/python/paddle/jit/pir_dy2static/parameter_recorder.py
@@ -14,6 +14,7 @@
 
 import paddle
 from paddle.autograd.backward_utils import ValueDict
+from paddle.framework import core
 
 from ..dy2static.program_translator import _program_hash, synchronized
 
@@ -37,8 +38,11 @@ def get(self, program, tensor):
         mappings = self.tensor2value[key]
         if id(tensor) not in mappings:
             non_used_initializer = paddle.nn.initializer.Constant(0.0)
+            dtype = tensor.dtype
+            if isinstance(dtype, core.VarDesc.VarType):
+                vartype_to_datatype[dtype]
             value = create_parameter(
-                dtype=vartype_to_datatype[tensor.dtype],
+                dtype=dtype,
                 shape=tensor.shape,
                 type=tensor.type,
                 initializer=non_used_initializer,
diff --git a/python/paddle/jit/sot/infer_meta.py b/python/paddle/jit/sot/infer_meta.py
index 7f90468bdf4b09..7eebf39e008916 100644
--- a/python/paddle/jit/sot/infer_meta.py
+++ b/python/paddle/jit/sot/infer_meta.py
@@ -16,7 +16,6 @@
 
 import paddle
 from paddle.amp.auto_cast import amp_state
-from paddle.base import framework
 from paddle.base.data_feeder import convert_dtype
 from paddle.base.unique_name import (
     UniqueNameGenerator,
@@ -41,15 +40,20 @@ def __init__(
 
     @staticmethod
     def from_tensor(tensor):
-        # We always use float32 in simulation if AMP is enabled.
         if isinstance(tensor, paddle.pir.Value):
             name = "Value@NoName"
-            persistable = tensor.persistable
-            dtype = framework.paddle_type_to_proto_type[tensor.dtype]
-        else:
+        else:  # For Tensor or Variable
             name = tensor.name
-            persistable = tensor.persistable
-            dtype = tensor.dtype
+        persistable = tensor.persistable
+        dtype = tensor.dtype
+        expected_dtype_class = (
+            paddle.core.DataType
+            if paddle.framework.use_pir_api()
+            else paddle.core.VarDesc.VarType
+        )
+        assert isinstance(dtype, expected_dtype_class)
+
+        # We always use float32 in simulation if AMP is enabled.
         current_amp_state = amp_state()
         if (
             dtype == paddle.float16
diff --git a/python/paddle/jit/sot/opcode_translator/executor/variables/basic.py b/python/paddle/jit/sot/opcode_translator/executor/variables/basic.py
index 7c3490aed0eb86..fe99525fe44a14 100644
--- a/python/paddle/jit/sot/opcode_translator/executor/variables/basic.py
+++ b/python/paddle/jit/sot/opcode_translator/executor/variables/basic.py
@@ -22,8 +22,7 @@
 import numpy as np
 
 import paddle
-from paddle.framework import use_pir_api
-from paddle.pir.core import vartype_to_datatype
+from paddle.framework import core
 
 from ....infer_meta import MetaInfo
 from ....symbolic.statement_ir import Symbol
@@ -61,30 +60,30 @@
 
 
 FP_DTYPE_ABBRS = {
-    paddle.bfloat16: 'bfloat16',
-    paddle.float64: 'float64',
-    paddle.float32: 'float32',
-    paddle.float16: 'float16',
+    core.DataType.BFLOAT16: "bfloat16",
+    core.DataType.FLOAT64: "float64",
+    core.DataType.FLOAT32: "float32",
+    core.DataType.FLOAT16: "float16",
 }
 
 CP_DTYPE_ABBRS = {
-    paddle.complex64: 'complex64',
-    paddle.complex128: 'complex128',
+    core.DataType.COMPLEX64: "complex64",
+    core.DataType.COMPLEX128: "complex128",
 }
 
 INT_DTYPE_ABBRS = {
-    paddle.int8: 'int8',
-    paddle.int16: 'int16',
-    paddle.int32: 'int32',
-    paddle.int64: 'int64',
-    paddle.uint8: 'uint8',
+    core.DataType.INT8: "int8",
+    core.DataType.INT16: "int16",
+    core.DataType.INT32: "int32",
+    core.DataType.INT64: "int64",
+    core.DataType.UINT8: "uint8",
 }
 
 DTYPE_ABBRS = {
     **FP_DTYPE_ABBRS,
     **CP_DTYPE_ABBRS,
     **INT_DTYPE_ABBRS,
-    paddle.bool: 'bool',
+    core.DataType.BOOL: "bool",
 }
 
