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May 31, 2018
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Fluid guide img #10979

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2c589f7
add developer's fluid guide
weixing02 May 28, 2018
bcafb32
fix error
weixing02 May 28, 2018
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68 changes: 34 additions & 34 deletions doc/fluid/getstarted/Developer's_Guide_to_Paddle_Fluid.md
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Expand Up @@ -86,7 +86,7 @@
<br>

<p align="center">
<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/fluid_compiler.png" width=100%>
<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/fluid-compiler.png" width=100%>
</p>

---
Expand Down Expand Up @@ -123,12 +123,12 @@
<font size=5>

- 在科学计算领域，计算图是一种描述计算的经典方式。下图展示了从前向计算图（蓝色）开始，通过添加反向（红色）和优化算法相关（绿色）操作，构建出整个计算图的过程：
-
-
<p align="center">
<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/graph_construction_example_all.png" width=60%>
</p>


- Fluid ==使用`Program`而不是计算图==来描述模型和优化过程。`Program`由`Block`、`Operator`和`Variable`构成，相关概念会在后文详细展开。
- 编译时 Fluid 接受前向计算（这里可以先简单的理解为是一段有序的计算流）`Program`，为这段前向计算按照：前向 -> 反向 -> 梯度 clip -> 正则 -> 优化 的顺序，添加相关 `Operator`和`Variable`到`Program`到完整的计算。

Expand Down Expand Up @@ -328,7 +328,7 @@

</font>

---
---

### 编译时概念 ：==**[Transpiler](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/fluid/design/motivation/fluid_compiler.md)**==
<font size=5>
Expand Down Expand Up @@ -402,7 +402,7 @@
- `Scope`

- 计算相关
- `Block`
- `Block`
- `Kernel`、`OpWithKernel`、`OpWithoutKernel`

<table>
Expand Down Expand Up @@ -439,7 +439,7 @@
</tbody>
</table>

- 执行相关 ：`Executor`
- 执行相关 ：`Executor`

</font>

Expand Down Expand Up @@ -798,7 +798,7 @@ class GPUAllocator : public SystemAllocator {

- step 1：添加Place类型，<span style="background-color:#DAB1D5;">由用户实现添加到框架</span>
- 可以将Place类型理解为一个整数加上一个枚举型，包括：设备号 + 设备类型

<p align="center">
<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/place.png" width=40%>
</p>
Expand All @@ -824,7 +824,7 @@ class GPUAllocator : public SystemAllocator {
1. DataType 执行数据类型 FP32/FP64/INT32/INT64
1. Memory layout： 运行时 Tensor 在内存中的排布格式 NCHW、 NHWC
1. 使用的库

来区分Kernel，为同一个operator注册多个 Kernel。

```cpp
Expand Down Expand Up @@ -876,7 +876,7 @@ step 3: 运行时的 KernelType 推断和Kernel切换，<span style="background-
namespace framework {
using LoDTensorArray = std::vector<LoDTensor>;
}
}
}
```
- 每一次循环，从原始输入中“切出”一个片段
- LoDTensorArray 在Python端暴露，是Fluid支持的基础数据结构之一，用户可以直接创建并使用
Expand Down Expand Up @@ -910,7 +910,7 @@ void Run(const framework::Scope &scope,
false /*create_local_scope*/);
}
}

```

</font>
Expand Down Expand Up @@ -951,7 +951,7 @@ void Run(const framework::Scope &scope,

---

#### dynamicRNN 中的 Memory
#### dynamicRNN 中的 Memory

<font size=5>

Expand All @@ -961,7 +961,7 @@ void Run(const framework::Scope &scope,
- `memory` 在 operator A 前向计算之后，进行前向计算
- 当 `memory` 的前向计算会 "指向" A 的输出 LoDTensor
- `memory` 的输出可以是另一个 operator 的输入，于是形成了“循环”连接

</font>

---
Expand Down Expand Up @@ -1107,7 +1107,7 @@ void Run(const framework::Scope &scope,
<td>
<p align="center">
<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/fluid/images/fluid_module_1.png" width=60%>
</p>
</p>
</td>
<td>
<p align="center">
Expand All @@ -1127,13 +1127,13 @@ void Run(const framework::Scope &scope,
<font size=5>

- 设计概览
- 重构概览 [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/refactorization.md)
- fluid [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/fluid.md)
- 重构概览 [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/refactorization.md)
- fluid [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/fluid.md)
- fluid_compiler [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/fluid/design/motivation/fluid_compiler.md)
- 核心概念
- variable 描述 [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/var_desc.md)
- Tensor [->](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/tensor.md)
- LoDTensor [->](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/lod_tensor.md)
- LoDTensor [->](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/framework/lod_tensor.md)
- TensorArray [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/tensor_array.md)
- Program [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/program.md)
- Block [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/block.md)
Expand All @@ -1152,7 +1152,7 @@ void Run(const framework::Scope &scope,
- 支持新设硬件设备库 [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/support_new_device.md)
- 添加新的Operator [->](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/howto/dev/new_op_cn.md)
- 添加新的Kernel [->](
https://github.com/PaddlePaddle/Paddle/blob/develop/doc/howto/dev/new_op_kernel_en.md)
https://github.com/PaddlePaddle/Paddle/blob/develop/doc/howto/dev/new_op_kernel_en.md)

</font>

Expand All @@ -1167,10 +1167,10 @@ https://github.com/PaddlePaddle/Paddle/blob/develop/doc/howto/dev/new_op_kernel_
<font size=5>

Docker编译PaddlePaddle源码: [->](http://www.paddlepaddle.org/docs/develop/documentation/fluid/zh/build_and_install/docker_install_cn.html)

PaddlePaddle 在 Dockerhub 地址：[->](
https://hub.docker.com/r/paddlepaddle/paddle/tags/)

1. 获取PaddlePaddle的Docker镜像
```bash
docker pull paddlepaddle/paddle:latest-dev
Expand All @@ -1183,7 +1183,7 @@ PaddlePaddle 在 Dockerhub 地址：[->](
```

1. 进入docker container后，从源码编译，请参考文档 [->]( http://www.paddlepaddle.org/docs/develop/documentation/fluid/zh/build_and_install/build_from_source_cn.html)

</font>

---
Expand All @@ -1196,7 +1196,7 @@ PaddlePaddle 在 Dockerhub 地址：[->](
1. 开发推荐使用tag为`latest-dev`的镜像，其中打包了所有编译依赖。`latest`及`lastest-gpu`是production镜像，主要用于运行PaddlePaddle程序。
2. 在Docker中运行GPU程序，推荐使用nvidia-docker，[否则需要将CUDA库和设备挂载到Docker容器内](http://www.paddlepaddle.org/docs/develop/documentation/fluid/zh/build_and_install/docker_install_cn.html)。
<font size=4>

