提交 33c21291 编写于 作者: T tensor-tang

Merge remote-tracking branch 'ups/develop' into fea/ut/vis

......@@ -19,7 +19,7 @@ Our vision is to enable deep learning for everyone via PaddlePaddle.
Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddle/releases) to track the latest feature of PaddlePaddle.
### Latest PaddlePaddle Release: [Fluid 0.14.0](https://github.com/PaddlePaddle/Paddle/tree/v0.14.0)
### Latest PaddlePaddle Release: [Fluid 0.15.0](https://github.com/PaddlePaddle/Paddle/tree/v0.15.0)
### Install Latest Stable Release:
```
# Linux CPU
......@@ -76,26 +76,26 @@ pip install paddlepaddle-gpu==0.14.0.post85
## Installation
It is recommended to read [this doc](http://paddlepaddle.org/documentation/docs/zh/0.14.0/new_docs/beginners_guide/install/install_doc.html) on our website.
It is recommended to read [this doc](http://paddlepaddle.org/documentation/docs/zh/0.15.0/new_docs/beginners_guide/install/install_doc.html) on our website.
## Documentation
We provide [English](http://paddlepaddle.org/documentation/docs/en/0.14.0/getstarted/index_en.html) and
[Chinese](http://paddlepaddle.org/documentation/docs/zh/0.14.0/new_docs/beginners_guide/index.html) documentation.
We provide [English](http://paddlepaddle.org/documentation/docs/en/0.15.0/getstarted/index_en.html) and
[Chinese](http://paddlepaddle.org/documentation/docs/zh/0.15.0/new_docs/beginners_guide/index.html) documentation.
- [Deep Learning 101](https://github.com/PaddlePaddle/book)
You might want to start from this online interactive book that can run in a Jupyter Notebook.
- [Distributed Training](http://paddlepaddle.org/documentation/docs/zh/0.14.0/new_docs/user_guides/howto/training/cluster_howto.html)
- [Distributed Training](http://paddlepaddle.org/documentation/docs/zh/0.15.0/new_docs/user_guides/howto/training/cluster_howto.html)
You can run distributed training jobs on MPI clusters.
- [Python API](http://paddlepaddle.org/documentation/api/zh/0.14.0/fluid.html)
- [Python API](http://paddlepaddle.org/documentation/api/zh/0.15.0/fluid.html)
Our new API enables much shorter programs.
- [How to Contribute](http://paddlepaddle.org/documentation/docs/zh/0.14.0/new_docs/advanced_usage/development/contribute_to_paddle.html)
- [How to Contribute](http://paddlepaddle.org/documentation/docs/zh/0.15.0/new_docs/advanced_usage/development/contribute_to_paddle.html)
We appreciate your contributions!
......
......@@ -51,7 +51,7 @@ int BuildFusion(Graph* graph, const std::string& name_scope, Scope* scope,
if (with_fc_bias) {
// Add FC-bias with LSTM-bias and create a new weight
PADDLE_ENFORCE(scope);
const std::string& new_bias_var = name_scope + "_bias.new";
const std::string& new_bias_var = patterns::UniqueKey("NewBias");
auto* bias_var = scope->Var(new_bias_var);
PADDLE_ENFORCE(bias_var);
auto* bias_tensor = bias_var->GetMutable<framework::LoDTensor>();
......@@ -120,7 +120,6 @@ int BuildFusion(Graph* graph, const std::string& name_scope, Scope* scope,
auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
Graph* g) {
GET_IR_NODE_FROM_SUBGRAPH(lstm, lstm, lstm_pattern);
GET_IR_NODE_FROM_SUBGRAPH(Weight, Weight, lstm_pattern);
GET_IR_NODE_FROM_SUBGRAPH(Bias, Bias, lstm_pattern);
......@@ -136,7 +135,7 @@ int BuildFusion(Graph* graph, const std::string& name_scope, Scope* scope,
fc_bias);
// Remove unneeded nodes.
std::unordered_set<const Node*> marked_nodes(
{mul, lstm, elementwise_add});
{mul, lstm, elementwise_add, fc_bias});
GraphSafeRemoveNodes(graph, marked_nodes);
} else {
GET_IR_NODE_FROM_SUBGRAPH(fc_out, mul_out, fc_pattern);
......
......@@ -14,6 +14,7 @@
#include "paddle/fluid/inference/analysis/ir_pass_manager.h"
#include <string>
#include <vector>
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/scope.h"
......@@ -37,13 +38,16 @@ IRPassManager::IRPassManager(const ProgramDesc &program,
void IRPassManager::Apply(const std::vector<std::string> &passes) {
// Apply all the passes
std::string pre_pass;
int pass_num = 0;
for (const std::string &pass_name : passes) {
PrettyLogEndl(Style::H2(), "--- Running IR pass [%s]", pass_name);
auto pass = framework::ir::PassRegistry::Instance().Get(pass_name);
if (pass_name == "graph_viz_pass") {
std::string dot_file_path =
"ir_" + (pre_pass.empty() ? "origin" : pre_pass) + ".dot";
std::string dot_file_path = std::to_string(pass_num) + "_ir_" +
(pre_pass.empty() ? "origin" : pre_pass) +
".dot";
pass->Set("graph_viz_path", new std::string(std::move(dot_file_path)));
pass_num++;
}
graph_ = pass->Apply(std::move(graph_));
pre_pass = pass_name;
......
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