 
@@ -271,32 +270,14 @@ def make_stringify_guard(self) -> list[StringifyExpression]:
             return object_equal_stringify_guard(self)
 
     def get_py_value(self, allow_tensor=False):
-        if use_pir_api() and isinstance(
-            self.value, paddle.base.core.VarDesc.VarType
-        ):
-            return vartype_to_datatype[self.value]
         return super().get_py_value(allow_tensor)
 
     def get_py_type(self):
-        if use_pir_api() and isinstance(
-            self.value, paddle.base.core.VarDesc.VarType
-        ):
-            return paddle.pir.core.DataType
         return super().get_py_type()
 
     def _reconstruct(self, codegen: PyCodeGen):
         # dtype of paddle.Tensor is hashable, we can just load it as const var
-        if use_pir_api() and isinstance(
-            self.value, paddle.base.core.VarDesc.VarType
-        ):
-            assert (
-                self.value in paddle.pir.core.vartype_to_datatype
-            ), f"Unknow dtype {self.value}"
-            codegen.gen_load_const(
-                paddle.pir.core.vartype_to_datatype[self.value]
-            )
-        else:
-            codegen.gen_load_const(self.value)
+        codegen.gen_load_const(self.value)
 
     @property
     def main_info(self) -> dict[str, Any]:
@@ -306,7 +287,9 @@ def main_info(self) -> dict[str, Any]:
 
     @VariableFactory.register_from_value()
     def from_value(value: Any, graph: FunctionGraph, tracker: Tracker):
-        if isinstance(value, paddle.dtype):
+        if isinstance(
+            value, (paddle.core.VarDesc.VarType, paddle.core.DataType)
+        ):
             return TensorDtypeVariable(value, graph, tracker)
 
 
@@ -410,15 +393,18 @@ def get_iter(self):
 
     @property
     def main_info(self) -> dict[str, Any]:
+        dtype = self.meta.dtype
+        if isinstance(dtype, paddle.core.VarDesc.VarType):
+            dtype = paddle.pir.core.vartype_to_datatype[dtype]
         return {
             "shape": self.meta.shape,
-            "dtype": DTYPE_ABBRS[self.meta.dtype],
+            "dtype": DTYPE_ABBRS[dtype],
             "stop_gradient": self.meta.stop_gradient,
             "var_name": self.var_name,
         }
 
     def getitem(self, key):
-        return self.graph.call_tensor_method('__getitem__', self, key)
+        return self.graph.call_tensor_method("__getitem__", self, key)
 
     def setitem(self, key, value):
         self.graph.add_global_guarded_variable(value)
@@ -502,16 +488,22 @@ def is_tensor(self):
 
     def is_complex(self):
         dtype = self.meta.dtype
+        if isinstance(dtype, paddle.core.VarDesc.VarType):
+            dtype = paddle.pir.core.vartype_to_datatype[dtype]
         is_cp_dtype = dtype in CP_DTYPE_ABBRS
         return ConstantVariable(is_cp_dtype, self.graph, DummyTracker([self]))
 
     def is_integer(self):
         dtype = self.meta.dtype
+        if isinstance(dtype, paddle.core.VarDesc.VarType):
+            dtype = paddle.pir.core.vartype_to_datatype[dtype]
         is_int_dtype = dtype in INT_DTYPE_ABBRS
         return ConstantVariable(is_int_dtype, self.graph, DummyTracker([self]))
 
     def is_floating_point(self):
         dtype = self.meta.dtype
+        if isinstance(dtype, paddle.core.VarDesc.VarType):
+            dtype = paddle.pir.core.vartype_to_datatype[dtype]
         is_fp_dtype = dtype in FP_DTYPE_ABBRS
         return ConstantVariable(is_fp_dtype, self.graph, DummyTracker([self]))
 
diff --git a/python/paddle/nn/clip.py b/python/paddle/nn/clip.py
index 8e3282e766fffa..0f551b1aa6c416 100644
--- a/python/paddle/nn/clip.py
+++ b/python/paddle/nn/clip.py
@@ -708,11 +708,11 @@ def _dygraph_clip(self, params_grads):
                 )
 
