提交 3b879598 编写于 作者: Y Yang Yang

update executor design doc

上级 d6a60694
......@@ -15,7 +15,7 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope) {
}
// Decide which operator should be run
std::vector<bool> should_run = Preprocess(pdesc);
std::vector<bool> should_run = Prune(pdesc);
// Run the block
Scope& local_scope = scope->NewScope();
......@@ -23,7 +23,7 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope) {
if (should_run[i]) {
for (auto var : block.ops(i).outputs()) {
for (auto argu : var.arguments()) {
// Create variable in the local_scope
// Create temp variable in the local_scope
if (local_scope.FindVar(argu) == nullptr) {
local_scope.NewVar(argu);
}
......@@ -36,60 +36,33 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope) {
}
```
## Tasks
## Challenge
As shown above, it is not hard to simply evaluate the graph. The real problem
is how do we actually construct the `ProgramDesc`. There are several different
situations that we need to consider.
It is not hard to simply evaluate a graph. However, it is hard to determine which op should be run. Consider the following different situations.
### 1. Init @tony @qijun
##### Problem:
Not sure which block to put init ops. Same concerns applys to `Load Model`.
##### Solution: In seperate Blocks
All `initop` and `parameter` goes to `block[0]`. Actual run starts from `block[1]`.
When user writes `a = Parameter(Variable, init)`, a init op is inserted into
`block[0]`, and a `NOP` is inserted into `block[1]` to substitute init op.
- Pro:
- Init Op can be run multiple times.
- Compatiable with current `Executor::Preprocessing`
- Still only one `ProgramDesc`
- Con:
- Let others know!
### 2. IO
#### 2.1 FeedOp and FetchOp
Design Doc: https://github.com/PaddlePaddle/Paddle/pull/4599
FeedOp and FetchOp in distributed environment:
https://github.com/PaddlePaddle/Paddle/issues/4613
#### 2.2 ReaderOp and WriterOp
### 3. Backward @jiayi
Executor test case is a good place to test `backward` module, even though executor
is not necessarily depends on `backward`. Currently exposed issue:
- Fill One: https://github.com/PaddlePaddle/Paddle/issues/4627
- Attribute map: https://github.com/PaddlePaddle/Paddle/issues/4642
### 4. Optimizer @longfei
```python
# Case 1: run foward pass.
cost_np = executor.run(target=cost)
# Case 2: run backward passing.
opts_np, _ = executor.run(target=[cost, opt])
# Case 3: run checkpointing
_ = executor.run(target=checkpoint)
```
Executor test case is a good place to test `optimizer `module, even though executor
is not necessarily depends on `optimizer `.
We want to support the evaluation of both variables and operators.
### 5. RNN @chunwei
## Solution
To be discussed.
To support evaluation of operators, we add `is_target` field in the `OpDesc`.
- How to deal with multiple blocks
- How to deal with LoDTensor
```c++
message OpDesc {
required string type = 3;
repeated Var inputs = 1;
repeated Var outputs = 2;
repeated Attr attrs = 4;
required bool is_target = 5 [ default = false ]; // true if the op is target
};
```
To support evaluation of variables, we add [fetch_op](https://github.com/PaddlePaddle/Paddle/pull/4599). For each variable in the `target`, we insert a `fetch_op` into the `ProgramDesc`. (Also, a user may want to overwrite a variable, so we also added [feed_op](https://github.com/PaddlePaddle/Paddle/pull/4599). )
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