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PaddleDetection
未验证 提交 09189732 编写于 作者: Y Yu Yang 提交者： GitHub
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Rename XXDescBind --> XXDesc (#6797) 

* Rename XXDescBind --> XXDesc

* Fix Compile
上级 0295b000
隐藏空白更改
内联 并排
Showing with 447 addition and 472 deletion
paddle/framework/backward.cc
浏览文件 @ 09189732
......@@ -42,7 +42,7 @@ static std::unordered_set<std::string>& CtrlFlowOps() {
static inline std::unique_ptr<OperatorBase> CreateGradOp(
const OperatorBase& op, const std::unordered_set<std::string>& no_grad_set,
std::unordered_map<std::string, std::string>* grad_to_var) {
OpDescBind op_desc;
OpDesc op_desc;
op_desc.SetInputMap(op.Inputs());
op_desc.SetOutputMap(op.Outputs());
op_desc.SetType(op.Type());
......@@ -53,7 +53,7 @@ static inline std::unique_ptr<OperatorBase> CreateGradOp(
grad_ops.reserve(grad_descs.size());
std::transform(grad_descs.begin(), grad_descs.end(),
std::back_inserter(grad_ops),
[](const std::unique_ptr<OpDescBind>& grad_desc) {
[](const std::unique_ptr<OpDesc>& grad_desc) {
return OpRegistry::CreateOp(*grad_desc);
});
PADDLE_ENFORCE(!grad_ops.empty());
......@@ -296,7 +296,7 @@ static std::string FwdName(const std::string& grad_name) {
static void CreateGradVarInBlock(
size_t grad_op_start_index,
const std::unordered_map<std::string, std::string>& param_name_map,
BlockDescBind* block_desc,
BlockDesc* block_desc,
std::unordered_map<std::string, GradVarInfo>* grad_var_record) {
auto ops = block_desc->AllOps();
for (size_t op_index = grad_op_start_index; op_index < ops.size();
......@@ -350,12 +350,11 @@ static void CreateGradVarInBlock(
}
}
std::vector<std::unique_ptr<OpDescBind>> MakeOpGrad(
const OpDescBind* op_desc, std::unordered_set<std::string>* no_grad_vars,
std::vector<std::unique_ptr<OpDesc>> MakeOpGrad(
const OpDesc* op_desc, std::unordered_set<std::string>* no_grad_vars,
std::unordered_map<std::string, std::string>* grad_to_var,
const std::vector<BlockDescBind*>& grad_block =
std::vector<BlockDescBind*>()) {
std::vector<std::unique_ptr<OpDescBind>> grad_op_descs;
const std::vector<BlockDesc*>& grad_block = std::vector<BlockDesc*>()) {
std::vector<std::unique_ptr<OpDesc>> grad_op_descs;
// All input gradients of forwarding operator do not need to calculate.
const std::vector<std::string>& inputs = op_desc->InputArgumentNames();
if (AllGradInSet(inputs, *no_grad_vars)) {
......@@ -386,7 +385,7 @@ std::vector<std::unique_ptr<OpDescBind>> MakeOpGrad(
.Get(op_desc->Type())
.GradOpMaker()(*op_desc, *no_grad_vars, grad_to_var, grad_block);
std::list<std::unique_ptr<OpDescBind>> pending_fill_zeros_ops;
std::list<std::unique_ptr<OpDesc>> pending_fill_zeros_ops;
for (auto& desc : grad_op_descs) {
for (const std::string& in_name : desc->InputArgumentNames()) {
if (no_grad_vars->count(in_name)) {
......@@ -394,9 +393,9 @@ std::vector<std::unique_ptr<OpDescBind>> MakeOpGrad(
0, in_name.size() - sizeof(kGradVarSuffix) / sizeof(char) + 1);
std::string new_name = prefix + kZeroVarSuffix;
desc->Rename(in_name, new_name);
std::unique_ptr<OpDescBind> fill_zeros_op(
new OpDescBind("fill_zeros_like", {{"X", {prefix}}},
{{"Y", {new_name}}}, AttributeMap{}));
std::unique_ptr<OpDesc> fill_zeros_op(
new OpDesc("fill_zeros_like", {{"X", {prefix}}},
{{"Y", {new_name}}}, AttributeMap{}));
pending_fill_zeros_ops.push_back(std::move(fill_zeros_op));
}
}
......@@ -408,34 +407,33 @@ std::vector<std::unique_ptr<OpDescBind>> MakeOpGrad(
return grad_op_descs;
}
static BlockDescBind* CreateStepBlock(
ProgramDescBind& program_desc,
std::unordered_set<std::string>* no_grad_vars,
static BlockDesc* CreateStepBlock(
ProgramDesc& program_desc, std::unordered_set<std::string>* no_grad_vars,
std::unordered_map<std::string, std::string>* grad_to_var,
int step_block_idx);
std::vector<std::unique_ptr<OpDescBind>> MakeBlockBackward(
ProgramDescBind& program_desc, int block_idx,
std::vector<std::unique_ptr<OpDesc>> MakeBlockBackward(
ProgramDesc& program_desc, int block_idx,
std::unordered_set<std::string>* no_grad_vars,
std::unordered_map<std::string, std::string>* grad_to_var) {
VLOG(5) << "MakeBlockBackward";
BlockDescBind* cur_block = program_desc.MutableBlock(block_idx);
std::vector<OpDescBind*> op_descs = cur_block->AllOps();
BlockDesc* cur_block = program_desc.MutableBlock(block_idx);
std::vector<OpDesc*> op_descs = cur_block->AllOps();
std::unordered_map<std::string, std::vector<size_t>> dup_out_ops;
size_t grad_desc_idx = 0;
std::vector<std::unique_ptr<OpDescBind>> backward_descs;
std::vector<std::unique_ptr<OpDesc>> backward_descs;
for (auto it = op_descs.rbegin(); it != op_descs.rend(); ++it) {
VLOG(5) << "Making backward " << (*it)->Type() << " op";
std::vector<std::unique_ptr<OpDescBind>> op_grads;
std::vector<std::unique_ptr<OpDesc>> op_grads;
if ((*it)->Type() == "recurrent" || (*it)->Type() == "while") {
int step_block_idx = (*it)->GetBlockAttr("sub_block");
BlockDescBind* backward_block = CreateStepBlock(
program_desc, no_grad_vars, grad_to_var, step_block_idx);
BlockDesc* backward_block = CreateStepBlock(program_desc, no_grad_vars,
grad_to_var, step_block_idx);
op_grads = MakeOpGrad(*it, no_grad_vars, grad_to_var, {backward_block});
} else if ((*it)->Type() == "conditional_block") {
BlockDescBind* backward_block =
BlockDesc* backward_block =
CreateStepBlock(program_desc, no_grad_vars, grad_to_var,
(*it)->GetBlockAttr("sub_block"));
op_grads = MakeOpGrad(*it, no_grad_vars, grad_to_var, {backward_block});
......@@ -463,14 +461,14 @@ std::vector<std::unique_ptr<OpDescBind>> MakeBlockBackward(
}
++grad_desc_idx;
}
std::transform(
op_grads.begin(), op_grads.end(), std::back_inserter(backward_descs),
[](std::unique_ptr<OpDescBind>& ptr) { return std::move(ptr); });
std::transform(op_grads.begin(), op_grads.end(),
std::back_inserter(backward_descs),
[](std::unique_ptr<OpDesc>& ptr) { return std::move(ptr); });
}
VLOG(5) << "Appending Sums";
// Check whether some variables are written more than once
std::list<std::pair<size_t, std::unique_ptr<OpDescBind>>> pending_sum_ops;
std::list<std::pair<size_t, std::unique_ptr<OpDesc>>> pending_sum_ops;
for (const auto& dup : dup_out_ops) {
const std::string& out_name = dup.first;
const std::vector<size_t> dup_op = dup.second;
......@@ -486,18 +484,17 @@ std::vector<std::unique_ptr<OpDescBind>> MakeBlockBackward(
sum_op_inputs.emplace_back(new_name);
next_g_name = sum_op_inputs.back();
}
std::unique_ptr<OpDescBind> sum_op(
new OpDescBind("sum", {{"X", sum_op_inputs}}, {{"Out", {out_name}}},
AttributeMap{}));
std::unique_ptr<OpDesc> sum_op(new OpDesc("sum", {{"X", sum_op_inputs}},
{{"Out", {out_name}}},
AttributeMap{}));
pending_sum_ops.push_back({dup_op.back(), std::move(sum_op)});
}
}
pending_sum_ops.sort(
[](const std::pair<size_t, std::unique_ptr<OpDescBind>>& a,
const std::pair<size_t, std::unique_ptr<OpDescBind>>& b) {
return a.first > b.first;
});
pending_sum_ops.sort([](const std::pair<size_t, std::unique_ptr<OpDesc>>& a,
const std::pair<size_t, std::unique_ptr<OpDesc>>& b) {
return a.first > b.first;
});
for (auto& p : pending_sum_ops) {
backward_descs.insert(backward_descs.begin() + p.first + 1,
std::move(p.second));
......@@ -508,14 +505,13 @@ std::vector<std::unique_ptr<OpDescBind>> MakeBlockBackward(
return backward_descs;
}
static BlockDescBind* CreateStepBlock(
ProgramDescBind& program_desc,
std::unordered_set<std::string>* no_grad_vars,
static BlockDesc* CreateStepBlock(
ProgramDesc& program_desc, std::unordered_set<std::string>* no_grad_vars,
std::unordered_map<std::string, std::string>* grad_to_var,
int step_block_idx) {
auto backward_block_op_descs = MakeBlockBackward(program_desc, step_block_idx,
no_grad_vars, grad_to_var);
BlockDescBind* backward_block =
BlockDesc* backward_block =
program_desc.AppendBlock(*program_desc.MutableBlock(step_block_idx));
for (auto& ptr : backward_block_op_descs) {
backward_block->AppendAllocatedOp(move(ptr));
......@@ -524,7 +520,7 @@ static BlockDescBind* CreateStepBlock(
}
ParamGradInfoMap AppendBackward(
ProgramDescBind& program_desc, const VarDescBind& target,
ProgramDesc& program_desc, const VarDesc& target,
const std::unordered_set<std::string>& no_grad_vars) {
std::unordered_set<std::string> no_grad_var_names;
no_grad_var_names.reserve(no_grad_vars.size() + 1);
......@@ -541,11 +537,11 @@ ParamGradInfoMap AppendBackward(
PADDLE_ENFORCE(is_scalar, "target should be scalar");
VLOG(3) << "backward from loss=" << target.Name()
<< " data_type=" << target.GetDataType();
std::unique_ptr<OpDescBind> fill_one_op(
new OpDescBind("fill_constant", {}, {{"Out", {fill_one_op_out}}},
{{"shape", std::vector<int>{1}},
{"value", static_cast<float>(1.0)},
{"dtype", target.GetDataType()}}));
std::unique_ptr<OpDesc> fill_one_op(
new OpDesc("fill_constant", {}, {{"Out", {fill_one_op_out}}},
{{"shape", std::vector<int>{1}},
{"value", static_cast<float>(1.0)},
{"dtype", target.GetDataType()}}));
// infer var type of fill_one_op
fill_one_op->InferVarType(root_block);
......
paddle/framework/backward.h
浏览文件 @ 09189732
......@@ -49,7 +49,7 @@ using ParamGradInfoMap = std::unordered_map<std::string /*fwd_var_name*/,
GradVarInfo /*grad_var_info*/>;
ParamGradInfoMap AppendBackward(
ProgramDescBind& program_desc, const VarDescBind& target,
ProgramDesc& program_desc, const VarDesc& target,
const std::unordered_set<std::string>& no_grad_vars);
} // namespace framework
......