             if (
-                sum_square.dtype == core.VarDesc.VarType.FP16
-                or sum_square.dtype == core.VarDesc.VarType.BF16
+                sum_square.dtype == paddle.float16
+                or sum_square.dtype == paddle.bfloat16
             ):
                 sum_square_list_fp16.append(sum_square)
-            elif sum_square.dtype == core.VarDesc.VarType.FP32:
+            elif sum_square.dtype == paddle.float32:
                 sum_square_list_fp32.append(sum_square)
             else:
                 sum_square_list.append(sum_square)
diff --git a/python/paddle/nn/layer/rnn.py b/python/paddle/nn/layer/rnn.py
index f8b3dfb7b515ea..de848b9e16cced 100644
--- a/python/paddle/nn/layer/rnn.py
+++ b/python/paddle/nn/layer/rnn.py
@@ -1555,6 +1555,11 @@ def flatten_parameters(self):
             )
             if in_dynamic_mode():
                 with paddle.no_grad():
+                    dtype = params[0].dtype
+                    if isinstance(dtype, core.DataType):
+                        dtype = paddle.base.framework.paddle_type_to_proto_type[
+                            dtype
+                        ]
                     _legacy_C_ops.coalesce_tensor(
                         self._all_weights,
                         self._all_weights,
@@ -1564,7 +1569,7 @@ def flatten_parameters(self):
                         "use_align",
                         False,
                         "dtype",
-                        params[0].dtype,
+                        dtype,
                     )
                     return
             # for static-graph, append coalesce_tensor into startup program
diff --git a/python/paddle/pir_utils.py b/python/paddle/pir_utils.py
index e52837889d71f0..9adf1d04710894 100644
--- a/python/paddle/pir_utils.py
+++ b/python/paddle/pir_utils.py
@@ -16,6 +16,7 @@
 from functools import wraps
 
 import paddle
+from paddle.framework.dtype import bind_datatype, bind_vartype
 
 
 class IrGuard:
@@ -49,11 +50,13 @@ def __enter__(self):
             paddle.enable_static()
         paddle.framework.set_flags({"FLAGS_enable_pir_api": True})
         paddle.base.framework.global_var._use_pir_api_ = True
+        bind_datatype()
         self._switch_to_pir()
 
     def __exit__(self, exc_type, exc_val, exc_tb):
         paddle.framework.set_flags({"FLAGS_enable_pir_api": False})
         paddle.base.framework.global_var._use_pir_api_ = False
+        bind_vartype()
         self._switch_to_old_ir()
         if self.in_dygraph_outside:
             paddle.disable_static()
diff --git a/python/paddle/tensor/random.py b/python/paddle/tensor/random.py
index d2a0c46369fadf..496ec9965d0cfc 100644
--- a/python/paddle/tensor/random.py
+++ b/python/paddle/tensor/random.py
@@ -23,6 +23,7 @@
     in_dynamic_mode,
     in_dynamic_or_pir_mode,
     in_pir_mode,
+    use_pir_api,
 )
 
 from ..base.data_feeder import (
@@ -1100,9 +1101,9 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None):
         low = 0
     if dtype is None:
         dtype = core.VarDesc.VarType.INT64
-        if in_pir_mode():
+        if use_pir_api():
             dtype = DataType.INT64
-    elif not isinstance(dtype, core.VarDesc.VarType):
+    elif not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
     if in_dynamic_mode():
diff --git a/test/dygraph_to_static/test_declarative.py b/test/dygraph_to_static/test_declarative.py
index 1ee370b1745bfd..2523efee2b395a 100644
--- a/test/dygraph_to_static/test_declarative.py
+++ b/test/dygraph_to_static/test_declarative.py
@@ -249,7 +249,7 @@ def test_with_different_input(self):
 
         foo = paddle.jit.to_static(foo_func)
 
-        # [16, 10] + [10] (varbase)
+        # [16, 10] + [10] (Tensor)
         out_1 = foo(paddle.to_tensor(x_data), paddle.to_tensor(y_data))
         np.testing.assert_allclose(x_data + y_data, out_1.numpy(), rtol=1e-05)
         self.assertTrue(len(foo.program_cache) == 1)
diff --git a/test/legacy_test/test_std_layer.py b/test/legacy_test/test_std_layer.py
index aed3e750402e5c..9c42e7aae3829b 100644
--- a/test/legacy_test/test_std_layer.py
+++ b/test/legacy_test/test_std_layer.py
@@ -116,6 +116,7 @@ def test_alias(self):
 
 class TestStdError(unittest.TestCase):
     def test_error(self):
+        paddle.enable_static()
         with paddle.static.program_guard(paddle.static.Program()):
             x = paddle.static.data('X', [2, 3, 4], 'int32')
             self.assertRaises(TypeError, paddle.std, x)