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modify some cn doc #2710

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Sep 30, 2020
Merged

modify some cn doc #2710

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36a98db
modify some cn doc, test=develop
wanghuancoder Sep 28, 2020
84413da
move unique_name to paddle.utils, test=develop
wanghuancoder Sep 29, 2020
1a02835
refine doc, test=develop
wanghuancoder Sep 29, 2020
62ed3bd
fix alias tab, test=develop
wanghuancoder Sep 29, 2020
ee5b6c0
fix alias bug, test=develop
wanghuancoder Sep 29, 2020
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3 changes: 3 additions & 0 deletions doc/paddle/api/alias_api_mapping
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Expand Up @@ -569,3 +569,6 @@ paddle.metric.metrics.Accuracy paddle.metric.Accuracy
paddle.metric.metrics.Precision paddle.metric.Precision
paddle.metric.metrics.Recall paddle.metric.Recall
paddle.metric.metrics.Auc paddle.metric.Auc
paddle.fluid.unique_name.guard paddle.utils.unique_name.guard
paddle.fluid.unique_name.switch paddle.utils.unique_name.switch
paddle.fluid.unique_name.generate paddle.utils.unique_name.generate
1 change: 0 additions & 1 deletion doc/paddle/api/not_display_doc_list
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@@ -1,4 +1,3 @@
paddle.utils
paddle.incubate
paddle.hapi.progressbar.ProgressBar
paddle.fluid.contrib
Expand Down
36 changes: 17 additions & 19 deletions doc/paddle/api/paddle/fluid/dygraph/container/Sequential_cn.rst
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Expand Up @@ -3,7 +3,7 @@
Sequential
-------------------------------

.. py:class:: paddle.fluid.dygraph.Sequential(*layers)
.. py:class:: paddle.nn.Sequential(*layers)



Expand All @@ -19,24 +19,22 @@ Sequential

.. code-block:: python

import paddle.fluid as fluid
import paddle
import numpy as np
data = np.random.uniform(-1, 1, [30, 10]).astype('float32')
with fluid.dygraph.guard():
data = fluid.dygraph.to_variable(data)
# 使用 iterable Layers 创建 Sequential 容器
model1 = fluid.dygraph.Sequential(
fluid.Linear(10, 1), fluid.Linear(1, 2)
)
model1[0] # 访问第一个子层
res1 = model1(data) # 顺序执行
# 使用 iterable name Layer 对创建 Sequential 容器
model2 = fluid.dygraph.Sequential(
('l1', fluid.Linear(10, 2)),
('l2', fluid.Linear(2, 3))
)
model2['l1'] # 访问 l1 子层
model2.add_sublayer('l3', fluid.Linear(3, 3)) # 添加子层
res2 = model2(data) # 顺序执行

data = paddle.to_tensor(data)
# create Sequential with iterable Layers
model1 = paddle.nn.Sequential(
paddle.nn.Linear(10, 1), paddle.nn.Linear(1, 2)
)
model1[0] # access the first layer
res1 = model1(data) # sequential execution
# create Sequential with name Layer pairs
model2 = paddle.nn.Sequential(
('l1', paddle.nn.Linear(10, 2)),
('l2', paddle.nn.Linear(2, 3))
)
model2['l1'] # access l1 layer
model2.add_sublayer('l3', paddle.nn.Linear(3, 3)) # add sublayer
res2 = model2(data) # sequential execution

16 changes: 7 additions & 9 deletions doc/paddle/api/paddle/fluid/layers/bilinear_tensor_product_cn.rst
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Expand Up @@ -4,7 +4,7 @@ bilinear_tensor_product
-------------------------------


.. py:function:: paddle.fluid.layers.bilinear_tensor_product(x, y, size, act=None, name=None, param_attr=None, bias_attr=None)
.. py:function:: paddle.static.nn.bilinear_tensor_product(x, y, size, act=None, name=None, param_attr=None, bias_attr=None)



Expand Down Expand Up @@ -32,19 +32,17 @@ bilinear_tensor_product
- **param_attr** (ParamAttr，可选) ：指定权重参数属性的对象。默认值为 None，表示使用默认的权重参数属性。具体用法请参见 :ref:`cn_api_fluid_ParamAttr` 。
- **bias_attr** (ParamAttr，可选) : 指定偏置参数属性的对象。默认值为 None，表示使用默认的偏置参数属性。具体用法请参见 :ref:`cn_api_fluid_ParamAttr` 。

返回： 一个形为 [batch_size, size] 的 2-D 张量。

返回类型：Variable
返回： Variable, 一个形为 [batch_size, size] 的 2-D 张量。

**代码示例：**

.. code-block:: python

import paddle.fluid as fluid
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返回类型 和 返回写在一起哈，如
【返回：Variable，一个xxx】

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done,thx!