paddle/framework/backward_test.cc
浏览文件 @ 09189732
......@@ -58,13 +58,13 @@ class RowWiseAddGradMaker : public SingleGradOpDescMaker {
using SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<OpDescBind> Apply() const override {
auto grad_op = new OpDescBind();
std::unique_ptr<OpDesc> Apply() const override {
auto grad_op = new OpDesc();
grad_op->SetInput(GradVarName("Out"), OutputGrad("Out"));
grad_op->SetOutput(GradVarName("X"), InputGrad("X"));
grad_op->SetOutput(GradVarName("b"), InputGrad("b"));
grad_op->SetType("rowwise_add_grad");
return std::unique_ptr<OpDescBind>(grad_op);
return std::unique_ptr<OpDesc>(grad_op);
}
};
......@@ -190,11 +190,11 @@ class MinusGradOpDescMaker : public GradOpDescMakerBase {
public:
using GradOpDescMakerBase::GradOpDescMakerBase;
std::vector<std::unique_ptr<OpDescBind>> operator()() const override {
std::vector<std::unique_ptr<OpDescBind>> retv;
std::vector<std::unique_ptr<OpDesc>> operator()() const override {
std::vector<std::unique_ptr<OpDesc>> retv;
auto x_g = InputGrad("X");
if (!x_g.empty()) {
auto *op_desc = new OpDescBind();
auto *op_desc = new OpDesc();
op_desc->SetType("scale");
op_desc->SetInput("X", OutputGrad("Out"));
op_desc->SetOutput("Out", x_g);
......@@ -204,7 +204,7 @@ class MinusGradOpDescMaker : public GradOpDescMakerBase {
auto y_g = InputGrad("Y");
if (!y_g.empty()) {
auto *op_desc = new OpDescBind();
auto *op_desc = new OpDesc();
op_desc->SetType("scale");
op_desc->SetInput("X", OutputGrad("Out"));
op_desc->SetOutput("Out", y_g);
......@@ -505,25 +505,25 @@ TEST(Backward, linear_net_intermediate_variable_has_no_grad) {
}
TEST(Backward, simple_single_op) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
f::OpDescBind *op = block->AppendOp();
f::OpDesc *op = block->AppendOp();
op->SetType("rowwise_add");
op->SetInput("X", {"x"});
op->SetInput("b", {"b"});
op->SetOutput("Out", {"out"});
auto target = f::VarDescBind("out");
auto target = f::VarDesc("out");
target.SetShape({1});
auto var_to_grad =
AppendBackward(program, target, std::unordered_set<std::string>{});
ASSERT_EQ(block->AllOps().size(), 3UL);
f::OpDescBind *fill_op = block->AllOps()[1];
f::OpDesc *fill_op = block->AllOps()[1];
EXPECT_EQ(fill_op->Type(), "fill_constant");
f::OpDescBind *grad_op = block->AllOps()[2];
f::OpDesc *grad_op = block->AllOps()[2];
EXPECT_EQ(grad_op->Type(), "rowwise_add_grad");
ASSERT_EQ(grad_op->InputNames().size(), 1UL);
ASSERT_EQ(grad_op->OutputNames().size(), 2UL);
......@@ -543,16 +543,16 @@ TEST(Backward, simple_single_op) {
}
TEST(Backward, default_attribute) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::OpDescBind *op = block->AppendOp();
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
f::OpDesc *op = block->AppendOp();
op->SetType("mul");
op->SetInput("X", {"x"});
op->SetInput("Y", {"y"});
op->SetOutput("Out", {"out"});
op->CheckAttrs();
auto target = f::VarDescBind("out");
auto target = f::VarDesc("out");
target.SetShape({1});
AppendBackward(program, target, std::unordered_set<std::string>{});
......@@ -560,47 +560,47 @@ TEST(Backward, default_attribute) {
EXPECT_EQ(boost::get<int>(op->GetAttr("x_num_col_dims")), 1);
EXPECT_EQ(boost::get<int>(op->GetAttr("y_num_col_dims")), 1);
f::OpDescBind *fill_op = block->AllOps()[1];
f::OpDesc *fill_op = block->AllOps()[1];
EXPECT_EQ(fill_op->Type(), "fill_constant");
f::OpDescBind *grad_op = block->AllOps()[2];
f::OpDesc *grad_op = block->AllOps()[2];
ASSERT_EQ(grad_op->Type(), "mul_grad");
EXPECT_EQ(boost::get<int>(grad_op->GetAttr("x_num_col_dims")), 1);
EXPECT_EQ(boost::get<int>(grad_op->GetAttr("y_num_col_dims")), 1);
}
TEST(Backward, simple_mult_op) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::OpDescBind *op1 = block->AppendOp();
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
f::OpDesc *op1 = block->AppendOp();
op1->SetType("rowwise_add");
op1->SetInput("X", {"x1"});
op1->SetInput("b", {"b1"});
op1->SetOutput("Out", {"out1"});
f::OpDescBind *op2 = block->AppendOp();
f::OpDesc *op2 = block->AppendOp();
op2->SetType("mul");
op2->SetInput("X", {"out1"});
op2->SetInput("Y", {"y2"});
op2->SetOutput("Out", {"out2"});
f::OpDescBind *op3 = block->AppendOp();
f::OpDesc *op3 = block->AppendOp();
op3->SetType("rowwise_add");
op3->SetInput("X", {"out2"});
op3->SetInput("b", {"b3"});
op3->SetOutput("Out", {"out3"});
auto target = f::VarDescBind("out3");
auto target = f::VarDesc("out3");
target.SetShape({1});
size_t forward_len = block->AllOps().size();
auto var_to_grad =
AppendBackward(program, target, std::unordered_set<std::string>{});
ASSERT_EQ(block->AllOps().size(), 6UL + 1);
f::OpDescBind *fill_op = block->AllOps()[forward_len];
f::OpDesc *fill_op = block->AllOps()[forward_len];
EXPECT_EQ(fill_op->Type(), "fill_constant");
f::OpDescBind *grad_op1 = block->AllOps()[6];
f::OpDesc *grad_op1 = block->AllOps()[6];
EXPECT_EQ(grad_op1->Type(), "rowwise_add_grad");
ASSERT_EQ(grad_op1->InputNames().size(), 1UL);
ASSERT_EQ(grad_op1->OutputNames().size(), 2UL);
......@@ -611,7 +611,7 @@ TEST(Backward, simple_mult_op) {
EXPECT_EQ(grad_op1->Output(f::GradVarName("b")),
std::vector<std::string>({f::GradVarName("b1")}));
f::OpDescBind *grad_op2 = block->AllOps()[5];
f::OpDesc *grad_op2 = block->AllOps()[5];
EXPECT_EQ(grad_op2->Type(), "mul_grad");
ASSERT_EQ(grad_op2->InputNames().size(), 4UL);
ASSERT_EQ(grad_op2->OutputNames().size(), 2UL);
......@@ -625,7 +625,7 @@ TEST(Backward, simple_mult_op) {
EXPECT_EQ(grad_op2->Output(f::GradVarName("Y")),
std::vector<std::string>({f::GradVarName("y2")}));
f::OpDescBind *grad_op3 = block->AllOps()[4];
f::OpDesc *grad_op3 = block->AllOps()[4];
EXPECT_EQ(grad_op3->Type(), "rowwise_add_grad");
ASSERT_EQ(grad_op3->InputNames().size(), 1UL);
ASSERT_EQ(grad_op3->OutputNames().size(), 2UL);
......@@ -655,42 +655,42 @@ TEST(Backward, simple_mult_op) {
}
TEST(Backward, intermedia_var_no_grad) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::OpDescBind *op1 = block->AppendOp();
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
f::OpDesc *op1 = block->AppendOp();
op1->SetType("rowwise_add");
op1->SetInput("X", {"x1"});
op1->SetInput("b", {"b1"});
op1->SetOutput("Out", {"out1"});
f::OpDescBind *op2 = block->AppendOp();
f::OpDesc *op2 = block->AppendOp();
op2->SetType("mul");
op2->SetInput("X", {"x2"});
op2->SetInput("Y", {"y2"});
op2->SetOutput("Out", {"out2"});
f::OpDescBind *op3 = block->AppendOp();
f::OpDesc *op3 = block->AppendOp();
op3->SetType("rowwise_add");
op3->SetInput("X", {"out2"});
op3->SetInput("b", {"b3"});
op3->SetOutput("Out", {"out3"});
f::OpDescBind *op4 = block->AppendOp();
f::OpDesc *op4 = block->AppendOp();
op4->SetType("mul");
op4->SetInput("X", {"out1"});
op4->SetInput("Y", {"out3"});
op4->SetOutput("Out", {"out4"});
auto target = f::VarDescBind("out4");
auto target = f::VarDesc("out4");
target.SetShape({1});
size_t forward_len = block->AllOps().size();
auto var_to_grad = AppendBackward(program, target, {"out3"});
ASSERT_EQ(block->AllOps().size(), 7UL);
f::OpDescBind *fill_op = block->AllOps()[forward_len];
f::OpDesc *fill_op = block->AllOps()[forward_len];
EXPECT_EQ(fill_op->Type(), "fill_constant");
f::OpDescBind *grad_op1 = block->AllOps()[6];
f::OpDesc *grad_op1 = block->AllOps()[6];
EXPECT_EQ(grad_op1->Type(), "rowwise_add_grad");
ASSERT_EQ(grad_op1->InputNames().size(), 1UL);
ASSERT_EQ(grad_op1->OutputNames().size(), 2UL);
......@@ -701,7 +701,7 @@ TEST(Backward, intermedia_var_no_grad) {
EXPECT_EQ(grad_op1->Output(f::GradVarName("b")),
std::vector<std::string>({f::GradVarName("b1")}));
f::OpDescBind *grad_op4 = block->AllOps()[5];
f::OpDesc *grad_op4 = block->AllOps()[5];
EXPECT_EQ(grad_op4->Type(), "mul_grad");
ASSERT_EQ(grad_op4->InputNames().size(), 4UL);
ASSERT_EQ(grad_op4->OutputNames().size(), 2UL);
......@@ -726,32 +726,32 @@ TEST(Backward, intermedia_var_no_grad) {
}
TEST(Backward, var_no_grad) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::OpDescBind *op1 = block->AppendOp();
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
f::OpDesc *op1 = block->AppendOp();
op1->SetType("mult_in_out");
op1->SetInput("X", {"x1"});
op1->SetInput("H", {"h1"});
op1->SetOutput("Y", {"y1"});
op1->SetOutput("Z", {"z1"});
f::OpDescBind *op2 = block->AppendOp();
f::OpDesc *op2 = block->AppendOp();
op2->SetType("mult_in_out");
op2->SetInput("X", {"y1"});
op2->SetInput("H", {"z1"});
op2->SetOutput("Y", {"y2"});
op2->SetOutput("Z", {"z2"});
auto target = f::VarDescBind("z2");
auto target = f::VarDesc("z2");
target.SetShape({1});
size_t forward_len = block->AllOps().size();
auto var_to_grad = AppendBackward(program, target, {"z1"});
ASSERT_EQ(block->AllOps().size(), 6UL);
f::OpDescBind *fill_op = block->AllOps()[forward_len];
f::OpDesc *fill_op = block->AllOps()[forward_len];
EXPECT_EQ(fill_op->Type(), "fill_constant");
f::OpDescBind *grad_op2 = block->AllOps()[3];
f::OpDesc *grad_op2 = block->AllOps()[3];
ASSERT_EQ(grad_op2->Type(), "mult_in_out_grad");
ASSERT_EQ(grad_op2->InputNames().size(), 6UL);
ASSERT_EQ(grad_op2->OutputNames().size(), 2UL);
......@@ -767,7 +767,7 @@ TEST(Backward, var_no_grad) {
std::vector<std::string>({f::GradVarName("y1")}));
EXPECT_EQ(grad_op2->Output(f::GradVarName("H")), std::vector<std::string>());
f::OpDescBind *fill_zero_op = block->AllOps()[4];
f::OpDesc *fill_zero_op = block->AllOps()[4];
ASSERT_EQ(fill_zero_op->Type(), "fill_zeros_like");
ASSERT_EQ(fill_zero_op->InputNames().size(), 1UL);
ASSERT_EQ(fill_zero_op->OutputNames().size(), 1UL);
......@@ -775,7 +775,7 @@ TEST(Backward, var_no_grad) {
EXPECT_EQ(fill_zero_op->Output("Y"),
std::vector<std::string>({std::string("z1") + f::kZeroVarSuffix}));
f::OpDescBind *grad_op1 = block->AllOps()[5];
f::OpDesc *grad_op1 = block->AllOps()[5];
ASSERT_EQ(grad_op1->Type(), "mult_in_out_grad");
ASSERT_EQ(grad_op1->InputNames().size(), 6UL);
ASSERT_EQ(grad_op1->OutputNames().size(), 2UL);
......@@ -803,37 +803,37 @@ TEST(Backward, var_no_grad) {
}
TEST(Backward, shared_var) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::OpDescBind *op1 = block->AppendOp();
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
f::OpDesc *op1 = block->AppendOp();
op1->SetType("rowwise_add");
op1->SetInput("X", {"x1"});
op1->SetInput("b", {"b1"});
op1->SetOutput("Out", {"out1"});
f::OpDescBind *op2 = block->AppendOp();
f::OpDesc *op2 = block->AppendOp();
op2->SetType("mul");
op2->SetInput("X", {"out1"});
op2->SetInput("Y", {"y2"});
op2->SetOutput("Out", {"out2"});
f::OpDescBind *op3 = block->AppendOp();
f::OpDesc *op3 = block->AppendOp();
op3->SetType("rowwise_add");
op3->SetInput("X", {"out1"});
op3->SetInput("b", {"b3"});
op3->SetOutput("Out", {"out3"});
auto target = f::VarDescBind("out3");
auto target = f::VarDesc("out3");
target.SetShape({1});
size_t forward_len = block->AllOps().size();
auto var_to_grad =
AppendBackward(program, target, std::unordered_set<std::string>{});