```bash
nvidia-docker run -it -v $PWD/Paddle:/paddle paddlepaddle/paddle:latest-dev /bin/bash
```
Expand Down Expand Up @@ -1353,9 +1353,9 @@ Op注册实现在`.cc`文件；Kernel注册CPU实现在`.cc`文件中，CUDA实
}
};
```

</font>

---

###### 实现带Kernel的Operator <span style="background-color:#c4e1e1;">step2</span>: 定义Operator类
Expand Down Expand Up @@ -1420,11 +1420,11 @@ class ClipOp : public framework::OperatorWithKernel {
2. override InferShape函数（参考 [clip_op](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/clip_op.cc#L24)）

1. 什么是`functor` ?

- 类或结构体仅重载了`()`，一般是可被多个kernel复用的计算函数。

<font size=4>

```cpp
template <typename T>
class CrossEntropyFunctor<platform::CPUDeviceContext, T> {
Expand All @@ -1438,9 +1438,9 @@ class ClipOp : public framework::OperatorWithKernel {
};
```
</font>

- 在 clip_op 内也会看到将一段计算函数抽象为functor的使用法： [->](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/clip_op.h#L27)。

</font>

---
Expand Down Expand Up @@ -1504,7 +1504,7 @@ class ClipKernel : public framework::OpKernel<T> {
- 需要注意，<span style="background-color:#e1c4c4;">Fluid中，不区分Cost Op和中间层Op，所有Op都必须正确处理接收到的梯度</span>
2. 反向Op的输出
- 对可学习参数的求导结果
- 对所有输入的求导结果
- 对所有输入的求导结果


</font>
Expand All @@ -1520,7 +1520,7 @@ class ClipKernel : public framework::OpKernel<T> {
1. 在`.cc`文件中注册前向、反向Op类，注册CPU Kernel。

<font size=4>

```cpp
namespace ops = paddle::operators;
REGISTER_OP(clip, ops::ClipOp, ops::ClipOpMaker<float>, clip_grad,
Expand All @@ -1530,13 +1530,13 @@ class ClipKernel : public framework::OpKernel<T> {
REGISTER_OP_CPU_KERNEL(
clip_grad, ops::ClipGradKernel<paddle::platform::CPUDeviceContext, float>);
```

- 在上面的代码片段中：

1. `REGISTER_OP` ： 注册`ops::ClipOp`类，类型名为`clip`，该类的`ProtoMaker`为`ops::ClipOpMaker`，注册`ops::ClipOpGrad`，类型名为`clip_grad`
1. `REGISTER_OP_WITHOUT_GRADIENT` ： 用于注册没有反向的Op，例如：优化算法相关的Op
1. `REGISTER_OP_CPU_KERNEL` ：注册`ops::ClipKernel`类，并特化模板参数为`paddle::platform::CPUPlace`和`float`类型，同理，注册`ops::ClipGradKernel`类

