From ab4121f5f4ada5b90d7032f25afdb32629455ccd Mon Sep 17 00:00:00 2001 From: Travis CI Date: Thu, 21 Dec 2017 03:58:21 +0000 Subject: [PATCH] Deploy to GitHub Pages: f734d0cb70a5b447f099beda15ef7b4922799aa7 --- .../_sources/design/kernel_hint_design.md.txt | 57 +++ develop/doc/design/kernel_hint_design.html | 322 +++++++++++++++++ develop/doc/objects.inv | Bin 3827 -> 3847 bytes develop/doc/searchindex.js | 2 +- .../_sources/design/kernel_hint_design.md.txt | 57 +++ develop/doc_cn/design/kernel_hint_design.html | 336 ++++++++++++++++++ develop/doc_cn/objects.inv | Bin 4380 -> 4400 bytes develop/doc_cn/searchindex.js | 2 +- 8 files changed, 774 insertions(+), 2 deletions(-) create mode 100644 develop/doc/_sources/design/kernel_hint_design.md.txt create mode 100644 develop/doc/design/kernel_hint_design.html create mode 100644 develop/doc_cn/_sources/design/kernel_hint_design.md.txt create mode 100644 develop/doc_cn/design/kernel_hint_design.html diff --git a/develop/doc/_sources/design/kernel_hint_design.md.txt b/develop/doc/_sources/design/kernel_hint_design.md.txt new file mode 100644 index 00000000000..a54b7da045e --- /dev/null +++ b/develop/doc/_sources/design/kernel_hint_design.md.txt @@ -0,0 +1,57 @@ +## Problem +In PaddlePaddle's [Design](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/switch_kernel.md), one Operator may have multiple kernels. Users may have some personal preference to choose a certain type of kernel for an operator, such as `force_cpu` to choose a CPU kernel, `use_cudnn` to choose a CUDNN kernel, we need to provide a way for users to do this. + +In the current design, we use KernelType to describe one kernel. + +```cpp +struct KernelType { + Place place_; + DataType data_type_; + LayoutType layout_; +}; +``` + `place_` `data_type_` and `layout_` can be got from the input tensors of the operator, `GetActualKernelType(inputs)` use inputs to infer the proper kernel key that fit the incoming data, but users can not directly configure it. + +The [design](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/switch_kernel.md) also provides a virtual method `GetExpectedKernelType` that user can overload and use to choose the KernelType they want to use. + +So we should send the information user defined in proto to `GetExpectedKernelType` for choosing a kernel. + +The problem is, how should we define and send the information for `GetExpectedKernelType` to use? + +## Solution + +### Potential choice +1. Do nothing, let the user add the information they want to operator‘s attribute and get them inside `GetExpectedKernelType`, this can work properly. But there is a little problem that users may define many kinds of hints for the same purpose, such as `force_cpu`, `use_cpu`, `cpu_kernel` to choose CPU kernel, and `use_cudnn`, `force_cudnn`, `cudnn_kernel` to choose CUDNN kernel. + +2. Pre-define all the needed option and use a single attr key such as `kernel_hint` for the user, this is not so flexible if the user wants to define some more kind of hint. + +### Final choice +To provide enough flexibility while avoiding confusion definition, we can define some global constants for these attribute names, such as `force_cpu`, `use_cudnn`, `use_mkldnn` for a user to choose. + +In C++ + +```cpp +const std::string kForceCPU = "force_cpu"; +const std::string kUseCUDNN = "use_cudnn"; +const std::string kUseMKLDNN = "use_mkldnn"; + +KernelType GetExpectedKernelType() { + if (Attr(kForceCPU)) { + return KernelType(CPUPlace, ...) + } else { + ... + } +} +``` + +In Python code + +```python +FORCE_CPU = core.kForceCPU() + +def xx_layer(..., force_cpu=false): + layer_helper = LayerHelper(...) + layer_helper.append_op( + type="xx", + attr={FORCE_CPU: force_cpu}) +``` diff --git a/develop/doc/design/kernel_hint_design.html b/develop/doc/design/kernel_hint_design.html new file mode 100644 index 00000000000..a20fb008329 --- /dev/null +++ b/develop/doc/design/kernel_hint_design.html @@ -0,0 +1,322 @@ + + + + + + + + + + + Problem — PaddlePaddle documentation + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+ Fork me on Github +
+ + English + + + + +
+ +
+
+ + + + +
+
+ + + +
+
+
+
+
+ +
+ + + + +
+ + + + + + + + + + + +
+
    + +
  • Problem
    • +
+
+ +
+
+
+
+ +
+

Problem

+

In PaddlePaddle’s Design, one Operator may have multiple kernels. Users may have some personal preference to choose a certain type of kernel for an operator, such as force_cpu to choose a CPU kernel, use_cudnn to choose a CUDNN kernel, we need to provide a way for users to do this.