ASSERT_EQ(block->AllOps().size(), 8UL);
f::OpDescBind *fill_op = block->AllOps()[forward_len];
f::OpDesc *fill_op = block->AllOps()[forward_len];
EXPECT_EQ(fill_op->Type(), "fill_constant");
f::OpDescBind *grad_op3 = block->AllOps()[4];
f::OpDesc *grad_op3 = block->AllOps()[4];
ASSERT_EQ(grad_op3->Type(), "rowwise_add_grad");
ASSERT_EQ(grad_op3->InputNames().size(), 1UL);
ASSERT_EQ(grad_op3->OutputNames().size(), 2UL);
......@@ -844,7 +844,7 @@ TEST(Backward, shared_var) {
EXPECT_EQ(grad_op3->Output(f::GradVarName("b")),
std::vector<std::string>({f::GradVarName("b3")}));
f::OpDescBind *grad_op4 = block->AllOps()[5];
f::OpDesc *grad_op4 = block->AllOps()[5];
ASSERT_EQ(grad_op4->Type(), "mul_grad");
ASSERT_EQ(grad_op4->InputNames().size(), 4UL);
ASSERT_EQ(grad_op4->OutputNames().size(), 2UL);
......@@ -858,7 +858,7 @@ TEST(Backward, shared_var) {
EXPECT_EQ(grad_op4->Output(f::GradVarName("Y")),
std::vector<std::string>({f::GradVarName("y2")}));
f::OpDescBind *sum_op = block->AllOps()[6];
f::OpDesc *sum_op = block->AllOps()[6];
ASSERT_EQ(sum_op->Type(), "sum");
ASSERT_EQ(sum_op->InputNames().size(), 1UL);
ASSERT_EQ(sum_op->OutputNames().size(), 1UL);
......@@ -868,7 +868,7 @@ TEST(Backward, shared_var) {
EXPECT_EQ(sum_op->Output("Out"),
std::vector<std::string>({f::GradVarName("out1")}));
f::OpDescBind *grad_op1 = block->AllOps()[7];
f::OpDesc *grad_op1 = block->AllOps()[7];
ASSERT_EQ(grad_op1->Type(), "rowwise_add_grad");
ASSERT_EQ(grad_op1->InputNames().size(), 1UL);
ASSERT_EQ(grad_op1->OutputNames().size(), 2UL);
......@@ -895,19 +895,19 @@ TEST(Backward, shared_var) {
}
TEST(Backward, half_backward) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
auto *op1 = block->AppendOp();
op1->SetType("minus");
op1->SetInput("X", {"a"});
op1->SetInput("Y", {"b"});
op1->SetOutput("Out", {"out"});
auto target = f::VarDescBind("out");
auto target = f::VarDesc("out");
target.SetShape({1});
size_t forward_len = block->AllOps().size();
auto var_to_grad = AppendBackward(program, target, {"b"});
f::OpDescBind *fill_op = block->AllOps()[forward_len];
f::OpDesc *fill_op = block->AllOps()[forward_len];
EXPECT_EQ(fill_op->Type(), "fill_constant");
auto ops = block->AllOps();
ASSERT_EQ(3UL, ops.size());
......
paddle/framework/block_desc.cc
浏览文件 @ 09189732
......@@ -19,18 +19,18 @@ limitations under the License. */
namespace paddle {
namespace framework {
VarDescBind *BlockDescBind::Var(const std::string &name) {
VarDesc *BlockDesc::Var(const std::string &name) {
auto it = vars_.find(name);
if (it != vars_.end()) {
return it->second.get();
}
need_update_ = true;
auto *var = new VarDescBind(name);
auto *var = new VarDesc(name);
vars_[name].reset(var);
return var;
}
VarDescBind *BlockDescBind::FindVar(const std::string &name) const {
VarDesc *BlockDesc::FindVar(const std::string &name) const {
auto it = vars_.find(name);
if (it == vars_.end()) {
return nullptr;
......@@ -38,11 +38,11 @@ VarDescBind *BlockDescBind::FindVar(const std::string &name) const {
return it->second.get();
}
bool BlockDescBind::HasVar(const std::string &name) const {
bool BlockDesc::HasVar(const std::string &name) const {
return vars_.find(name) != vars_.end();
}
VarDescBind *BlockDescBind::FindVarRecursive(const std::string &name) const {
VarDesc *BlockDesc::FindVarRecursive(const std::string &name) const {
if (name == kEmptyVarName) return nullptr;
auto it = vars_.find(name);
......@@ -53,53 +53,52 @@ VarDescBind *BlockDescBind::FindVarRecursive(const std::string &name) const {
return it->second.get();
}
VarDescBind *BlockDescBind::FindRecursiveOrCreateVar(
const std::string &name_bytes) {
VarDescBind *res = FindVarRecursive(name_bytes);
VarDesc *BlockDesc::FindRecursiveOrCreateVar(const std::string &name_bytes) {
VarDesc *res = FindVarRecursive(name_bytes);
if (res == nullptr) {
res = Var(name_bytes);
}
return res;
}
bool BlockDescBind::HasVarRecursive(const std::string &name) const {
bool BlockDesc::HasVarRecursive(const std::string &name) const {
return FindVarRecursive(name) != nullptr;
}
std::vector<VarDescBind *> BlockDescBind::AllVars() const {
std::vector<VarDescBind *> res;
std::vector<VarDesc *> BlockDesc::AllVars() const {
std::vector<VarDesc *> res;
for (const auto &p : vars_) {
res.push_back(p.second.get());
}
return res;
}
OpDescBind *BlockDescBind::AppendOp() {
OpDesc *BlockDesc::AppendOp() {
need_update_ = true;
ops_.emplace_back(new OpDescBind());
ops_.emplace_back(new OpDesc());
return ops_.back().get();
}
void BlockDescBind::AppendAllocatedOp(std::unique_ptr<OpDescBind> &&op_desc) {
void BlockDesc::AppendAllocatedOp(std::unique_ptr<OpDesc> &&op_desc) {
need_update_ = true;
ops_.emplace_back(std::move(op_desc));
}
OpDescBind *BlockDescBind::PrependOp() {
OpDesc *BlockDesc::PrependOp() {
need_update_ = true;
ops_.emplace_front(new OpDescBind());
ops_.emplace_front(new OpDesc());
return ops_.front().get();
}
std::vector<OpDescBind *> BlockDescBind::AllOps() const {
std::vector<OpDescBind *> res;
std::vector<OpDesc *> BlockDesc::AllOps() const {
std::vector<OpDesc *> res;
for (const auto &op : ops_) {
res.push_back(op.get());
}
return res;
}
void BlockDescBind::Flush() {
void BlockDesc::Flush() {
for (auto &op_desc : ops_) {
op_desc->Flush();
}
......@@ -121,43 +120,43 @@ void BlockDescBind::Flush() {
}
}
BlockDescBind *BlockDescBind::ParentBlock() const {
BlockDesc *BlockDesc::ParentBlock() const {
if (this->desc_->parent_idx() == kNoneBlockIndex) {
return nullptr;
}
return prog_->MutableBlock(static_cast<size_t>(this->desc_->parent_idx()));
}
proto::BlockDesc *BlockDescBind::Proto() {
proto::BlockDesc *BlockDesc::Proto() {
Flush();
return desc_;
}
BlockDescBind::BlockDescBind(ProgramDescBind *prog, proto::BlockDesc *desc)
BlockDesc::BlockDesc(ProgramDesc *prog, proto::BlockDesc *desc)
: prog_(prog), desc_(desc), need_update_(false) {
for (const proto::VarDesc &var_desc : desc_->vars()) {
vars_[var_desc.name()].reset(new VarDescBind(var_desc));
vars_[var_desc.name()].reset(new VarDesc(var_desc));
}
for (const proto::OpDesc &op_desc : desc_->ops()) {
ops_.emplace_back(new OpDescBind(op_desc, prog));
ops_.emplace_back(new OpDesc(op_desc, prog));
}
}
BlockDescBind::BlockDescBind(const BlockDescBind &other, proto::BlockDesc *desc,
ProgramDescBind *prog)
BlockDesc::BlockDesc(const BlockDesc &other, proto::BlockDesc *desc,
ProgramDesc *prog)
: prog_(prog), desc_(desc) {
need_update_ = true;
for (auto &op : other.ops_) {
ops_.emplace_back(new OpDescBind(*op));
ops_.emplace_back(new OpDesc(*op));
}
for (auto &it : other.vars_) {
auto *var = new VarDescBind(*it.second);
auto *var = new VarDesc(*it.second);
vars_[it.first].reset(var);
}
}
void BlockDescBind::ClearPBOps() {
void BlockDesc::ClearPBOps() {
auto ops = this->desc_->mutable_ops();
while (!ops->empty()) {
// we do not own the OpDesc, so release the ownership.
......@@ -165,7 +164,7 @@ void BlockDescBind::ClearPBOps() {
}
}
void BlockDescBind::ClearPBVars() {
void BlockDesc::ClearPBVars() {
auto vars = this->desc_->mutable_vars();
while (!vars->empty()) {
// we do not own the VarDesc, so release the ownership.
......
paddle/framework/block_desc.h
浏览文件 @ 09189732
......@@ -28,20 +28,19 @@ limitations under the License. */
namespace paddle {
namespace framework {
class ProgramDescBind;
class ProgramDesc;
// Each Protobuf Message, we provide a XXXBind class. In that class, we optimize
// read/write speed. Only when we want the protobuf message, the local changes
// will be synchronized (by `Sync` method).
class BlockDescBind {
class BlockDesc {
public:
BlockDescBind(ProgramDescBind *prog, proto::BlockDesc *desc);
BlockDesc(ProgramDesc *prog, proto::BlockDesc *desc);
BlockDescBind(const BlockDescBind &other, proto::BlockDesc *desc,
ProgramDescBind *prog);
BlockDesc(const BlockDesc &other, proto::BlockDesc *desc, ProgramDesc *prog);
~BlockDescBind() {
~BlockDesc() {
this->ClearPBVars();
this->ClearPBOps();
}
......@@ -50,15 +49,15 @@ class BlockDescBind {
int32_t Parent() const { return desc_->parent_idx(); }
VarDescBind *Var(const std::string &name_bytes);
VarDesc *Var(const std::string &name_bytes);
VarDescBind *FindVar(const std::string &name_bytes) const;
VarDesc *FindVar(const std::string &name_bytes) const;
bool HasVar(const std::string &var_name) const;
VarDescBind *FindVarRecursive(const std::string &name_bytes) const;
VarDesc *FindVarRecursive(const std::string &name_bytes) const;
VarDescBind *FindRecursiveOrCreateVar(const std::string &name_bytes);
VarDesc *FindRecursiveOrCreateVar(const std::string &name_bytes);
bool HasVarRecursive(const std::string &var_name) const;
......@@ -70,41 +69,41 @@ class BlockDescBind {
return var_names;
}
std::vector<VarDescBind *> AllVars() const;
std::vector<VarDesc *> AllVars() const;
BlockDescBind *ParentBlock() const;
BlockDesc *ParentBlock() const;
OpDescBind *AppendOp();
OpDesc *AppendOp();
void AppendAllocatedOp(std::unique_ptr<OpDescBind> &&op_desc);
void AppendAllocatedOp(std::unique_ptr<OpDesc> &&op_desc);
OpDescBind *PrependOp();
OpDesc *PrependOp();
std::vector<OpDescBind *> AllOps() const;
std::vector<OpDesc *> AllOps() const;
size_t OpSize() const { return ops_.size(); }
OpDescBind *Op(int idx) { return ops_.at(idx).get(); }
OpDesc *Op(int idx) { return ops_.at(idx).get(); }
void Flush();
proto::BlockDesc *Proto();
ProgramDescBind *Program() { return this->prog_; }
ProgramDesc *Program() { return this->prog_; }
private:
void ClearPBOps();
void ClearPBVars();
private:
ProgramDescBind *prog_; // not_own
ProgramDesc *prog_; // not_own
proto::BlockDesc *desc_; // not_own
bool need_update_;
std::deque<std::unique_ptr<OpDescBind>> ops_;
std::unordered_map<std::string, std::unique_ptr<VarDescBind>> vars_;
std::deque<std::unique_ptr<OpDesc>> ops_;
std::unordered_map<std::string, std::unique_ptr<VarDesc>> vars_;
DISABLE_COPY_AND_ASSIGN(BlockDescBind);
DISABLE_COPY_AND_ASSIGN(BlockDesc);
};
} // namespace framework
} // namespace paddle
paddle/framework/details/op_registry.h
浏览文件 @ 09189732
......@@ -106,10 +106,10 @@ template <typename T>
struct OpInfoFiller<T, kGradOpDescMaker> {
void operator()(const char* op_type, OpInfo* info) const {
info->grad_op_maker_ = [](
const OpDescBind& fwd_op,
const OpDesc& fwd_op,
const std::unordered_set<std::string>& no_grad_set,
std::unordered_map<std::string, std::string>* grad_to_var,
const std::vector<BlockDescBind*>& grad_block) {
const std::vector<BlockDesc*>& grad_block) {
T maker(fwd_op, no_grad_set, grad_to_var, grad_block);
return maker();
};
......@@ -119,7 +119,7 @@ struct OpInfoFiller<T, kGradOpDescMaker> {
template <typename T>
struct OpInfoFiller<T, kVarTypeInference> {
void operator()(const char* op_type, OpInfo* info) const {
info->infer_var_type_ = [](const OpDescBind& fwd_op, BlockDescBind* block) {
info->infer_var_type_ = [](const OpDesc& fwd_op, BlockDesc* block) {
T inference;
inference(fwd_op, block);
};
......
