[API2.0] Fix documents of 6 APIs to fit API2.0: (#28514)

1. Remove 'fluid';
2. Variable -> Tensor

APIs:
 sum, convert_call, convert_ifelse,
 convert_logical_and, convert_logical_or, convert_logical_not

python/paddle/fluid/dygraph/dygraph_to_static/convert_call_func.py

@@ -98,20 +98,22 @@ def convert_call(func):
     Examples:
         .. code-block:: python
 
-          import paddle.fluid as fluid
-          from paddle.fluid.dygraph.dygraph_to_static import convert_call
+            import paddle
+            from paddle.jit.dy2static import convert_call
 
+            paddle.enable_static()
             def dyfunc(x):
-              if fluid.layers.mean(x) < 0:
+                if paddle.mean(x) < 0:
                     x_v = x - 1
                 else:
                     x_v = x + 1
-
                 return x_v
+
             new_func = convert_call(dyfunc)
-          x = fluid.layers.fill_constant(shape=[3, 3], value=0, dtype='float64')
+            x = paddle.tensor.manipulation.fill_constant(shape=[3, 3], value=0, dtype='float64')
             x_v = new_func(x)
-          exe = fluid.Executor(fluid.CPUPlace())
+
+            exe = paddle.static.Executor(paddle.CPUPlace())
             out = exe.run(fetch_list=[x_v])
             print(out[0])
             # [[1. 1. 1.]

python/paddle/fluid/dygraph/dygraph_to_static/convert_operators.py

@@ -44,7 +44,7 @@ def convert_while_loop(cond, body, loop_vars):
 
 
 def _run_paddle_while_loop(cond, body, loop_vars):
-    # NOTE: loop_vars of Paddle op `control_flow.while_loop` must be Paddle Variable.
+    # NOTE: loop_vars of Paddle op `control_flow.while_loop` must be Paddle Tensors.
     loop_vars = [to_static_variable(var) for var in loop_vars]
     loop_vars = control_flow.while_loop(cond, body, loop_vars)
     return loop_vars
@@ -61,8 +61,8 @@ def convert_logical_and(x, y):
     A function representation of a Python ``and`` statement.
 
     Args:
-        x(bool|Variable): Left hand operand of ``and`` operator.
-        y(bool|Variable): Right hand operand of ``and`` operator.
+        x(bool|Tensor): Left hand operand of ``and`` operator.
+        y(bool|Tensor): Right hand operand of ``and`` operator.
 
     Returns:
         A python bool variable or a bool Tensor.
@@ -94,8 +94,8 @@ def convert_logical_or(x, y):
     A function representation of a Python ``or`` statement.
 
     Args:
-        x(bool|Variable): Left hand operand of ``or`` operator.
-        y(bool|Variable): Right hand operand of ``or`` operator.
+        x(bool|Tensor): Left hand operand of ``or`` operator.
+        y(bool|Tensor): Right hand operand of ``or`` operator.
 
     Returns:
         A python bool variable or a bool Tensor.
@@ -127,7 +127,7 @@ def convert_logical_not(x):
     A function representation of a Python ``not`` statement.
 
     Args:
-        x(bool|Variable): Operand of of ``not`` operator.
+        x(bool|Tensor): Operand of of ``not`` operator.
 
     Returns:
         A python bool variable or a bool Tensor.
@@ -153,7 +153,7 @@ def convert_ifelse(pred, true_fn, false_fn, true_args, false_args, return_vars):
     A function representation of a Python ``if/else`` statement.
 
     Args:
-        pred(bool|Variable): A boolean variable which determines whether to return the result of ``true_fn`` or ``false_fn`` .
+        pred(bool|Tensor): A boolean Tensor which determines whether to return the result of ``true_fn`` or ``false_fn`` .
         true_fn(callable): A callable to be performed if ``pred`` is true.
         false_fn(callable): A callable to be performed if ``pred`` is false.
         true_args(tuple): Parameters of ``true_fn``.
@@ -175,7 +175,7 @@ def _run_paddle_cond(pred, true_fn, false_fn, true_args, false_args,
                      return_vars):
 
     return_var_ids = [id(var) for var in return_vars]
-    # NOTE 1: return vars of Paddle op `control_flow.cond` must be Paddle Variable
+    # NOTE 1: Returned vars of Paddle op `control_flow.cond` must be Paddle Tensors
     # NOTE 2: Here uses id(var) not var, because `if var in return_var` use operator `==`,
     #  which will call `fluid.layers.equal` and causes error when var in return_vars is not initialized.
     true_args = [

python/paddle/tensor/math.py

@@ -627,7 +627,6 @@ def sum(x, axis=None, dtype=None, keepdim=False, name=None):
         .. code-block:: python
 
             import paddle
-            paddle.disable_static()
 
             # x is a Tensor with following elements:
             #    [[0.2, 0.3, 0.5, 0.9]