+

In the current design, we use KernelType to describe one kernel.

+
struct KernelType {
+  Place place_;
+  DataType data_type_;
+  LayoutType layout_;
+};
+
+
+

place_ data_type_ and layout_ can be got from the input tensors of the operator, GetActualKernelType(inputs) use inputs to infer the proper kernel key that fit the incoming data, but users can not directly configure it.

+

The design also provides a virtual method GetExpectedKernelType that user can overload and use to choose the KernelType they want to use.

+

So we should send the information user defined in proto to GetExpectedKernelType for choosing a kernel.

+

The problem is, how should we define and send the information for GetExpectedKernelType to use?

+
+
+

Solution

+
+

Potential choice

+
    +
  1. Do nothing, let the user add the information they want to operator‘s attribute and get them inside GetExpectedKernelType, this can work properly. But there is a little problem that users may define many kinds of hints for the same purpose, such as force_cpu, use_cpu, cpu_kernel to choose CPU kernel, and use_cudnn, force_cudnn, cudnn_kernel to choose CUDNN kernel.
    2. +
  2. Pre-define all the needed option and use a single attr key such as kernel_hint for the user, this is not so flexible if the user wants to define some more kind of hint.
    3. +
+
+
+

Final choice

+

To provide enough flexibility while avoiding confusion definition, we can define some global constants for these attribute names, such as force_cpu, use_cudnn, use_mkldnn for a user to choose.

+

In C++

+
const std::string kForceCPU = "force_cpu";
+const std::string kUseCUDNN = "use_cudnn";
+const std::string kUseMKLDNN = "use_mkldnn";
+
+KernelType GetExpectedKernelType() {
+  if (Attr<bool>(kForceCPU)) {
+    return KernelType(CPUPlace, ...)
+  } else {
+    ...
+  }
+}
+
+
+

In Python code

+
FORCE_CPU = core.kForceCPU()
+
+def xx_layer(..., force_cpu=false):
+  layer_helper = LayerHelper(...)
+  layer_helper.append_op(
+    type="xx",
+    attr={FORCE_CPU: force_cpu})
+
+
+
+
+ + +
+
+
+ + +
+ +
+

+ © Copyright 2016, PaddlePaddle developers. + +

+
+ Built with Sphinx using a theme provided by Read the Docs. + +
+ +
+
+ +
+ +
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Android","PaddlePaddle Compiling Guide for iOS","Build PaddlePaddle for Raspberry Pi","MOBILE","Cluster bootstrapping tool survey","<no title>","Chinese Word Embedding Model Tutorial","Generative Adversarial Networks (GAN)","Model Zoo - ImageNet","Quick 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\ No newline at end of file diff --git a/develop/doc_cn/_sources/design/kernel_hint_design.md.txt b/develop/doc_cn/_sources/design/kernel_hint_design.md.txt new file mode 100644 index 00000000000..a54b7da045e --- /dev/null +++ b/develop/doc_cn/_sources/design/kernel_hint_design.md.txt @@ -0,0 +1,57 @@ +## Problem +In PaddlePaddle's [Design](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/switch_kernel.md), one Operator may have multiple kernels. Users may have some personal preference to choose a certain type of kernel for an operator, such as `force_cpu` to choose a CPU kernel, `use_cudnn` to choose a CUDNN kernel, we need to provide a way for users to do this. + +In the current design, we use KernelType to describe one kernel. + +```cpp +struct KernelType { + Place place_; + DataType data_type_; + LayoutType layout_; +}; +``` + `place_` `data_type_` and `layout_` can be got from the input tensors of the operator, `GetActualKernelType(inputs)` use inputs to infer the proper kernel key that fit the incoming data, but users can not directly configure it. + +The [design](https://github.com/PaddlePaddle/Paddle/blob/develop/doc/design/switch_kernel.md) also provides a virtual method `GetExpectedKernelType` that user can overload and use to choose the KernelType they want to use. + +So we should send the information user defined in proto to `GetExpectedKernelType` for choosing a kernel. + +The problem is, how should we define and send the information for `GetExpectedKernelType` to use? + +## Solution + +### Potential choice +1. Do nothing, let the user add the information they want to operator‘s attribute and get them inside `GetExpectedKernelType`, this can work properly. But there is a little problem that users may define many kinds of hints for the same purpose, such as `force_cpu`, `use_cpu`, `cpu_kernel` to choose CPU kernel, and `use_cudnn`, `force_cudnn`, `cudnn_kernel` to choose CUDNN kernel. + +2. Pre-define all the needed option and use a single attr key such as `kernel_hint` for the user, this is not so flexible if the user wants to define some more kind of hint. + +### Final choice +To provide enough flexibility while avoiding confusion definition, we can define some global constants for these attribute names, such as `force_cpu`, `use_cudnn`, `use_mkldnn` for a user to choose. + +In C++ + +```cpp +const std::string kForceCPU = "force_cpu"; +const std::string kUseCUDNN = "use_cudnn"; +const std::string kUseMKLDNN = "use_mkldnn"; + +KernelType GetExpectedKernelType() { + if (Attr(kForceCPU)) { + return KernelType(CPUPlace, ...) + } else { + ... + } +} +``` + +In Python code + +```python +FORCE_CPU = core.kForceCPU() + +def xx_layer(..., force_cpu=false): + layer_helper = LayerHelper(...) + layer_helper.append_op( + type="xx", + attr={FORCE_CPU: force_cpu}) +``` diff --git a/develop/doc_cn/design/kernel_hint_design.html b/develop/doc_cn/design/kernel_hint_design.html new file mode 100644 index 00000000000..054646a01f2 --- /dev/null +++ b/develop/doc_cn/design/kernel_hint_design.html @@ -0,0 +1,336 @@ + + + + + + + + + + + Problem — PaddlePaddle 文档 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ +
+
+ Fork me on Github +
+ + English + + + + +
+ +
+
+ + + + +
+
+ + + +
+
+
+
+
+ +
+ + + + +
+ + + + + + + + + + + +
+
    + +
  • Problem
    • +
+
+ +
+
+
+
+ +
+

