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fix api doc,test=develop (#17241)

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revert-17304-fix_default_paddle_version
Zeng Jinle 7 years ago committed by GitHub
parent 4f8594088d
commit f2fa3f7300
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4 changed files with 124 additions and 24 deletions
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4
paddle/fluid/API.spec
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@ -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'))

125
paddle/fluid/pybind/pybind.cc
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@ -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); });

15
python/paddle/fluid/lod_tensor.py
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@ -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

4
python/paddle/fluid/param_attr.py
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@ -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)
"""

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