fix api doc,test=develop (#17241)

paddle/fluid/API.spec

@@ -32,8 +32,8 @@ paddle.fluid.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], var
 paddle.fluid.DistributeTranspilerConfig.__init__ 
 paddle.fluid.ParallelExecutor.__init__ (ArgSpec(args=['self', 'use_cuda', 'loss_name', 'main_program', 'share_vars_from', 'exec_strategy', 'build_strategy', 'num_trainers', 'trainer_id', 'scope'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 1, 0, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.ParallelExecutor.run (ArgSpec(args=['self', 'fetch_list', 'feed', 'feed_dict', 'return_numpy'], varargs=None, keywords=None, defaults=(None, None, True)), ('document', '2cb4bd74481861345c70228a0f57620c'))
-paddle.fluid.create_lod_tensor (ArgSpec(args=['data', 'recursive_seq_lens', 'place'], varargs=None, keywords=None, defaults=None), ('document', '8e7bb21e83ff4604f5b379672e285b94'))
-paddle.fluid.create_random_int_lodtensor (ArgSpec(args=['recursive_seq_lens', 'base_shape', 'place', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '368f638b99f1dfe59e9b02aa6f077752'))
+paddle.fluid.create_lod_tensor (ArgSpec(args=['data', 'recursive_seq_lens', 'place'], varargs=None, keywords=None, defaults=None), ('document', 'b82ea20e2dc5ff2372e0643169ca47ff'))
+paddle.fluid.create_random_int_lodtensor (ArgSpec(args=['recursive_seq_lens', 'base_shape', 'place', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '74dc6d23185d90a7a50fbac19f5b65fb'))
 paddle.fluid.DataFeedDesc.__init__ (ArgSpec(args=['self', 'proto_file'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.DataFeedDesc.desc (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '4294493e31c4bc9fc4bd48753044235f'))
 paddle.fluid.DataFeedDesc.set_batch_size (ArgSpec(args=['self', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', '8d9f44601e0a99dd431f14fd9250cd21'))

paddle/fluid/pybind/pybind.cc

@@ -383,28 +383,37 @@ PYBIND11_MODULE(core, m) {
     LoD is short for Level of Details and is usually used for varied sequence
     length. You can skip the following comment if you don't need optional LoD.
 
-  For example:
-     A LoDTensor X can look like the example below. It contains 2 sequences.
-     The first has length 2 and the second has length 3, as described by x.lod.
+    For example, a LoDTensor X can look like the example below. It contains 
+    2 sequences. The first has length 2 and the second has length 3, as 
+    described by x.lod.
 
-     The first tensor dimension 5=2+3 is calculated from LoD if it's available.
-     It means the total number of sequence element. In X, each element has 2
-     columns, hence [5, 2].
+    The first tensor dimension 5=2+3 is calculated from LoD if it's available.
+    It means the total number of sequence element. In X, each element has 2
+    columns, hence [5, 2].
 
-      x.lod  = [[2, 3]]
-      x.data = [[1, 2], [3, 4],
-                [5, 6], [7, 8], [9, 10]]
-      x.shape = [5, 2]
+    x.lod  = [[2, 3]]
+     
+    x.data = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]]
 
-      LoD can have multiple levels (for example, a paragraph can have multiple
-      sentences and a sentence can have multiple words). In the following
-      LodTensor Y, the lod_level is 2. It means there are 2 sequence, the
-      first sequence length is 2 (has 2 sub-sequences), the second one's
-      length is 1. The first sequence's 2 sub-sequences have length 2 and 2,
-      respectively. And the second sequence's 1 sub-sequence has length 3.
+    x.shape = [5, 2]
 
-      y.lod = [[2 1], [2 2 3]]
-      y.shape = [2+2+3, ...]
+    LoD can have multiple levels (for example, a paragraph can have multiple
+    sentences and a sentence can have multiple words). In the following
+    LodTensor Y, the lod_level is 2. It means there are 2 sequence, the
+    first sequence length is 2 (has 2 sub-sequences), the second one's
+    length is 1. The first sequence's 2 sub-sequences have length 2 and 2,
+    respectively. And the second sequence's 1 sub-sequence has length 3.
+
+    y.lod = [[2 1], [2 2 3]]
+
+    y.shape = [2+2+3, ...]
+
+    Examples:
+        .. code-block:: python
+
+          import paddle.fluid as fluid
+
+          t = fluid.LoDTensor()
 
   Note:
       In above description, LoD is length-based. In Paddle internal
@@ -416,7 +425,6 @@ PYBIND11_MODULE(core, m) {
       self-explanatory. In this case, it must be length-based. Due to history
       reasons. when LoD is called lod in public API, it might be offset-based.
       Users should be careful about it.
-
         )DOC")
       .def("__array__", [](Tensor &self) { return TensorToPyArray(self); })
       .def("__init__",
@@ -454,6 +462,16 @@ PYBIND11_MODULE(core, m) {
 
            Args:
                lod (List[List[int]]): the lod to be set.
+
+           Examples:
+               .. code-block:: python
+
+                 import paddle.fluid as fluid
+                 import numpy as np
+
+                 t = fluid.LoDTensor()
+                 t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+                 t.set_lod([[0, 2, 5]])
            )DOC")
       .def("set_recursive_sequence_lengths",
            [](LoDTensor &self, const std::vector<std::vector<size_t>>
@@ -480,6 +498,16 @@ PYBIND11_MODULE(core, m) {
 
