update unbind norm add CUDAPlace api doc information (#29322) (#29391)

* enhance array_to_lod_tensor_op lod_tensor_to_array_op errors information. test=develop

* fix format. test=develop

* format fix. test=develop

* add lod_rank_table. test=develop

* fix format. test=develop

* fix doc info. test=develop

* fix np error

* add unbind dygraph api. test=develop

* fix unbind doc.test=develop

paddle/fluid/pybind/pybind.cc

@@ -1375,7 +1375,6 @@ All parameter, weight, gradient are variables in Paddle.
           import paddle
 
           place = paddle.CUDAPlace(0)
-          paddle.disable_static(place)
 
         )DOC")
       .def("__init__",

python/paddle/tensor/linalg.py

@@ -173,8 +173,6 @@ def matmul(x, y, transpose_x=False, transpose_y=False, name=None):
 
 def norm(x, p='fro', axis=None, keepdim=False, name=None):
     """
-	:alias_main: paddle.norm
-	:alias: paddle.norm,paddle.tensor.norm,paddle.tensor.linalg.norm
 
     Returns the matrix norm (Frobenius) or vector norm (the 1-norm, the Euclidean
     or 2-norm, and in general the p-norm for p > 0) of a given tensor.
@@ -206,7 +204,6 @@ def norm(x, p='fro', axis=None, keepdim=False, name=None):
             
             import paddle
             import numpy as np
-            paddle.disable_static()
             shape=[2, 3, 4]
             np_input = np.arange(24).astype('float32') - 12
             np_input = np_input.reshape(shape)

python/paddle/tensor/manipulation.py

@@ -791,29 +791,29 @@ def gather(x, index, axis=None, name=None):
 
 def unbind(input, axis=0):
     """
-	:alias_main: paddle.tensor.unbind
-	:alias: paddle.tensor.unbind,paddle.tensor.manipulation.unbind
 
     Removes a tensor dimension, then split the input tensor into multiple sub-Tensors.
-    Args:
-        input (Variable): The input variable which is an N-D Tensor, data type being float32, float64, int32 or int64.
 
-        axis (int32|int64, optional): A scalar with type ``int32|int64`` shape [1]. The dimension along which to unbind. If :math:`axis < 0`, the
-            dimension to unbind along is :math:`rank(input) + axis`. Default is 0.
+    Args:
+        input (Tensor): The input variable which is an N-D Tensor, data type being float32, float64, int32 or int64.
+        axis (int32|int64, optional): A scalar with type ``int32|int64`` shape [1]. The dimension along which to unbind. 
+            If :math:`axis < 0`, the dimension to unbind along is :math:`rank(input) + axis`. Default is 0.
     Returns:
-        list(Variable): The list of segmented Tensor variables.
+        list(Tensor): The list of segmented Tensor variables.
 
     Example:
         .. code-block:: python
+
             import paddle
+            import numpy as np
             # input is a variable which shape is [3, 4, 5]
-            input = paddle.fluid.data(
-                 name="input", shape=[3, 4, 5], dtype="float32")
-            [x0, x1, x2] = paddle.tensor.unbind(input, axis=0)
+            np_input = np.random.rand(3, 4, 5).astype('float32')
+            input = paddle.to_tensor(np_input)
+            [x0, x1, x2] = paddle.unbind(input, axis=0)
             # x0.shape [4, 5]
             # x1.shape [4, 5]
             # x2.shape [4, 5]
-            [x0, x1, x2, x3] = paddle.tensor.unbind(input, axis=1)
+            [x0, x1, x2, x3] = paddle.unbind(input, axis=1)
             # x0.shape [3, 5]
             # x1.shape [3, 5]
             # x2.shape [3, 5]
@@ -837,6 +837,8 @@ def unbind(input, axis=0):
         helper.create_variable_for_type_inference(dtype=helper.input_dtype())
         for i in range(num)
     ]
+    if in_dygraph_mode():
+        return core.ops.unbind(input, num, 'axis', axis)
 
     helper.append_op(
         type="unbind",