paddle/framework/executor.cc
浏览文件 @ 09189732
......@@ -64,7 +64,7 @@ static void CreateTensor(Variable* var, proto::VarDesc::VarType var_type) {
}
}
void Executor::Run(const ProgramDescBind& pdesc, Scope* scope, int block_id,
void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id,
bool create_local_scope) {
// TODO(tonyyang-svail):
// - only runs on the first device (i.e. no interdevice communication)
......
paddle/framework/executor.h
浏览文件 @ 09189732
......@@ -114,7 +114,7 @@ class Executor {
* ProgramDesc
* Scope
*/
void Run(const ProgramDescBind&, Scope*, int, bool create_local_scope = true);
void Run(const ProgramDesc&, Scope*, int, bool create_local_scope = true);
private:
std::vector<const platform::DeviceContext*> device_contexts_;
......
paddle/framework/grad_op_desc_maker.h
浏览文件 @ 09189732
......@@ -25,18 +25,16 @@ namespace framework {
class GradOpDescMakerBase {
public:
explicit GradOpDescMakerBase(
const OpDescBind& fwd_op,
const std::unordered_set<std::string>& no_grad_set,
const OpDesc& fwd_op, const std::unordered_set<std::string>& no_grad_set,
std::unordered_map<std::string, std::string>* grad_to_var,
const std::vector<BlockDescBind*>& grad_block =
std::vector<BlockDescBind*>())
const std::vector<BlockDesc*>& grad_block = std::vector<BlockDesc*>())
: fwd_op_(fwd_op),
no_grad_set_(no_grad_set),
grad_to_var_(grad_to_var),
grad_block_(grad_block) {}
virtual ~GradOpDescMakerBase() = default;
virtual std::vector<std::unique_ptr<OpDescBind>> operator()() const = 0;
virtual std::vector<std::unique_ptr<OpDesc>> operator()() const = 0;
protected:
std::vector<std::string> InputGrad(const std::string& name,
......@@ -105,26 +103,26 @@ class GradOpDescMakerBase {
std::string ForwardOpType() const { return this->fwd_op_.Type(); }
private:
const OpDescBind& fwd_op_;
const OpDesc& fwd_op_;
const std::unordered_set<std::string>& no_grad_set_;
std::unordered_map<std::string, std::string>* grad_to_var_;
protected:
std::vector<BlockDescBind*> grad_block_;
std::vector<BlockDesc*> grad_block_;
};
class SingleGradOpDescMaker : public GradOpDescMakerBase {
public:
using GradOpDescMakerBase::GradOpDescMakerBase;
std::vector<std::unique_ptr<OpDescBind>> operator()() const {
std::vector<std::unique_ptr<OpDescBind>> retv;
std::vector<std::unique_ptr<OpDesc>> operator()() const {
std::vector<std::unique_ptr<OpDesc>> retv;
retv.emplace_back(this->Apply());
return retv;
}
protected:
virtual std::unique_ptr<OpDescBind> Apply() const = 0;
virtual std::unique_ptr<OpDesc> Apply() const = 0;
};
template <bool DropEmptyIG = true>
......@@ -133,8 +131,8 @@ class DefaultGradOpDescMaker : public SingleGradOpDescMaker {
using SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
virtual std::unique_ptr<OpDescBind> Apply() const {
auto* grad = new OpDescBind();
virtual std::unique_ptr<OpDesc> Apply() const {
auto* grad = new OpDesc();
grad->SetType(this->GradOpType());
for (auto& input_param : this->InputNames()) {
......@@ -150,7 +148,7 @@ class DefaultGradOpDescMaker : public SingleGradOpDescMaker {
grad->SetAttrMap(this->Attrs());
return std::unique_ptr<OpDescBind>(grad);
return std::unique_ptr<OpDesc>(grad);
}
virtual std::string GradOpType() const {
......@@ -161,7 +159,7 @@ class DefaultGradOpDescMaker : public SingleGradOpDescMaker {
class EmptyGradOpMaker : public GradOpDescMakerBase {
public:
using GradOpDescMakerBase::GradOpDescMakerBase;
std::vector<std::unique_ptr<OpDescBind>> operator()() const override {
std::vector<std::unique_ptr<OpDesc>> operator()() const override {
return {};
}
};
......
paddle/framework/op_desc.cc
浏览文件 @ 09189732
......@@ -25,12 +25,11 @@ limitations under the License. */
namespace paddle {
namespace framework {
class OpDescBind;
class BlockDescBind;
class OpDesc;
class BlockDesc;
class CompileTimeInferShapeContext : public InferShapeContext {
public:
CompileTimeInferShapeContext(const OpDescBind &op,
const BlockDescBind &block);
CompileTimeInferShapeContext(const OpDesc &op, const BlockDesc &block);
bool HasInput(const std::string &name) const override;
......@@ -76,13 +75,12 @@ class CompileTimeInferShapeContext : public InferShapeContext {
void SetDim(const std::string &name, const DDim &dim) override;
const OpDescBind &op_;
const BlockDescBind &block_;
const OpDesc &op_;
const BlockDesc &block_;
};
OpDescBind::OpDescBind(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs,
const AttributeMap &attrs) {
OpDesc::OpDesc(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const AttributeMap &attrs) {
desc_.set_type(type);
inputs_ = inputs;
outputs_ = outputs;
......@@ -90,7 +88,7 @@ OpDescBind::OpDescBind(const std::string &type, const VariableNameMap &inputs,
need_update_ = true;
}
OpDescBind::OpDescBind(const proto::OpDesc &desc, ProgramDescBind *prog)
OpDesc::OpDesc(const proto::OpDesc &desc, ProgramDesc *prog)
: desc_(desc), need_update_(false) {
// restore inputs_
int input_size = desc_.inputs_size();
......@@ -126,20 +124,19 @@ OpDescBind::OpDescBind(const proto::OpDesc &desc, ProgramDescBind *prog)
}
}
proto::OpDesc *OpDescBind::Proto() {
proto::OpDesc *OpDesc::Proto() {
Flush();
return &desc_;
}
const std::vector<std::string> &OpDescBind::Input(
const std::string &name) const {
const std::vector<std::string> &OpDesc::Input(const std::string &name) const {
auto it = inputs_.find(name);
PADDLE_ENFORCE(it != inputs_.end(), "Input %s cannot be found in Op %s", name,
Type());
return it->second;
}
std::vector<std::string> OpDescBind::InputArgumentNames() const {
std::vector<std::string> OpDesc::InputArgumentNames() const {
std::vector<std::string> retv;
for (auto &ipt : this->inputs_) {
retv.insert(retv.end(), ipt.second.begin(), ipt.second.end());
......@@ -147,21 +144,20 @@ std::vector<std::string> OpDescBind::InputArgumentNames() const {
return retv;
}
void OpDescBind::SetInput(const std::string &param_name,
const std::vector<std::string> &args) {
void OpDesc::SetInput(const std::string &param_name,
const std::vector<std::string> &args) {
need_update_ = true;
inputs_[param_name] = args;
}
const std::vector<std::string> &OpDescBind::Output(
const std::string &name) const {
const std::vector<std::string> &OpDesc::Output(const std::string &name) const {
auto it = outputs_.find(name);
PADDLE_ENFORCE(it != outputs_.end(), "Output %s cannot be found in Op %s",
name, Type());
return it->second;
}
std::vector<std::string> OpDescBind::OutputArgumentNames() const {
std::vector<std::string> OpDesc::OutputArgumentNames() const {
std::vector<std::string> retv;
for (auto &ipt : this->outputs_) {
retv.insert(retv.end(), ipt.second.begin(), ipt.second.end());
......@@ -169,19 +165,19 @@ std::vector<std::string> OpDescBind::OutputArgumentNames() const {
return retv;
}
void OpDescBind::SetOutput(const std::string &param_name,
const std::vector<std::string> &args) {
void OpDesc::SetOutput(const std::string &param_name,
const std::vector<std::string> &args) {
need_update_ = true;
this->outputs_[param_name] = args;
}
proto::AttrType OpDescBind::GetAttrType(const std::string &name) const {
proto::AttrType OpDesc::GetAttrType(const std::string &name) const {
auto it = attrs_.find(name);
PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
return static_cast<proto::AttrType>(it->second.which() - 1);
}
std::vector<std::string> OpDescBind::AttrNames() const {
std::vector<std::string> OpDesc::AttrNames() const {
std::vector<std::string> retv;
retv.reserve(attrs_.size());
for (auto &attr : attrs_) {
......@@ -190,41 +186,39 @@ std::vector<std::string> OpDescBind::AttrNames() const {
return retv;
}
void OpDescBind::SetAttr(const std::string &name, const Attribute &v) {
void OpDesc::SetAttr(const std::string &name, const Attribute &v) {
this->attrs_[name] = v;
need_update_ = true;
}
void OpDescBind::SetBlockAttr(const std::string &name, BlockDescBind &block) {
void OpDesc::SetBlockAttr(const std::string &name, BlockDesc &block) {
this->attrs_[name] = &block;
need_update_ = true;
}
void OpDescBind::SetAttrMap(
void OpDesc::SetAttrMap(
const std::unordered_map<std::string, Attribute> &attr_map) {
attrs_ = attr_map;
need_update_ = true;
}
Attribute OpDescBind::GetAttr(const std::string &name) const {
Attribute OpDesc::GetAttr(const std::string &name) const {
auto it = attrs_.find(name);
PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
return it->second;
}
int OpDescBind::GetBlockAttr(const std::string &name) const {
int OpDesc::GetBlockAttr(const std::string &name) const {
auto it = attrs_.find(name);
PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
return boost::get<BlockDescBind *>(it->second)->ID();
return boost::get<BlockDesc *>(it->second)->ID();
}
const std::unordered_map<std::string, Attribute> &OpDescBind::GetAttrMap()
const {
const std::unordered_map<std::string, Attribute> &OpDesc::GetAttrMap() const {
return attrs_;
}
void OpDescBind::Rename(const std::string &old_name,
const std::string &new_name) {
void OpDesc::Rename(const std::string &old_name, const std::string &new_name) {
for (auto &input : inputs_) {
std::replace(input.second.begin(), input.second.end(), old_name, new_name);
}
......@@ -235,8 +229,8 @@ void OpDescBind::Rename(const std::string &old_name,
need_update_ = true;
}
void OpDescBind::RenameOutput(const std::string &old_name,
const std::string &new_name) {
void OpDesc::RenameOutput(const std::string &old_name,
const std::string &new_name) {
for (auto &output : outputs_) {
std::replace(output.second.begin(), output.second.end(), old_name,
new_name);
......@@ -244,8 +238,8 @@ void OpDescBind::RenameOutput(const std::string &old_name,
need_update_ = true;
}
void OpDescBind::RenameInput(const std::string &old_name,
const std::string &new_name) {
void OpDesc::RenameInput(const std::string &old_name,
const std::string &new_name) {
for (auto &input : inputs_) {
std::replace(input.second.begin(), input.second.end(), old_name, new_name);
}
......@@ -278,7 +272,7 @@ struct SetAttrDescVisitor : public boost::static_visitor<void> {
void operator()(boost::blank) const { PADDLE_THROW("Unexpected branch"); }
};
void OpDescBind::Flush() {
void OpDesc::Flush() {
if (need_update_) {
this->desc_.mutable_inputs()->Clear();
for (auto &ipt : inputs_) {
......@@ -330,7 +324,7 @@ static void InitInferShapeFuncs() {
});
}
void OpDescBind::CheckAttrs() {
void OpDesc::CheckAttrs() {
PADDLE_ENFORCE(!Type().empty(),
"CheckAttr() can not be called before type is setted.");
auto *checker = OpInfoMap::Instance().Get(Type()).Checker();
......@@ -342,7 +336,7 @@ void OpDescBind::CheckAttrs() {
checker->Check(attrs_);
}
void OpDescBind::InferShape(const BlockDescBind &block) const {
void OpDesc::InferShape(const BlockDesc &block) const {
VLOG(3) << "CompileTime infer shape on " << Type();
InitInferShapeFuncs();
auto &infer_shape = OpInfoMap::Instance().Get(this->Type()).infer_shape_;
......@@ -365,7 +359,7 @@ void OpDescBind::InferShape(const BlockDescBind &block) const {
infer_shape(&ctx);
}
void OpDescBind::InferVarType(BlockDescBind *block) const {
void OpDesc::InferVarType(BlockDesc *block) const {
auto &info = OpInfoMap::Instance().Get(this->Type());
if (info.infer_var_type_) {
info.infer_var_type_(*this, block);
......@@ -384,7 +378,7 @@ void OpDescBind::InferVarType(BlockDescBind *block) const {
}
CompileTimeInferShapeContext::CompileTimeInferShapeContext(
const OpDescBind &op, const BlockDescBind &block)
const OpDesc &op, const BlockDesc &block)
: op_(op), block_(block) {}
bool CompileTimeInferShapeContext::HasInput(const std::string &name) const {
......
