提交 8a4bd171 编写于 作者: F fengjiayi

add brief explanation of DDim usage

上级 f7396293
......@@ -48,7 +48,9 @@ int main()
}
```
In Majel, `DDimVar` is derived from `Dim`, `DArrayVar` is from `Array`.
In Majel, `DDimVar` is derived from `Dim`, `DArrayVar` is from
`Array`.
```c++
template<int i>
......@@ -68,8 +70,8 @@ private:
Dim<D> stride_;
T* ptr_;
};
```
```
```c++
typedef boost::variant<GpuPlace, CpuPlace> Place;
typedef boost::variant<Dim<1>, Dim<2>, Dim<3>, Dim<4>, Dim<5>,
......@@ -93,6 +95,20 @@ typedef boost::variant<
Because `variant` may be thought of as "multi-type, single value", we can utilize it to implement unified interfaces for PaddlePaddle.
`DDim` plays two kinds of roles in Majel. First, it is used to indicate the size of a tensor. For example, we can construct a new `DArray` by following way:
```c++
DArray arr = make_darray(make_ddim({2,3}), 0.0f);
```
It means that `arr` will be a two-dimension tensor, or a matrix. The size of its first dimension is 2 and the second is 3. All the element value of `arr` will be initialized as 0.0 .
The second meaning of `DDim` is tensor index. For example, if we want to access the value in the 1st row and 2nd column of `arr` and set it to 1.0, we can do like this:
```c++
arr[make_ddim({0, 1})] = 1.0
```
## implement Tensor in Paddle
Before writing code, please make sure you already look through Majel Source Code and grabbed the design philosophy of `DArray` in Majel.
......@@ -113,8 +129,8 @@ To assign subtasks to our colleagues, we have to discuss how to divide it to ind
- [ ] 3. Re-implement `Dim`.
`Dim` is an excellent implementation in Majel.
`Dim` is an excellent implementation in Majel.
> ???
- [ ] 4. Re-implement `Array/Tensor`.
......
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