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Polish tracer code

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test=develop
revert-15207-remove_op_handle_lock_and_fix_var
minqiyang 6 years ago
parent cded24768c
commit 08e2a5d611
3 changed files with 148 additions and 133 deletions
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143
paddle/fluid/imperative/tracer.cc
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@ -15,5 +15,146 @@
#include "paddle/fluid/imperative/tracer.h"
namespace paddle {
namespace imperative {} // namespace imperative
namespace imperative {
void CreateGradOp(const framework::OpDesc& op_desc,
const std::unordered_set<std::string>& no_grad_set,
const std::vector<framework::BlockDesc*>& grad_sub_block,
framework::OpDesc** grad_op_desc,
std::unordered_map<std::string, std::string>* grad_to_var) {
std::vector<std::unique_ptr<framework::OpDesc>> grad_op_descs =
framework::OpInfoMap::Instance()
.Get(op_desc.Type())
.GradOpMaker()(op_desc, no_grad_set, grad_to_var, grad_sub_block);
PADDLE_ENFORCE(grad_op_descs.size() == 1, "Only support 1 grad op now.");
// TODO(panyx0718): Leak?
*grad_op_desc = grad_op_descs[0].release();
}
void InitVar(framework::Variable* var, framework::Variable* grad_var) {
auto& var_t = var->Get<framework::LoDTensor>();
float* data =
grad_var->GetMutable<framework::LoDTensor>()->mutable_data<float>(
var_t.dims(), platform::CPUPlace());
std::fill(data, data + var_t.numel(), 0.0);
}
void Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
const VarBasePtrMap& outputs, framework::BlockDesc* block,
const bool stop_gradient) {
std::map<std::string, VarBase*> vars;
framework::OpDesc* op_desc = op->op_desc_;
VLOG(3) << "tracer tracing " << op_desc->Type();
op_desc->InferShape(*block);
op_desc->InferVarType(block);
std::unique_ptr<framework::OperatorBase> op_base =
framework::OpRegistry::CreateOp(*op_desc);
framework::VariableValueMap invars_map;
framework::VariableValueMap outvars_map;
op->input_vars_ = inputs;
for (auto it : op->input_vars_) {
auto& invars = invars_map[it.first];
for (VarBase* inp : it.second) {
PADDLE_ENFORCE_NOT_NULL(inp->var_.get(), "op %s input %s nullptr",
op->op_desc_->Type(), inp->var_desc_->Name());
invars.push_back(inp->var_.get());
vars[inp->var_desc_->Name()] = inp;
if (inp->pre_op_) {
op->pre_ops_[it.first].push_back(inp->pre_op_);
op->pre_ops_out_idx_[it.first].push_back(inp->pre_op_out_idx_);
} else {
op->pre_ops_[it.first].push_back(nullptr);
}
VLOG(3) << "input vname " << inp->var_desc_->Name() << " "
<< inp->var_->IsInitialized();
}
}
op->output_vars_ = outputs;
for (auto it : op->output_vars_) {
auto& outvars = outvars_map[it.first];
const std::vector<VarBase*>& outputs = it.second;
for (size_t i = 0; i < outputs.size(); ++i) {
VarBase* out = outputs[i];
outvars.push_back(out->var_.get());
vars[out->var_desc_->Name()] = out;
framework::VarDesc* var_desc = block->FindVar(out->var_desc_->Name());
if (var_desc->GetType() == framework::proto::VarType::LOD_TENSOR) {
out->var_->GetMutable<framework::LoDTensor>();
} else {
LOG(ERROR) << "tracer doesn't support yet";
}
out->stop_gradient_ = stop_gradient;
out->pre_op_ = op;
out->pre_op_out_name_ = it.first;
out->pre_op_out_idx_ = i;
VLOG(3) << "output vname " << out->var_desc_->Name() << " "
<< out->var_->IsInitialized();
}
}
VLOG(3) << "tracer running " << op_desc->Type();
framework::RuntimeContext ctx(invars_map, outvars_map);
// TODO(panyx0718): Cache p.