paddle/framework/op_desc.h
浏览文件 @ 09189732
......@@ -23,17 +23,17 @@ limitations under the License. */
namespace paddle {
namespace framework {
class BlockDescBind;
class ProgramDescBind;
class BlockDesc;
class ProgramDesc;
class OpDescBind {
class OpDesc {
public:
OpDescBind() {}
OpDesc() {}
OpDescBind(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const AttributeMap &attrs);
OpDesc(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const AttributeMap &attrs);
OpDescBind(const proto::OpDesc &desc, ProgramDescBind *prog);
OpDesc(const proto::OpDesc &desc, ProgramDesc *prog);
proto::OpDesc *Proto();
......@@ -65,7 +65,7 @@ class OpDescBind {
void SetAttr(const std::string &name, const Attribute &v);
void SetBlockAttr(const std::string &name, BlockDescBind &block);
void SetBlockAttr(const std::string &name, BlockDesc &block);
Attribute GetAttr(const std::string &name) const;
......@@ -107,9 +107,9 @@ class OpDescBind {
void CheckAttrs();
void InferShape(const BlockDescBind &block) const;
void InferShape(const BlockDesc &block) const;
void InferVarType(BlockDescBind *block) const;
void InferVarType(BlockDesc *block) const;
void MarkAsTarget() { desc_.set_is_target(true); }
......
paddle/framework/op_registry.cc
浏览文件 @ 09189732
......@@ -47,7 +47,7 @@ static VariableNameMap ConvertOpDescVarsToVarNameMap(
std::unique_ptr<OperatorBase> OpRegistry::CreateOp(
const proto::OpDesc& op_desc) {
VLOG(1) << "CreateOp directly from OpDesc is deprecated. It should only be"
"used in unit tests. Use CreateOp(const OpDescBind& op_desc) "
"used in unit tests. Use CreateOp(const OpDesc& op_desc) "
"instead.";
VariableNameMap inputs = ConvertOpDescVarsToVarNameMap(op_desc.inputs());
VariableNameMap outputs = ConvertOpDescVarsToVarNameMap(op_desc.outputs());
......@@ -59,7 +59,7 @@ std::unique_ptr<OperatorBase> OpRegistry::CreateOp(
return CreateOp(op_desc.type(), inputs, outputs, attrs);
}
std::unique_ptr<OperatorBase> OpRegistry::CreateOp(const OpDescBind& op_desc) {
std::unique_ptr<OperatorBase> OpRegistry::CreateOp(const OpDesc& op_desc) {
return CreateOp(op_desc.Type(), op_desc.Inputs(), op_desc.Outputs(),
op_desc.GetAttrMap());
}
......
paddle/framework/op_registry.h
浏览文件 @ 09189732
......@@ -79,7 +79,7 @@ class OpRegistry {
static std::unique_ptr<OperatorBase> CreateOp(const proto::OpDesc& op_desc);
static std::unique_ptr<OperatorBase> CreateOp(const OpDescBind& op_desc);
static std::unique_ptr<OperatorBase> CreateOp(const OpDesc& op_desc);
};
template <typename PlaceType, bool at_end, size_t I, typename... KernelType>
......
paddle/framework/program_desc.cc
浏览文件 @ 09189732
......@@ -18,49 +18,49 @@ limitations under the License. */
namespace paddle {
namespace framework {
BlockDescBind *ProgramDescBind::AppendBlock(const BlockDescBind &parent) {
BlockDesc *ProgramDesc::AppendBlock(const BlockDesc &parent) {
auto *b = desc_.add_blocks();
b->set_parent_idx(parent.ID());
b->set_idx(desc_.blocks_size() - 1);
blocks_.emplace_back(new BlockDescBind(this, b));
blocks_.emplace_back(new BlockDesc(this, b));
return blocks_.back().get();
}
proto::ProgramDesc *ProgramDescBind::Proto() {
proto::ProgramDesc *ProgramDesc::Proto() {
for (auto &block : blocks_) {
block->Flush();
}
return &desc_;
}
ProgramDescBind::ProgramDescBind() {
ProgramDesc::ProgramDesc() {
auto *block = desc_.mutable_blocks()->Add();
block->set_idx(kRootBlockIndex);
block->set_parent_idx(kNoneBlockIndex);
blocks_.emplace_back(new BlockDescBind(this, block));
blocks_.emplace_back(new BlockDesc(this, block));
}
ProgramDescBind::ProgramDescBind(const ProgramDescBind &o) {
ProgramDesc::ProgramDesc(const ProgramDesc &o) {
desc_ = o.desc_;
for (int i = 0; i < desc_.blocks_size(); ++i) {
auto *block = desc_.mutable_blocks(i);
blocks_.emplace_back(new BlockDescBind(*o.blocks_[i], block, this));
blocks_.emplace_back(new BlockDesc(*o.blocks_[i], block, this));
}
}
ProgramDescBind::ProgramDescBind(const proto::ProgramDesc &desc) {
ProgramDesc::ProgramDesc(const proto::ProgramDesc &desc) {
desc_ = desc;
for (auto &block_desc : *desc_.mutable_blocks()) {
blocks_.emplace_back(new BlockDescBind(this, &block_desc));
blocks_.emplace_back(new BlockDesc(this, &block_desc));
}
}
ProgramDescBind::ProgramDescBind(const std::string &binary_str) {
ProgramDesc::ProgramDesc(const std::string &binary_str) {
PADDLE_ENFORCE(desc_.ParseFromString(binary_str),
"Fail to parse program_desc from binary string.");
for (auto &block_desc : *desc_.mutable_blocks()) {
blocks_.emplace_back(new BlockDescBind(this, &block_desc));
blocks_.emplace_back(new BlockDesc(this, &block_desc));
}
}
......
paddle/framework/program_desc.h
浏览文件 @ 09189732
......@@ -23,23 +23,23 @@ limitations under the License. */
namespace paddle {
namespace framework {
class BlockDescBind;
class BlockDesc;
class ProgramDescBind {
class ProgramDesc {
public:
ProgramDescBind();
ProgramDesc();
explicit ProgramDescBind(const proto::ProgramDesc &desc);
explicit ProgramDesc(const proto::ProgramDesc &desc);
ProgramDescBind(const ProgramDescBind &o);
ProgramDesc(const ProgramDesc &o);
explicit ProgramDescBind(const std::string &binary_str);
explicit ProgramDesc(const std::string &binary_str);
BlockDescBind *AppendBlock(const BlockDescBind &parent);
BlockDesc *AppendBlock(const BlockDesc &parent);
BlockDescBind *MutableBlock(size_t idx) { return blocks_[idx].get(); }
BlockDesc *MutableBlock(size_t idx) { return blocks_[idx].get(); }
const BlockDescBind &Block(size_t idx) const { return *blocks_[idx]; }
const BlockDesc &Block(size_t idx) const { return *blocks_[idx]; }
size_t Size() const { return blocks_.size(); }
......@@ -48,7 +48,7 @@ class ProgramDescBind {
private:
proto::ProgramDesc desc_;
std::vector<std::unique_ptr<BlockDescBind>> blocks_;
std::vector<std::unique_ptr<BlockDesc>> blocks_;
};
} // namespace framework
} // namespace paddle
paddle/framework/program_desc_test.cc
浏览文件 @ 09189732
......@@ -19,7 +19,7 @@
namespace paddle {
namespace framework {
TEST(ProgramDesc, copy_ctor) {
ProgramDescBind program;
ProgramDesc program;
auto* global_block = program.MutableBlock(0);
auto* x = global_block->Var("X");
x->SetType(proto::VarDesc_VarType_LOD_TENSOR);
......@@ -42,12 +42,12 @@ TEST(ProgramDesc, copy_ctor) {
out->SetType(proto::VarDesc_VarType_LOD_TENSOR);
op->SetOutput("Y", {out->Name()});
ProgramDescBind program_copy(program);
ProgramDesc program_copy(program);
auto* global_block_copy = program_copy.MutableBlock(0);
ASSERT_NE(global_block, global_block_copy);
auto assert_same_var = [&](const std::string& name, VarDescBind* var_before) {
auto assert_same_var = [&](const std::string& name, VarDesc* var_before) {
ASSERT_TRUE(global_block_copy->HasVar(name));
auto* copy = global_block_copy->Var(name);
ASSERT_NE(copy, var_before);
......@@ -81,7 +81,7 @@ TEST(ProgramDesc, copy_ctor) {
}
TEST(ProgramDescBind, serialize_and_deserialize) {
ProgramDescBind program_origin;
ProgramDesc program_origin;
auto* global_block = program_origin.MutableBlock(0);
auto* x = global_block->Var("X");
x->SetType(proto::VarDesc_VarType_LOD_TENSOR);
......@@ -107,11 +107,11 @@ TEST(ProgramDescBind, serialize_and_deserialize) {
std::string binary_str;
program_origin.Proto()->SerializeToString(&binary_str);
ProgramDescBind program_restored(binary_str);
ProgramDesc program_restored(binary_str);
auto* global_block_restored = program_restored.MutableBlock(0);
ASSERT_NE(global_block, global_block_restored);
auto assert_same_var = [&](const std::string& name, VarDescBind* var_before) {
auto assert_same_var = [&](const std::string& name, VarDesc* var_before) {
ASSERT_TRUE(global_block_restored->HasVar(name));
auto* restored = global_block_restored->Var(name);
ASSERT_NE(restored, var_before);
......