layer1 = fluid.layers.data("t1", shape=[-1, 5], dtype="float32")
layer2 = fluid.layers.data("t2", shape=[-1, 4], dtype="float32")
tensor = fluid.layers.bilinear_tensor_product(x=layer1, y=layer2, size=1000)

import paddle
paddle.enable_static()
layer1 = paddle.static.data("t1", shape=[-1, 5], dtype="float32")
layer2 = paddle.static.data("t2", shape=[-1, 4], dtype="float32")
tensor = paddle.static.nn.bilinear_tensor_product(x=layer1, y=layer2, size=1000)



15 changes: 6 additions & 9 deletions doc/paddle/api/paddle/fluid/unique_name/generate_cn.rst
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Expand Up @@ -3,7 +3,7 @@
generate
-------------------------------

.. py:function:: paddle.fluid.unique_name.generate(key)
.. py:function:: paddle.utils.unique_name.generate(key)



Expand All @@ -13,17 +13,14 @@ generate
参数:
- **key** (str) - 产生的唯一名称的前缀。

返回：含前缀key的唯一名称。

返回类型：str。
返回：str, 含前缀key的唯一名称。

**代码示例**

.. code-block:: python
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返回类型同上

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done,thx!


import paddle.fluid as fluid
name1 = fluid.unique_name.generate('fc')
name2 = fluid.unique_name.generate('fc')
print(name1, name2) # fc_0, fc_1

import paddle
name1 = paddle.utils.unique_name.generate('fc')
name2 = paddle.utils.unique_name.generate('fc')
print(name1, name2) # fc_0, fc_1

27 changes: 13 additions & 14 deletions doc/paddle/api/paddle/fluid/unique_name/guard_cn.rst
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Expand Up @@ -3,7 +3,7 @@
guard
-------------------------------

.. py:function:: paddle.fluid.unique_name.guard(new_generator=None)
.. py:function:: paddle.utils.unique_name.guard(new_generator=None)



Expand All @@ -19,17 +19,16 @@ guard

.. code-block:: python

import paddle.fluid as fluid
with fluid.unique_name.guard():
name_1 = fluid.unique_name.generate('fc')
with fluid.unique_name.guard():
name_2 = fluid.unique_name.generate('fc')
print(name_1, name_2) # fc_0, fc_0

with fluid.unique_name.guard('A'):
name_1 = fluid.unique_name.generate('fc')
with fluid.unique_name.guard('B'):
name_2 = fluid.unique_name.generate('fc')
print(name_1, name_2) # Afc_0, Bfc_0

import paddle
with paddle.utils.unique_name.guard():
name_1 = paddle.utils.unique_name.generate('fc')
with paddle.utils.unique_name.guard():
name_2 = paddle.utils.unique_name.generate('fc')
print(name_1, name_2) # fc_0, fc_0

with paddle.utils.unique_name.guard('A'):
name_1 = paddle.utils.unique_name.generate('fc')
with paddle.utils.unique_name.guard('B'):
name_2 = paddle.utils.unique_name.generate('fc')
print(name_1, name_2) # Afc_0, Bfc_0

30 changes: 14 additions & 16 deletions doc/paddle/api/paddle/fluid/unique_name/switch_cn.rst
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Expand Up @@ -3,7 +3,7 @@
switch
-------------------------------

.. py:function:: paddle.fluid.unique_name.switch(new_generator=None)
.. py:function:: paddle.utils.unique_name.switch(new_generator=None)



Expand All @@ -13,23 +13,21 @@ switch
参数:
- **new_generator** (UniqueNameGenerator, 可选) - 要切换到的新命名空间，一般无需设置。缺省值为None，表示切换到一个匿名的新命名空间。

返回：先前的命名空间，一般无需操作该返回值。

返回类型：UniqueNameGenerator。
返回：UniqueNameGenerator, 先前的命名空间，一般无需操作该返回值。

**代码示例**

.. code-block:: python
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返回类型同上

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done,thx!


import paddle.fluid as fluid
name1 = fluid.unique_name.generate('fc')
name2 = fluid.unique_name.generate('fc')
print(name1, name2) # fc_0, fc_1
pre_generator = fluid.unique_name.switch() # 切换到新命名空间
name2 = fluid.unique_name.generate('fc')
print(name2) # fc_0

fluid.unique_name.switch(pre_generator) # 切换回原命名空间
name3 = fluid.unique_name.generate('fc')
print(name3) # fc_2, 因为原命名空间已生成fc_0, fc_1
import paddle
name1 = paddle.utils.unique_name.generate('fc')
name2 = paddle.utils.unique_name.generate('fc')
print(name1, name2) # fc_0, fc_1

pre_generator, pre_dygraph_name_checker = paddle.utils.unique_name.switch() # switch to a new anonymous namespace.
name2 = paddle.utils.unique_name.generate('fc')
print(name2) # fc_0

paddle.utils.unique_name.switch(pre_generator, pre_dygraph_name_checker) # switch back to pre_generator.
name3 = paddle.utils.unique_name.generate('fc')
print(name3) # fc_2, since pre_generator has generated fc_0, fc_1.