framework::OperatorWithKernel* op_kernel =
dynamic_cast<framework::OperatorWithKernel*>(op_base.get());
PADDLE_ENFORCE_NOT_NULL(op_kernel, "only support op with kernel");
framework::Scope scope;
platform::CPUPlace place;
PreparedOp p = PreparedOp::Prepare(ctx, *op_kernel, place);
p.op.RuntimeInferShape(scope, place, ctx);
p.func(framework::ExecutionContext(p.op, scope, *p.dev_ctx, p.ctx));
if (!stop_gradient) {
framework::OpDesc* grad_op_desc;
auto grad_to_var = new std::unordered_map<std::string, std::string>();
CreateGradOp(*op_desc, {}, {block}, &grad_op_desc, grad_to_var);
op->grad_op_desc_ = grad_op_desc;
for (auto it : grad_op_desc->Inputs()) {
auto& grad_in_vars = op->grad_input_vars_[it.first];
for (const std::string& grad_invar : it.second) {
block->FindRecursiveOrCreateVar(grad_invar);
auto var_it = grad_to_var->find(grad_invar);
if (var_it == grad_to_var->end()) {
auto fwd_var_it = vars.find(grad_invar);
PADDLE_ENFORCE(fwd_var_it != vars.end());
grad_in_vars.push_back(fwd_var_it->second->var_.get());
} else {
VarBase* var = vars[var_it->second];
if (!var->grads_->var_->IsInitialized()) {
InitVar(var->var_.get(), var->grads_->var_.get());
}
grad_in_vars.push_back(var->grads_->var_.get());
}
}
}
for (auto it : grad_op_desc->Outputs()) {
auto& grad_out_vars = op->grad_output_vars_[it.first];
for (const std::string& grad_outvar : it.second) {
block->FindRecursiveOrCreateVar(grad_outvar);
auto var_it = grad_to_var->find(grad_outvar);
PADDLE_ENFORCE(var_it != grad_to_var->end());
VarBase* var = vars[var_it->second];
if (!var->grads_->var_->IsInitialized()) {
InitVar(var->var_.get(), var->grads_->var_.get());
}
grad_out_vars.push_back(var->grads_->var_.get());
}
}
}
op->block_ = block;
}
} // namespace imperative
} // namespace paddle

133
paddle/fluid/imperative/tracer.h
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@ -30,23 +30,9 @@ void CreateGradOp(const framework::OpDesc& op_desc,
const std::unordered_set<std::string>& no_grad_set,
const std::vector<framework::BlockDesc*>& grad_sub_block,
framework::OpDesc** grad_op_desc,
std::unordered_map<std::string, std::string>* grad_to_var) {
std::vector<std::unique_ptr<framework::OpDesc>> grad_op_descs =
framework::OpInfoMap::Instance()
.Get(op_desc.Type())
.GradOpMaker()(op_desc, no_grad_set, grad_to_var, grad_sub_block);
PADDLE_ENFORCE(grad_op_descs.size() == 1, "Only support 1 grad op now.");
// TODO(panyx0718): Leak?
*grad_op_desc = grad_op_descs[0].release();
}
std::unordered_map<std::string, std::string>* grad_to_var);
void InitVar(framework::Variable* var, framework::Variable* grad_var) {
auto& var_t = var->Get<framework::LoDTensor>();
float* data =
grad_var->GetMutable<framework::LoDTensor>()->mutable_data<float>(
var_t.dims(), platform::CPUPlace());
std::fill(data, data + var_t.numel(), 0.0);
}
void InitVar(framework::Variable* var, framework::Variable* grad_var);
class Tracer {
public:
@ -57,120 +43,7 @@ class Tracer {
void Trace(OpBase* op,
const std::map<std::string, std::vector<VarBase*>>& inputs,
const std::map<std::string, std::vector<VarBase*>>& outputs,
framework::BlockDesc* block, const bool stop_gradient = false) {
std::map<std::string, VarBase*> vars;
framework::OpDesc* op_desc = op->op_desc_;
VLOG(3) << "tracer tracing " << op_desc->Type();
op_desc->InferShape(*block);
op_desc->InferVarType(block);
std::unique_ptr<framework::OperatorBase> op_base =
framework::OpRegistry::CreateOp(*op_desc);
framework::VariableValueMap invars_map;
framework::VariableValueMap outvars_map;
op->input_vars_ = inputs;
for (auto it : op->input_vars_) {
auto& invars = invars_map[it.first];
for (VarBase* inp : it.second) {
PADDLE_ENFORCE_NOT_NULL(inp->var_.get(), "op %s input %s nullptr",