paddle/framework/prune_test.cc
浏览文件 @ 09189732
......@@ -29,7 +29,7 @@ namespace ops = paddle::operators;
void AddOp(const std::string &type, const f::VariableNameMap &inputs,
const f::VariableNameMap &outputs, f::AttributeMap attrs,
paddle::framework::BlockDescBind *block) {
paddle::framework::BlockDesc *block) {
// insert output
for (auto kv : outputs) {
for (auto v : kv.second) {
......@@ -51,8 +51,8 @@ void AddOp(const std::string &type, const f::VariableNameMap &inputs,
}
TEST(Prune, one_operator) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
AddOp("one_one", {{"input", {"a"}}}, {{"output", {"b"}}}, f::AttributeMap{},
block);
......@@ -69,8 +69,8 @@ TEST(Prune, one_operator) {
}
TEST(Prune, forward) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
AddOp("one_one", {{"input", {"a"}}}, {{"output", {"b"}}}, f::AttributeMap{},
block);
......@@ -92,8 +92,8 @@ TEST(Prune, forward) {
}
TEST(Prune, multi_input_op) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
AddOp("one_one", {{"input", {"a0"}}}, {{"output", {"b0"}}}, f::AttributeMap{},
block);
......@@ -113,8 +113,8 @@ TEST(Prune, multi_input_op) {
}
TEST(Prune, multi_output_op) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
AddOp("one_two", {{"input", {"a"}}}, {{"output", {"b", "c"}}},
f::AttributeMap{}, block);
......@@ -132,8 +132,8 @@ TEST(Prune, multi_output_op) {
}
TEST(Prune, multi_target) {
f::ProgramDescBind program;
f::BlockDescBind *block = program.MutableBlock(0);
f::ProgramDesc program;
f::BlockDesc *block = program.MutableBlock(0);
AddOp("one_two", {{"input", {"a"}}}, {{"output", {"b", "c"}}},
f::AttributeMap{}, block);
......
paddle/framework/type_defs.h
浏览文件 @ 09189732
......@@ -25,11 +25,9 @@
namespace paddle {
namespace framework {
class OperatorBase;
class OpDescBind;
class BlockDescBind;
class BlockDesc;
class OpDesc;
class InferShapeContext;
class BlockDescBind;
class BlockDesc;
using VariableNameMap = std::map<std::string, std::vector<std::string>>;
......@@ -37,7 +35,7 @@ using VariableNameMap = std::map<std::string, std::vector<std::string>>;
using Attribute =
boost::variant<boost::blank, int, float, std::string, std::vector<int>,
std::vector<float>, std::vector<std::string>, bool,
std::vector<bool>, BlockDescBind*>;
std::vector<bool>, BlockDesc*>;
using AttributeMap = std::unordered_map<std::string, Attribute>;
......@@ -45,13 +43,13 @@ using OpCreator = std::function<OperatorBase*(
const std::string& /*type*/, const VariableNameMap& /*inputs*/,
const VariableNameMap& /*outputs*/, const AttributeMap& /*attrs*/)>;
using GradOpMakerFN = std::function<std::vector<std::unique_ptr<OpDescBind>>(
const OpDescBind&, const std::unordered_set<std::string>& /*no_grad_set*/,
using GradOpMakerFN = std::function<std::vector<std::unique_ptr<OpDesc>>(
const OpDesc&, const std::unordered_set<std::string>& /*no_grad_set*/,
std::unordered_map<std::string, std::string>* /*grad_to_var*/,
const std::vector<BlockDescBind*>& grad_block)>;
const std::vector<BlockDesc*>& grad_block)>;
using InferVarTypeFN = std::function<void(const OpDescBind& /*op_desc*/,
BlockDescBind* /*block*/)>;
using InferVarTypeFN =
std::function<void(const OpDesc& /*op_desc*/, BlockDesc* /*block*/)>;
using InferShapeFN = std::function<void(InferShapeContext*)>;
......
paddle/framework/var_desc.cc
浏览文件 @ 09189732
......@@ -18,29 +18,27 @@ limitations under the License. */
namespace paddle {
namespace framework {
proto::VarDesc::VarType VarDescBind::GetType() const { return desc_.type(); }
proto::VarDesc::VarType VarDesc::GetType() const { return desc_.type(); }
void VarDescBind::SetType(proto::VarDesc::VarType type) {
desc_.set_type(type);
}
void VarDesc::SetType(proto::VarDesc::VarType type) { desc_.set_type(type); }
void VarDescBind::SetShape(const std::vector<int64_t> &dims) {
void VarDesc::SetShape(const std::vector<int64_t> &dims) {
VectorToRepeated(dims, mutable_tensor_desc()->mutable_dims());
}
void VarDescBind::SetDataType(proto::DataType data_type) {
void VarDesc::SetDataType(proto::DataType data_type) {
mutable_tensor_desc()->set_data_type(data_type);
}
std::vector<int64_t> VarDescBind::Shape() const {
std::vector<int64_t> VarDesc::Shape() const {
return RepeatedToVector(tensor_desc().dims());
}
proto::DataType VarDescBind::GetDataType() const {
proto::DataType VarDesc::GetDataType() const {
return tensor_desc().data_type();
}
void VarDescBind::SetLoDLevel(int32_t lod_level) {
void VarDesc::SetLoDLevel(int32_t lod_level) {
switch (desc_.type()) {
case proto::VarDesc::LOD_TENSOR:
desc_.mutable_lod_tensor()->set_lod_level(lod_level);
......@@ -54,7 +52,7 @@ void VarDescBind::SetLoDLevel(int32_t lod_level) {
}
}
int32_t VarDescBind::GetLodLevel() const {
int32_t VarDesc::GetLodLevel() const {
switch (desc_.type()) {
case proto::VarDesc::LOD_TENSOR:
return desc_.lod_tensor().lod_level();
......@@ -66,7 +64,7 @@ int32_t VarDescBind::GetLodLevel() const {
}
}
const proto::TensorDesc &VarDescBind::tensor_desc() const {
const proto::TensorDesc &VarDesc::tensor_desc() const {
PADDLE_ENFORCE(desc_.has_type(), "invoke TensorDesc must after set type");
switch (desc_.type()) {
case proto::VarDesc::SELECTED_ROWS:
......@@ -80,7 +78,7 @@ const proto::TensorDesc &VarDescBind::tensor_desc() const {
}
}
proto::TensorDesc *VarDescBind::mutable_tensor_desc() {
proto::TensorDesc *VarDesc::mutable_tensor_desc() {
PADDLE_ENFORCE(desc_.has_type(),
"invoke MutableTensorDesc must after set type");
switch (desc_.type()) {
......
paddle/framework/var_desc.h
浏览文件 @ 09189732
......@@ -53,14 +53,14 @@ inline void VectorToRepeated(const std::vector<bool> &vec,
}
}
class VarDescBind {
class VarDesc {
public:
explicit VarDescBind(const std::string &name) {
explicit VarDesc(const std::string &name) {
desc_.set_name(name);
desc_.set_type(proto::VarDesc::LOD_TENSOR);
}
explicit VarDescBind(const proto::VarDesc &desc) : desc_(desc) {}
explicit VarDesc(const proto::VarDesc &desc) : desc_(desc) {}
proto::VarDesc *Proto() { return &desc_; }
......
paddle/framework/var_type_inference.h
浏览文件 @ 09189732
......@@ -21,8 +21,7 @@ namespace framework {
class VarTypeInference {
public:
virtual ~VarTypeInference() {}
virtual void operator()(const OpDescBind& op_desc,
BlockDescBind* block) const = 0;
virtual void operator()(const OpDesc& op_desc, BlockDesc* block) const = 0;
};
} // namespace framework
......
paddle/framework/var_type_inference_test.cc
浏览文件 @ 09189732
......@@ -33,8 +33,7 @@ class SumOpMaker : public OpProtoAndCheckerMaker {
class SumOpVarTypeInference : public VarTypeInference {
public:
void operator()(const OpDescBind &op_desc,
BlockDescBind *block) const override {
void operator()(const OpDesc &op_desc, BlockDesc *block) const override {
auto &inputs = op_desc.Input("X");
auto default_var_type = proto::VarDesc::SELECTED_ROWS;
......@@ -62,7 +61,7 @@ namespace paddle {
namespace framework {
TEST(InferVarType, sum_op) {
ProgramDescBind prog;
ProgramDesc prog;
auto *op = prog.MutableBlock(0)->AppendOp();
op->SetType("sum");
op->SetInput("X", {"test_a", "test_b", "test_c"});
......@@ -85,7 +84,7 @@ TEST(InferVarType, sum_op) {
}
TEST(InferVarType, sum_op_without_infer_var_type) {
ProgramDescBind prog;
ProgramDesc prog;
auto *op = prog.MutableBlock(0)->AppendOp();
op->SetType("sum_without_infer_var_type");
op->SetInput("X", {"test2_a", "test2_b", "test2_c"});
......
paddle/operators/array_to_lod_tensor_op.cc
浏览文件 @ 09189732
......@@ -149,14 +149,14 @@ class ArrayToLoDTensorGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("lod_tensor_to_array");
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetInput("RankTable", Input("RankTable"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/assign_op.cc
浏览文件 @ 09189732
......@@ -121,12 +121,12 @@ class AssignGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *op = new framework::OpDesc();
op->SetType("assign");
op->SetInput("X", OutputGrad("Out"));
op->SetOutput("Out", InputGrad("X"));
return std::unique_ptr<framework::OpDescBind>(op);
return std::unique_ptr<framework::OpDesc>(op);
}
};
......
paddle/operators/beam_search_decode_op.cc
浏览文件 @ 09189732
......@@ -119,8 +119,8 @@ class BeamSearchDecodeInferShape : public framework::InferShapeBase {
class BeamSearchDecodeInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDescBind& op_desc,
framework::BlockDescBind* block) const override {
void operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const override {
for (auto& o : op_desc.Output("SentenceIds")) {
block->Var(o)->SetType(framework::proto::VarDesc::LOD_TENSOR);
}
......
paddle/operators/cast_op.cc
浏览文件 @ 09189732
......@@ -52,14 +52,14 @@ class CastOpGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto grad = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto grad = new framework::OpDesc();
grad->SetType("cast");
grad->SetInput("X", OutputGrad("Out"));
grad->SetOutput("Out", InputGrad("X"));
grad->SetAttr("out_dtype", GetAttr("in_dtype"));
grad->SetAttr("in_dtype", GetAttr("out_dtype"));
return std::unique_ptr<framework::OpDescBind>(grad);
return std::unique_ptr<framework::OpDesc>(grad);
}
};
......
paddle/operators/conditional_block_op.cc
浏览文件 @ 09189732
......@@ -65,7 +65,7 @@ class ConditionalBlockOp : public ConditionalOp {
scopes->front() = &scope.NewScope();
auto &cur_scope = *scopes->front();
auto *block = Attr<framework::BlockDescBind *>("sub_block");
auto *block = Attr<framework::BlockDesc *>("sub_block");
framework::Executor exec(dev_ctx);
exec.Run(*block->Program(), &cur_scope, block->ID(), false);
}
......@@ -86,7 +86,7 @@ class ConditionalBlockOpProtoMaker : public framework::OpProtoAndCheckerMaker {
"(std::vector<Scope*>) The step scope of conditional block. To "
"unify the conditional block, rnn and while op, the type of "
"scope is std::vector<Scope*>");
AddAttr<framework::BlockDescBind *>(
AddAttr<framework::BlockDesc *>(
"sub_block", "The step block of conditional block operator");
AddComment(R"DOC(Conditional block operator
......@@ -116,7 +116,7 @@ class ConditionalBlockGradOp : public ConditionalOp {
auto &scopes = scope_var->Get<std::vector<framework::Scope *>>();
framework::Scope &cur_scope = *scopes[0];
auto *block = Attr<framework::BlockDescBind *>("sub_block");
auto *block = Attr<framework::BlockDesc *>("sub_block");
framework::Executor exec(dev_ctx);
exec.Run(*block->Program(), &cur_scope, block->ID(), false);
......@@ -170,8 +170,8 @@ class ConditionalBlockGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto grad_op = new framework::OpDesc();
grad_op->SetType("conditional_block_grad");
grad_op->SetInput("X", Input("X"));
grad_op->SetInput("Params", Input("Params"));
......@@ -181,7 +181,7 @@ class ConditionalBlockGradMaker : public framework::SingleGradOpDescMaker {
grad_op->SetOutput(framework::GradVarName("X"), InputGrad("X"));
grad_op->SetOutput(framework::GradVarName("Params"), InputGrad("Params"));
grad_op->SetBlockAttr("sub_block", *this->grad_block_[0]);
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/increment_op.cc
浏览文件 @ 09189732
......@@ -93,13 +93,13 @@ class IncrementGradOpMaker : public framework::SingleGradOpDescMaker {
public:
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("increment");
grad_op->SetInput("X", Output("Out"));
grad_op->SetOutput("Out", Input("X"));
grad_op->SetAttr("step", -boost::get<float>(GetAttr("step")));
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/lod_rank_table_op.cc
浏览文件 @ 09189732
......@@ -63,8 +63,8 @@ class LoDRankTableInferShape : public framework::InferShapeBase {
class LoDRankTableInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDescBind &op_desc,
framework::BlockDescBind *block) const override {
void operator()(const framework::OpDesc &op_desc,
framework::BlockDesc *block) const override {
for (auto &o : op_desc.Output("Out")) {
block->FindRecursiveOrCreateVar(o)->SetType(
framework::proto::VarDesc::LOD_RANK_TABLE);
......
