Modify paddle.static.nn.cond doc (#36694) (#36767)

Update `cond` English document

python/paddle/fluid/layers/control_flow.py

@@ -2316,10 +2316,13 @@ def cond(pred, true_fn=None, false_fn=None, name=None):
         the same shape because of dataflow model of PaddlePaddle while the
         tensors in the tuples or the lists can have different shapes.
 
-        2. Any tensors or operations created outside of ``true_fn`` and
-        ``false_fn`` will be executed regardless of which branch is selected at
-        runtime. This has frequently surprised users who expected a lazy
-        semantics. For example:
+        2. This API could be used under both static mode or dygraph mode. If it
+        is in dygraph mode, the API only runs one branch based on condition.
+
+        3. If it is in static mode, any tensors or operations created outside 
+        or inside of ``true_fn`` and ``false_fn`` will be in net building
+        regardless of which branch is selected at runtime. This has frequently
+        surprised users who expected a lazy semantics. For example:
 
         .. code-block:: python
 
@@ -2328,9 +2331,11 @@ def cond(pred, true_fn=None, false_fn=None, name=None):
             a = paddle.zeros((1, 1))
             b = paddle.zeros((1, 1))
             c = a * b
-            out = paddle.nn.cond(a < b, lambda: a + c, lambda: b * b)
+            out = paddle.static.nn.cond(a < b, lambda: a + c, lambda: b * b)
 
-        No matter whether ``a < b`` , ``c = a * b`` will run.
+        No matter whether ``a < b`` , ``c = a * b`` will be in net building and
+        run. ``a + c`` and ``b * b`` will be in net building, but only one
+        branch will be executed during runtime.
 
     Args:
         pred(Tensor): A boolean tensor whose numel should be 1. The boolean
@@ -2366,24 +2371,24 @@ def cond(pred, true_fn=None, false_fn=None, name=None):
             #     return 3, 2
             #
 
-
             def true_func():
-                return paddle.fill_constant(shape=[1, 2], dtype='int32',
-                                            value=1), paddle.fill_constant(shape=[2, 3],
-                                                                           dtype='bool',
-                                                                           value=True)
+                return paddle.full(shape=[1, 2], dtype='int32',
+                                   fill_value=1), paddle.full(shape=[2, 3],
+                                                              dtype='bool',
+                                                              fill_value=True)
 
 
             def false_func():
-                return paddle.fill_constant(shape=[3, 4], dtype='float32',
-                                            value=3), paddle.fill_constant(shape=[4, 5],
-                                                                           dtype='int64',
-                                                                           value=2)
+                return paddle.full(shape=[3, 4], dtype='float32',
+                                   fill_value=3), paddle.full(shape=[4, 5],
+                                                              dtype='int64',
+                                                              fill_value=2)
+
 
-            x = paddle.fill_constant(shape=[1], dtype='float32', value=0.1)
-            y = paddle.fill_constant(shape=[1], dtype='float32', value=0.23)
+            x = paddle.full(shape=[1], dtype='float32', fill_value=0.1)
+            y = paddle.full(shape=[1], dtype='float32', fill_value=0.23)
             pred = paddle.less_than(x=x, y=y, name=None)
-            ret = paddle.nn.cond(pred, true_func, false_func)
+            ret = paddle.static.nn.cond(pred, true_func, false_func)
             # ret is a tuple containing 2 tensors
             # ret[0] = [[1 1]]
             # ret[1] = [[ True  True  True]