op->op_desc_->Type(), inp->var_desc_->Name());
invars.push_back(inp->var_.get());
vars[inp->var_desc_->Name()] = inp;
if (inp->pre_op_) {
op->pre_ops_[it.first].push_back(inp->pre_op_);
op->pre_ops_out_idx_[it.first].push_back(inp->pre_op_out_idx_);
} else {
op->pre_ops_[it.first].push_back(nullptr);
}
VLOG(3) << "input vname " << inp->var_desc_->Name() << " "
<< inp->var_->IsInitialized();
}
}
op->output_vars_ = outputs;
for (auto it : op->output_vars_) {
auto& outvars = outvars_map[it.first];
const std::vector<VarBase*>& outputs = it.second;
for (size_t i = 0; i < outputs.size(); ++i) {
VarBase* out = outputs[i];
outvars.push_back(out->var_.get());
vars[out->var_desc_->Name()] = out;
framework::VarDesc* var_desc = block->FindVar(out->var_desc_->Name());
if (var_desc->GetType() == framework::proto::VarType::LOD_TENSOR) {
out->var_->GetMutable<framework::LoDTensor>();
} else {
LOG(ERROR) << "tracer doesn't support yet";
}
out->stop_gradient_ = stop_gradient;
out->pre_op_ = op;
out->pre_op_out_name_ = it.first;
out->pre_op_out_idx_ = i;
VLOG(3) << "output vname " << out->var_desc_->Name() << " "
<< out->var_->IsInitialized();
}
}
VLOG(3) << "tracer running " << op_desc->Type();
framework::RuntimeContext ctx(invars_map, outvars_map);
// TODO(panyx0718): Cache p.
framework::OperatorWithKernel* op_kernel =
dynamic_cast<framework::OperatorWithKernel*>(op_base.get());
PADDLE_ENFORCE_NOT_NULL(op_kernel, "only support op with kernel");
framework::Scope scope;
platform::CPUPlace place;
PreparedOp p = PreparedOp::Prepare(ctx, *op_kernel, place);
p.op.RuntimeInferShape(scope, place, ctx);
p.func(framework::ExecutionContext(p.op, scope, *p.dev_ctx, p.ctx));
if (!stop_gradient) {
framework::OpDesc* grad_op_desc;
auto grad_to_var = new std::unordered_map<std::string, std::string>();
CreateGradOp(*op_desc, {}, {block}, &grad_op_desc, grad_to_var);
op->grad_op_desc_ = grad_op_desc;
for (auto it : grad_op_desc->Inputs()) {
auto& grad_in_vars = op->grad_input_vars_[it.first];
for (const std::string& grad_invar : it.second) {
block->FindRecursiveOrCreateVar(grad_invar);
auto var_it = grad_to_var->find(grad_invar);
if (var_it == grad_to_var->end()) {
auto fwd_var_it = vars.find(grad_invar);
PADDLE_ENFORCE(fwd_var_it != vars.end());
grad_in_vars.push_back(fwd_var_it->second->var_.get());
} else {
VarBase* var = vars[var_it->second];
if (!var->grads_->var_->IsInitialized()) {
InitVar(var->var_.get(), var->grads_->var_.get());
}
grad_in_vars.push_back(var->grads_->var_.get());
}
}
}
for (auto it : grad_op_desc->Outputs()) {
auto& grad_out_vars = op->grad_output_vars_[it.first];
for (const std::string& grad_outvar : it.second) {
block->FindRecursiveOrCreateVar(grad_outvar);
auto var_it = grad_to_var->find(grad_outvar);
PADDLE_ENFORCE(var_it != grad_to_var->end());
VarBase* var = vars[var_it->second];
if (!var->grads_->var_->IsInitialized()) {
InitVar(var->var_.get(), var->grads_->var_.get());
}
grad_out_vars.push_back(var->grads_->var_.get());
}
}
}
op->block_ = block;
}
framework::BlockDesc* block, const bool stop_gradient = false);
private:
framework::BlockDesc* root_block_;

5
paddle/fluid/pybind/CMakeLists.txt
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@ -1,5 +1,6 @@
set(PYBIND_DEPS pybind python proto_desc memory executor async_executor prune feed_fetch_method pass_builder parallel_executor profiler layer scope_pool)
set(PYBIND_DEPS pybind python proto_desc memory executor async_executor prune
feed_fetch_method pass_builder parallel_executor profiler layer scope_pool
tracer)
if(WITH_PYTHON)
list(APPEND PYBIND_DEPS py_func_op)
endif()

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