paddle/operators/lod_tensor_to_array_op.cc
浏览文件 @ 09189732
......@@ -127,8 +127,8 @@ class LoDTensorToArrayInferShape : public framework::InferShapeBase {
class LoDTensorToArrayInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDescBind &op_desc,
framework::BlockDescBind *block) const override {
void operator()(const framework::OpDesc &op_desc,
framework::BlockDesc *block) const override {
for (auto &out_var : op_desc.Output("Out")) {
block->Var(out_var)->SetType(framework::proto::VarDesc::LOD_TENSOR_ARRAY);
}
......@@ -140,14 +140,14 @@ class LoDTensorToArrayGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("array_to_lod_tensor");
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetInput("RankTable", Input("RankTable"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/lookup_table_op.cc
浏览文件 @ 09189732
......@@ -108,8 +108,8 @@ class LookupTableOpGrad : public framework::OperatorWithKernel {
class LookupTableOpGradVarTypeInference : public framework::VarTypeInference {
public:
void operator()(const framework::OpDescBind& op_desc,
framework::BlockDescBind* block) const override {
void operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const override {
auto out_var_name = op_desc.Output(framework::GradVarName("W")).front();
auto attr = op_desc.GetAttr("is_sparse");
bool is_sparse = boost::get<bool>(attr);
......
paddle/operators/mean_op.cc
浏览文件 @ 09189732
......@@ -60,13 +60,13 @@ class MeanGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto* grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto* grad_op = new framework::OpDesc();
grad_op->SetType("mean_grad");
grad_op->SetInput("X", Input("X"));
grad_op->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
grad_op->SetOutput(framework::GradVarName("X"), InputGrad("X"));
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/merge_lod_tensor_op.cc
浏览文件 @ 09189732
......@@ -161,15 +161,15 @@ class MergeLoDTensorGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("split_lod_tensor");
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetInput("Mask", Input("Mask"));
grad_op->SetOutput("OutTrue", InputGrad("InTrue"));
grad_op->SetOutput("OutFalse", InputGrad("InFalse"));
grad_op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/minus_op.cc
浏览文件 @ 09189732
......@@ -70,12 +70,11 @@ class MinusGradMaker : public framework::GradOpDescMakerBase {
public:
using framework::GradOpDescMakerBase::GradOpDescMakerBase;
std::vector<std::unique_ptr<framework::OpDescBind>> operator()()
const override {
std::vector<std::unique_ptr<framework::OpDescBind>> ops;
std::vector<std::unique_ptr<framework::OpDesc>> operator()() const override {
std::vector<std::unique_ptr<framework::OpDesc>> ops;
auto x_g = InputGrad("X");
if (!x_g.empty()) {
auto *x_g_op = new framework::OpDescBind();
auto *x_g_op = new framework::OpDesc();
x_g_op->SetType("scale");
x_g_op->SetInput("X", OutputGrad("Out"));
x_g_op->SetOutput("Out", x_g);
......@@ -85,7 +84,7 @@ class MinusGradMaker : public framework::GradOpDescMakerBase {
auto y_g = InputGrad("Y");
if (!y_g.empty()) {
auto *y_g_op = new framework::OpDescBind();
auto *y_g_op = new framework::OpDesc();
y_g_op->SetType("scale");
y_g_op->SetInput("X", OutputGrad("Out"));
y_g_op->SetOutput("Out", y_g);
......
paddle/operators/nccl_op_test.cu.cc
浏览文件 @ 09189732
......@@ -65,7 +65,7 @@ class NCCLTester : public ::testing::Test {
}
void NCCLInitOp() {
std::unique_ptr<f::OpDescBind> op1(new f::OpDescBind);
std::unique_ptr<f::OpDesc> op1(new f::OpDesc);
op1->SetType("ncclInit");
op1->SetOutput("Communicator", {"comm"});
......@@ -81,10 +81,9 @@ class NCCLTester : public ::testing::Test {
}
template <class T>
void PerThreadProgram(int gpu_id, const f::OpDescBind &op_desc,
f::Scope *scope) {
void PerThreadProgram(int gpu_id, const f::OpDesc &op_desc, f::Scope *scope) {
std::unique_lock<std::mutex> lk(mu);
const f::OpDescBind *op1 = &op_desc;
const f::OpDesc *op1 = &op_desc;
p::GPUPlace place(gpu_id);
auto &ctx = dev_ctxs.at(gpu_id);
......@@ -125,7 +124,7 @@ class NCCLTester : public ::testing::Test {
// ncclInitOp with desc
TEST(NCCL, ncclInitOp) {
std::unique_ptr<f::OpDescBind> op_desc(new f::OpDescBind);
std::unique_ptr<f::OpDesc> op_desc(new f::OpDesc);
op_desc->SetType("ncclInit");
op_desc->SetOutput("Communicator", {"x1"});
......@@ -145,7 +144,7 @@ TEST(NCCL, ncclInitOp) {
// ncclAllReduceOp with desc
TEST_F(NCCLTester, ncclAllReduceOp) {
std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
std::unique_ptr<f::OpDesc> op2(new f::OpDesc);
op2->SetType("ncclAllReduce");
op2->SetInput("X", {"st"});
op2->SetInput("Communicator", {"comm"});
......@@ -192,7 +191,7 @@ TEST_F(NCCLTester, ncclAllReduceOp) {
// ncclReduceOp with desc
TEST_F(NCCLTester, ncclReduceOp) {
std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
std::unique_ptr<f::OpDesc> op2(new f::OpDesc);
const int kRoot = 0;
op2->SetType("ncclReduce");
op2->SetInput("X", {"st"});
......@@ -240,7 +239,7 @@ TEST_F(NCCLTester, ncclReduceOp) {
// ncclBcastOp with desc
TEST_F(NCCLTester, ncclBcastOp) {
std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
std::unique_ptr<f::OpDesc> op2(new f::OpDesc);
const int kRoot = 5;
op2->SetType("ncclBcast");
op2->SetInput("X", {"st"});
......
paddle/operators/pad_op.cc
浏览文件 @ 09189732
......@@ -116,14 +116,14 @@ class PadOpGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto* bind = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto* bind = new framework::OpDesc();
bind->SetInput("X", Input("X"));
bind->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
bind->SetOutput(framework::GradVarName("X"), InputGrad("X"));
bind->SetAttrMap(Attrs());
bind->SetType("pad_grad");
return std::unique_ptr<framework::OpDescBind>(bind);
return std::unique_ptr<framework::OpDesc>(bind);
}
};
......
paddle/operators/recurrent_op.cc
浏览文件 @ 09189732
......@@ -234,7 +234,7 @@ class RecurrentOp : public RecurrentBase {
auto reverse = Attr<bool>(kReverse);
framework::Executor executor(dev_ctx);
auto *block = Attr<framework::BlockDescBind *>(kStepBlock);
auto *block = Attr<framework::BlockDesc *>(kStepBlock);
auto *program = block->Program();
for (size_t i = 0; i < seq_len; ++i) {
......@@ -317,7 +317,7 @@ class RecurrentGradOp : public RecurrentBase {
auto reverse = Attr<bool>(kReverse);
framework::Executor executor(dev_ctx);
auto *block = Attr<framework::BlockDescBind *>(kStepBlock);
auto *block = Attr<framework::BlockDesc *>(kStepBlock);
auto *program = block->Program();
for (size_t step_id = 0; step_id < seq_len; ++step_id) {
......@@ -522,8 +522,7 @@ The ex-state means the state value in the ex-timestep or the previous time step
string::Sprintf(
"The state variable names. [%s, %s, %s] must be the same order",
kExStates, kStates, kInitStateGrads));
AddAttr<framework::BlockDescBind *>(kStepBlock,
"The step block inside RNN");
AddAttr<framework::BlockDesc *>(kStepBlock, "The step block inside RNN");
AddAttr<bool>(kReverse, R"DOC(Calculate RNN reversely or not.
By default reverse=False
......@@ -565,8 +564,8 @@ class RecurrentGradOpDescMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
virtual std::unique_ptr<framework::OpDescBind> Apply() const {
auto *grad = new framework::OpDescBind();
virtual std::unique_ptr<framework::OpDesc> Apply() const {
auto *grad = new framework::OpDesc();
grad->SetType("recurrent_grad");
for (auto &input_param : this->InputNames()) {
grad->SetInput(input_param, this->Input(input_param));
......@@ -588,7 +587,7 @@ class RecurrentGradOpDescMaker : public framework::SingleGradOpDescMaker {
grad->SetAttrMap(this->Attrs());
grad->SetBlockAttr(kStepBlock, *grad_block_[0]);
return std::unique_ptr<framework::OpDescBind>(grad);
return std::unique_ptr<framework::OpDesc>(grad);
}
};
......
paddle/operators/scale_op.cc
浏览文件 @ 09189732
......@@ -58,13 +58,13 @@ class ScaleGradMaker : public framework::SingleGradOpDescMaker {
public:
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("scale");
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttr("scale", GetAttr("scale"));
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/shrink_rnn_memory_op.cc
浏览文件 @ 09189732
......@@ -136,14 +136,14 @@ class ShrinkRNNGradOpMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *op = new framework::OpDesc();
op->SetType("shrink_rnn_memory_grad");
op->SetInput("X", Input("X"));
op->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
op->SetOutput(framework::GradVarName("X"), InputGrad("X"));
op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(op);
return std::unique_ptr<framework::OpDesc>(op);
}
};
......
paddle/operators/sign_op.cc
浏览文件 @ 09189732
......@@ -50,13 +50,13 @@ class SignGradMaker : public framework::SingleGradOpDescMaker {
public:
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("scale");
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttr("scale", 0.0f);
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/softmax_with_cross_entropy_op.cc
浏览文件 @ 09189732
......@@ -173,8 +173,8 @@ class SoftmaxGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto* grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto* grad_op = new framework::OpDesc();
grad_op->SetType("softmax_with_cross_entropy_grad");
grad_op->SetInput("Label", Input("Label"));
grad_op->SetInput("Softmax", Output("Softmax"));
......@@ -183,7 +183,7 @@ class SoftmaxGradMaker : public framework::SingleGradOpDescMaker {
grad_op->SetInput(framework::GradVarName("Loss"), OutputGrad("Loss"));
grad_op->SetOutput(framework::GradVarName("Logits"), InputGrad("Logits"));
grad_op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/split_lod_tensor_op.cc
浏览文件 @ 09189732
......@@ -163,8 +163,8 @@ class SplitLoDTensorArrayGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("merge_lod_tensor");
grad_op->SetInput("InTrue", OutputGrad("OutTrue"));
grad_op->SetInput("InFalse", OutputGrad("OutFalse"));
......@@ -172,7 +172,7 @@ class SplitLoDTensorArrayGradMaker : public framework::SingleGradOpDescMaker {
grad_op->SetInput("X", Input("X"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/split_op.cc
浏览文件 @ 09189732
......@@ -108,13 +108,13 @@ class SplitGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto op = new framework::OpDesc();
op->SetType("concat");
op->SetInput("X", OutputGrad("Out"));
op->SetOutput("Out", InputGrad("X"));
op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(op);
return std::unique_ptr<framework::OpDesc>(op);
}
};
......
paddle/operators/sum_op.cc
浏览文件 @ 09189732
......@@ -115,8 +115,8 @@ the LoD information with the first input.