</font>
1. 按照同样方法，在`.cu`文件中注册GPU Kernel
- <span style="background-color:#e1c4c4;">如果CUDA Kernel的实现基于Eigen，需在 `.cu`的开始加上宏定义 `#define EIGEN_USE_GPU` </span>
Expand Down Expand Up @@ -1593,7 +1593,7 @@ class ClipKernel : public framework::OpKernel<T> {
```bash
make test ARGS="-R test_mul_op -V"
```

或者:

```
Expand All @@ -1613,7 +1613,7 @@ class ClipKernel : public framework::OpKernel<T> {
- 如果多个Op依赖一些共用的函数，可以创建非`*_op.*`格式的文件来存放，如`gather.h`文件。

</font>

---

### ==10.== 使用相关问题
Expand Down Expand Up @@ -1735,7 +1735,7 @@ class ClipKernel : public framework::OpKernel<T> {
y_data = np.random.randint(0, 8, [1]).astype("int32")
y_tensor = core.Tensor()
y_tensor.set(y_data, place)

x_data = np.random.uniform(0.1, 1, [11, 8]).astype("float32")
x_tensor = core.Tensor()
x_tensor.set(x_data, place)
Expand Down
1 change: 1 addition & 0 deletions doc/fluid/getstarted/index_cn.rst
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Expand Up @@ -17,3 +17,4 @@
:maxdepth: 1

concepts/use_concepts_cn.rst
developer's_guide_to_paddle_fluid.md
1 change: 1 addition & 0 deletions doc/fluid/getstarted/index_en.rst
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Expand Up @@ -16,3 +16,4 @@ Here is an example of linear regression. It introduces workflow of PaddlePaddle,
:maxdepth: 1

concepts/index_en.rst
developer's_guide_to_paddle_fluid.md
12 changes: 6 additions & 6 deletions doc/fluid/getstarted/quickstart_cn.rst
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Expand Up @@ -11,7 +11,7 @@ PaddlePaddle支持使用pip快速安装，目前支持CentOS 6以上, Ubuntu 14.

pip install paddlepaddle

如果需要安装支持GPU的版本（cuda7.5_cudnn5_avx_openblas），需要执行：
如果需要安装支持GPU的版本（cuda8.0_cudnn5_avx_openblas），需要执行：

.. code-block:: bash

Expand All @@ -28,18 +28,18 @@ PaddlePaddle支持使用pip快速安装，目前支持CentOS 6以上, Ubuntu 14.

import paddle.dataset.uci_housing as uci_housing
import paddle.fluid as fluid

with fluid.scope_guard(fluid.core.Scope()):
# initialize executor with cpu
exe = fluid.Executor(place=fluid.CPUPlace())
# load inference model
# load inference model
[inference_program, feed_target_names,fetch_targets] = \
fluid.io.load_inference_model(uci_housing.fluid_model(), exe)
# run inference
result = exe.run(inference_program,
feed={feed_target_names[0]: uci_housing.predict_reader()},
result = exe.run(inference_program,
feed={feed_target_names[0]: uci_housing.predict_reader()},
fetch_list=fetch_targets)
# print predicted price is $12,273.97
# print predicted price is $12,273.97
print 'Predicted price: ${:,.2f}'.format(result[0][0][0] * 1000)

执行 :code:`python housing.py` 瞧！ 它应该打印出预测住房数据的清单。
12 changes: 6 additions & 6 deletions doc/fluid/getstarted/quickstart_en.rst
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Expand Up @@ -12,7 +12,7 @@ Simply run the following command to install, the version is cpu_avx_openblas:

pip install paddlepaddle

If you need to install GPU version (cuda7.5_cudnn5_avx_openblas), run:
If you need to install GPU version (cuda8.0_cudnn5_avx_openblas), run:

.. code-block:: bash

Expand All @@ -31,18 +31,18 @@ code:

import paddle.dataset.uci_housing as uci_housing
import paddle.fluid as fluid

with fluid.scope_guard(fluid.core.Scope()):
# initialize executor with cpu
exe = fluid.Executor(place=fluid.CPUPlace())
# load inference model
# load inference model
[inference_program, feed_target_names,fetch_targets] = \
fluid.io.load_inference_model(uci_housing.fluid_model(), exe)
# run inference
result = exe.run(inference_program,
feed={feed_target_names[0]: uci_housing.predict_reader()},
result = exe.run(inference_program,
feed={feed_target_names[0]: uci_housing.predict_reader()},
fetch_list=fetch_targets)
# print predicted price is $12,273.97
# print predicted price is $12,273.97
print 'Predicted price: ${:,.2f}'.format(result[0][0][0] * 1000)

Run :code:`python housing.py` and voila! It should print out a list of predictions
Expand Down