            Args:
                 recursive_sequence_lengths (List[List[int]]): sequence lengths.
+
+           Examples:
+               .. code-block:: python
+
+                 import paddle.fluid as fluid
+                 import numpy as np
+
+                 t = fluid.LoDTensor()
+                 t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+                 t.set_recursive_sequence_lengths([[2, 3]])
            )DOC")
       .def("lod",
            [](LoDTensor &self) -> std::vector<std::vector<size_t>> {
@@ -495,6 +523,17 @@ PYBIND11_MODULE(core, m) {
 
            Returns:
                out (List[List[int]]): the lod of the LoDTensor.
+
+           Examples:
+               .. code-block:: python
+
+                 import paddle.fluid as fluid
+                 import numpy as np
+
+                 t = fluid.LoDTensor()
+                 t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+                 t.set_lod([[0, 2, 5]])
+                 print(t.lod()) # [[0, 2, 5]]
            )DOC")
       // Set above comments of set_lod.
       .def("recursive_sequence_lengths",
@@ -511,6 +550,17 @@ PYBIND11_MODULE(core, m) {
 
            Returns:
                out (List[List[int]): the sequence lengths.
+
+           Examples:
+               .. code-block:: python
+
+                 import paddle.fluid as fluid
+                 import numpy as np
+
+                 t = fluid.LoDTensor()
+                 t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+                 t.set_recursive_sequence_lengths([[2, 3]])
+                 print(t.recursive_sequence_lengths()) # [[2, 3]]
            )DOC")
       .def("has_valid_recursive_sequence_lengths",
            [](LoDTensor &self) -> bool {
@@ -523,6 +573,17 @@ PYBIND11_MODULE(core, m) {
 
            Returns:
                out (bool): whether the lod is valid.
+
+           Examples:
+               .. code-block:: python
+
+                 import paddle.fluid as fluid
+                 import numpy as np
+
+                 t = fluid.LoDTensor()
+                 t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+                 t.set_recursive_sequence_lengths([[2, 3]])
+                 print(t.has_valid_recursive_sequence_lengths()) # True
            )DOC")
       .def("__getitem__", PySliceTensor, py::return_value_policy::reference,
            R"DOC(
@@ -985,7 +1046,16 @@ All parameter, weight, gradient are variables in Paddle.
         return res;
       });
 
-  py::class_<LoDTensorArray>(m, "LoDTensorArray")
+  py::class_<LoDTensorArray>(m, "LoDTensorArray", R"DOC(
+    Array of LoDTensor.
+
+    Examples:
+        .. code-block:: python
+        
+          import paddle.fluid as fluid
+
+          arr = fluid.LoDTensorArray()
+)DOC")
       .def("__init__",
            [](LoDTensorArray &instance) { new (&instance) LoDTensorArray(); })
       .def("__getitem__",
@@ -1004,7 +1074,20 @@ All parameter, weight, gradient are variables in Paddle.
              self.back().ShareDataWith(t);
              self.back().set_lod(t.lod());
            },
-           py::arg("tensor"), "Append a LoDensor to LoDTensorArray.");
+           py::arg("tensor"), R"DOC(
+             Append a LoDensor to LoDTensorArray.
+
+             Examples:
+                 .. code-block:: python
+
+                   import paddle.fluid as fluid
+                   import numpy as np
+
+                   arr = fluid.LoDTensorArray()
+                   t = fluid.LoDTensor()
+                   t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+                   arr.append(t)
+           )DOC");
 
   m.def("IsInplace",
         [](std::string op) -> bool { return operators::IsInplace(op); });

python/paddle/fluid/lod_tensor.py

@@ -47,6 +47,13 @@ def create_lod_tensor(data, recursive_seq_lens, place):
         sentence. This length-based :code:`recursive_seq_lens` [[2, 3]] will be converted to
         offset-based LoD [[0, 2, 5]] inside the function call.
 
+        .. code-block:: python
+
+          import paddle.fluid as fluid
+          import numpy as np
+
+          t = fluid.create_lod_tensor(np.ndarray([5, 30]), [[2, 3]], fluid.CPUPlace())
+
     Please reference :ref:`api_guide_low_level_lod_tensor` for more details
     regarding LoD.
 
@@ -127,6 +134,14 @@ def create_random_int_lodtensor(recursive_seq_lens, base_shape, place, low,
 
     Returns:
         A fluid LoDTensor object with tensor data and recursive_seq_lens info.
+
+    Examples:
+        .. code-block:: python
+
+          import paddle.fluid as fluid
+
+          t = fluid.create_random_int_lodtensor(recursive_seq_lens=[[2, 3]], 
+                base_shape=[30], place=fluid.CPUPlace(), low=0, high=10)
     """
     assert isinstance(base_shape, list), "base_shape should be a list"
     # append the total number of basic elements to the front of its shape

python/paddle/fluid/param_attr.py

@@ -48,11 +48,13 @@ class ParamAttr(object):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid as fluid
+
             w_param_attrs = fluid.ParamAttr(name="fc_weight",
                                             learning_rate=0.5,
                                             regularizer=fluid.regularizer.L2Decay(1.0),
                                             trainable=True)
-	    x = fluid.layers.data(name='X', shape=[1], dtype='float32')
+            x = fluid.layers.data(name='X', shape=[1], dtype='float32')
             y_predict = fluid.layers.fc(input=x, size=10, param_attr=w_param_attrs)
     """