Problem

+

In PaddlePaddle’s Design, one Operator may have multiple kernels. Users may have some personal preference to choose a certain type of kernel for an operator, such as force_cpu to choose a CPU kernel, use_cudnn to choose a CUDNN kernel, we need to provide a way for users to do this.

+

In the current design, we use KernelType to describe one kernel.

+
struct KernelType {
+  Place place_;
+  DataType data_type_;
+  LayoutType layout_;
+};
+
+
+

place_ data_type_ and layout_ can be got from the input tensors of the operator, GetActualKernelType(inputs) use inputs to infer the proper kernel key that fit the incoming data, but users can not directly configure it.

+

The design also provides a virtual method GetExpectedKernelType that user can overload and use to choose the KernelType they want to use.

+

So we should send the information user defined in proto to GetExpectedKernelType for choosing a kernel.

+

The problem is, how should we define and send the information for GetExpectedKernelType to use?

+
+
+

Solution

+
+

Potential choice

+
    +
  1. Do nothing, let the user add the information they want to operator‘s attribute and get them inside GetExpectedKernelType, this can work properly. But there is a little problem that users may define many kinds of hints for the same purpose, such as force_cpu, use_cpu, cpu_kernel to choose CPU kernel, and use_cudnn, force_cudnn, cudnn_kernel to choose CUDNN kernel.
    2. +
  2. Pre-define all the needed option and use a single attr key such as kernel_hint for the user, this is not so flexible if the user wants to define some more kind of hint.
    3. +
+
+
+

Final choice

+

To provide enough flexibility while avoiding confusion definition, we can define some global constants for these attribute names, such as force_cpu, use_cudnn, use_mkldnn for a user to choose.

+

In C++

+
const std::string kForceCPU = "force_cpu";
+const std::string kUseCUDNN = "use_cudnn";
+const std::string kUseMKLDNN = "use_mkldnn";
+
+KernelType GetExpectedKernelType() {
+  if (Attr<bool>(kForceCPU)) {
+    return KernelType(CPUPlace, ...)
+  } else {
+    ...
+  }
+}
+
+
+

In Python code

+
FORCE_CPU = core.kForceCPU()
+
+def xx_layer(..., force_cpu=false):
+  layer_helper = LayerHelper(...)
+  layer_helper.append_op(
+    type="xx",
+    attr={FORCE_CPU: force_cpu})
+
+
+
+
+ + +
+
+
+ + +
+ +
+

+ © Copyright 2016, PaddlePaddle developers. + +

+
+ Built with Sphinx using a theme provided by Read the Docs. + +
+ +
+
+ +
+ +
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