class SumOpVarTypeInference : public framework::VarTypeInference {
public:
void operator()(const framework::OpDescBind& op_desc,
framework::BlockDescBind* block) const override {
void operator()(const framework::OpDesc& op_desc,
framework::BlockDesc* block) const override {
auto& inputs = op_desc.Input("X");
auto var_type = framework::proto::VarDesc::SELECTED_ROWS;
......@@ -169,20 +169,19 @@ class SumGradMaker : public framework::GradOpDescMakerBase {
public:
using framework::GradOpDescMakerBase::GradOpDescMakerBase;
std::vector<std::unique_ptr<framework::OpDescBind>> operator()()
const override {
std::vector<std::unique_ptr<framework::OpDesc>> operator()() const override {
auto x_grads = InputGrad("X");
std::vector<std::unique_ptr<framework::OpDescBind>> grad_ops;
std::vector<std::unique_ptr<framework::OpDesc>> grad_ops;
grad_ops.reserve(x_grads.size());
auto og = OutputGrad("Out");
std::transform(x_grads.begin(), x_grads.end(), std::back_inserter(grad_ops),
[&og](const std::string& x_grad) {
auto* grad_op = new framework::OpDescBind();
auto* grad_op = new framework::OpDesc();
grad_op->SetType("scale");
grad_op->SetInput("X", og);
grad_op->SetOutput("Out", {x_grad});
grad_op->SetAttr("scale", 1.0f);
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
});
return grad_ops;
}
......
paddle/operators/tensor_array_read_write_op.cc
浏览文件 @ 09189732
......@@ -96,8 +96,8 @@ class WriteToArrayInferShape : public framework::InferShapeBase {
class WriteToArrayInferVarType : public framework::VarTypeInference {
public:
void operator()(const framework::OpDescBind &op_desc,
framework::BlockDescBind *block) const override {
void operator()(const framework::OpDesc &op_desc,
framework::BlockDesc *block) const override {
auto x_name = op_desc.Input("X")[0];
auto out_name = op_desc.Output("Out")[0];
VLOG(10) << "Set Variable " << out_name << " as LOD_TENSOR_ARRAY";
......@@ -175,14 +175,14 @@ class WriteToArrayGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("read_from_array");
grad_op->SetInput("I", Input("I"));
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......@@ -191,14 +191,14 @@ class ReadFromArrayGradMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad_op = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad_op = new framework::OpDesc();
grad_op->SetType("write_to_array");
grad_op->SetInput("I", Input("I"));
grad_op->SetInput("X", OutputGrad("Out"));
grad_op->SetOutput("Out", InputGrad("X"));
grad_op->SetAttrMap(Attrs());
return std::unique_ptr<framework::OpDescBind>(grad_op);
return std::unique_ptr<framework::OpDesc>(grad_op);
}
};
......
paddle/operators/while_op.cc
浏览文件 @ 09189732
......@@ -46,7 +46,7 @@ class WhileOp : public framework::OperatorBase {
PADDLE_ENFORCE_EQ(cond.dims(), paddle::framework::make_ddim({1}));
framework::Executor executor(dev_ctx);
auto *block = Attr<framework::BlockDescBind *>(kStepBlock);
auto *block = Attr<framework::BlockDesc *>(kStepBlock);
auto *program = block->Program();
auto step_scopes =
......@@ -82,8 +82,8 @@ class WhileOpMaker : public framework::OpProtoAndCheckerMaker {
"(StepScopeVar) A vector of local scope, which size equals the "
"step number of While Op. The i'th scope storages temporary "
"variables generated in the i'th step.");
AddAttr<framework::BlockDescBind *>(kStepBlock,
"The step block inside WhileOp");
AddAttr<framework::BlockDesc *>(kStepBlock,
"The step block inside WhileOp");
AddComment(R"DOC(
)DOC");
}
......@@ -99,7 +99,7 @@ class WhileGradOp : public framework::OperatorBase {
void Run(const framework::Scope &scope,
const platform::DeviceContext &dev_ctx) const override {
framework::Executor executor(dev_ctx);
auto *block = Attr<framework::BlockDescBind *>(kStepBlock);
auto *block = Attr<framework::BlockDesc *>(kStepBlock);
auto *program = block->Program();
auto *step_scopes =
......@@ -209,8 +209,8 @@ class WhileGradOpDescMaker : public framework::SingleGradOpDescMaker {
using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
protected:
std::unique_ptr<framework::OpDescBind> Apply() const override {
auto *grad = new framework::OpDescBind();
std::unique_ptr<framework::OpDesc> Apply() const override {
auto *grad = new framework::OpDesc();
grad->SetType("while_grad");
grad->SetInput(kParameters, Input(kParameters));
......@@ -279,14 +279,14 @@ class WhileGradOpDescMaker : public framework::SingleGradOpDescMaker {
// while operator could be renamed.
grad->SetAttr("original_output_grad", extra_inputs_list);
return std::unique_ptr<framework::OpDescBind>(grad);
return std::unique_ptr<framework::OpDesc>(grad);
}
};
class WhileGradOpVarTypeInference : public framework::VarTypeInference {
public:
void operator()(const framework::OpDescBind &op_desc,
framework::BlockDescBind *block) const override {
void operator()(const framework::OpDesc &op_desc,
framework::BlockDesc *block) const override {
auto p_names = op_desc.Input(kParameters);
auto pg_names = op_desc.Output(framework::GradVarName(kParameters));
......
paddle/pybind/protobuf.cc
浏览文件 @ 09189732
......@@ -108,21 +108,21 @@ static py::bytes SerializeMessage(T &self) {
// Bind Methods
void BindProgramDesc(py::module &m) {
py::class_<ProgramDescBind>(m, "ProgramDesc", "")
py::class_<ProgramDesc>(m, "ProgramDesc", "")
.def(py::init<>())
.def("__init__",
[](ProgramDescBind &self, const ProgramDescBind &other) {
new (&self) ProgramDescBind(other);
[](ProgramDesc &self, const ProgramDesc &other) {
new (&self) ProgramDesc(other);
})
.def("__init__",
[](ProgramDescBind &self, const py::bytes &binary_str) {
[](ProgramDesc &self, const py::bytes &binary_str) {
std::string str(binary_str);
new (&self) ProgramDescBind(str);
new (&self) ProgramDesc(str);
})
.def("append_block", &ProgramDescBind::AppendBlock,
.def("append_block", &ProgramDesc::AppendBlock,
py::return_value_policy::reference)
.def("append_backward",
[](ProgramDescBind &program_desc, const VarDescBind &target,
[](ProgramDesc &program_desc, const VarDesc &target,
const std::unordered_set<std::string> &no_grad_vars) {
ParamGradInfoMap param_grad_map =
AppendBackward(program_desc, target, no_grad_vars);
......@@ -138,12 +138,12 @@ void BindProgramDesc(py::module &m) {
}
return retv;
})
.def("block", &ProgramDescBind::MutableBlock,
.def("block", &ProgramDesc::MutableBlock,
py::return_value_policy::reference)
.def("num_blocks", &ProgramDescBind::Size)
.def("serialize_to_string", SerializeMessage<ProgramDescBind>)
.def("num_blocks", &ProgramDesc::Size)
.def("serialize_to_string", SerializeMessage<ProgramDesc>)
.def("parse_from_string",
[](ProgramDescBind &program_desc, const std::string &data) {
[](ProgramDesc &program_desc, const std::string &data) {
proto::ProgramDesc *desc = program_desc.Proto();
PADDLE_ENFORCE(desc->ParseFromString(data),
"Fail to parse ProgramDesc from string. This could "
......@@ -152,35 +152,34 @@ void BindProgramDesc(py::module &m) {
}
void BindBlockDesc(py::module &m) {
py::class_<BlockDescBind>(m, "BlockDesc", "")
.def_property_readonly("id", &BlockDescBind::ID)
.def_property_readonly("parent", &BlockDescBind::Parent)
.def("append_op", &BlockDescBind::AppendOp,
py::class_<BlockDesc>(m, "BlockDesc", "")
.def_property_readonly("id", &BlockDesc::ID)
.def_property_readonly("parent", &BlockDesc::Parent)
.def("append_op", &BlockDesc::AppendOp,
py::return_value_policy::reference)
.def("prepend_op", &BlockDescBind::PrependOp,
.def("prepend_op", &BlockDesc::PrependOp,
py::return_value_policy::reference)
.def("var",
[](BlockDescBind &self, py::bytes byte_name) {
[](BlockDesc &self, py::bytes byte_name) {
std::string name = byte_name;
return self.Var(name);
},
py::return_value_policy::reference)
.def("has_var",
[](BlockDescBind &self, py::bytes byte_name) {
[](BlockDesc &self, py::bytes byte_name) {
std::string name = byte_name;
return self.HasVar(name);
})
.def("find_var",
[](BlockDescBind &self, py::bytes byte_name) {
[](BlockDesc &self, py::bytes byte_name) {
std::string name = byte_name;
return self.FindVar(name);
},
py::return_value_policy::reference)
.def("all_vars", &BlockDescBind::AllVars,
py::return_value_policy::reference)
.def("op_size", &BlockDescBind::OpSize)
.def("op", &BlockDescBind::Op, py::return_value_policy::reference)
.def("serialize_to_string", SerializeMessage<BlockDescBind>);
.def("all_vars", &BlockDesc::AllVars, py::return_value_policy::reference)
.def("op_size", &BlockDesc::OpSize)
.def("op", &BlockDesc::Op, py::return_value_policy::reference)
.def("serialize_to_string", SerializeMessage<BlockDesc>);
}
void BindVarDsec(py::module &m) {
......@@ -193,25 +192,25 @@ void BindVarDsec(py::module &m) {
.value("FP32", proto::DataType::FP32)
.value("FP64", proto::DataType::FP64);
py::class_<VarDescBind> var_desc(m, "VarDesc", "");
py::class_<VarDesc> var_desc(m, "VarDesc", "");
var_desc
.def("name",
[](const VarDescBind &self) {
[](const VarDesc &self) {
py::bytes name = self.Name();
return name;
},
py::return_value_policy::reference)
.def("set_shape", &VarDescBind::SetShape)
.def("set_dtype", &VarDescBind::SetDataType)
.def("shape", &VarDescBind::Shape, py::return_value_policy::reference)
.def("dtype", &VarDescBind::GetDataType)
.def("lod_level", &VarDescBind::GetLodLevel)
.def("set_lod_level", &VarDescBind::SetLoDLevel)
.def("type", &VarDescBind::GetType)
.def("set_type", &VarDescBind::SetType)
.def("serialize_to_string", SerializeMessage<VarDescBind>)
.def("persistable", &VarDescBind::Persistable)
.def("set_persistable", &VarDescBind::SetPersistable);
.def("set_shape", &VarDesc::SetShape)
.def("set_dtype", &VarDesc::SetDataType)
.def("shape", &VarDesc::Shape, py::return_value_policy::reference)
.def("dtype", &VarDesc::GetDataType)
.def("lod_level", &VarDesc::GetLodLevel)
.def("set_lod_level", &VarDesc::SetLoDLevel)
.def("type", &VarDesc::GetType)
.def("set_type", &VarDesc::SetType)
.def("serialize_to_string", SerializeMessage<VarDesc>)
.def("persistable", &VarDesc::Persistable)
.def("set_persistable", &VarDesc::SetPersistable);
py::enum_<proto::VarDesc::VarType>(var_desc, "VarType", "")
.value("LOD_TENSOR", proto::VarDesc::LOD_TENSOR)
......@@ -235,26 +234,26 @@ void BindOpDesc(py::module &m) {
.value("BOOLS", proto::AttrType::BOOLEANS)
.value("BLOCK", proto::AttrType::BLOCK);
py::class_<OpDescBind> op_desc(m, "OpDesc", "");
op_desc.def("type", &OpDescBind::Type)
.def("set_type", &OpDescBind::SetType)
.def("input", &OpDescBind::Input)
.def("input_names", &OpDescBind::InputNames)
.def("set_input", &OpDescBind::SetInput)
.def("output", &OpDescBind::Output)
.def("output_names", &OpDescBind::OutputNames)
.def("set_output", &OpDescBind::SetOutput)
.def("has_attr", &OpDescBind::HasAttr)
.def("attr_type", &OpDescBind::GetAttrType)
.def("attr_names", &OpDescBind::AttrNames)
.def("set_attr", &OpDescBind::SetAttr)
.def("attr", &OpDescBind::GetAttr)
.def("set_block_attr", &OpDescBind::SetBlockAttr)
.def("block_attr", &OpDescBind::GetBlockAttr)
.def("check_attrs", &OpDescBind::CheckAttrs)
.def("infer_shape", &OpDescBind::InferShape)
.def("infer_var_type", &OpDescBind::InferVarType)
.def("serialize_to_string", SerializeMessage<OpDescBind>);
py::class_<OpDesc> op_desc(m, "OpDesc", "");
op_desc.def("type", &OpDesc::Type)
.def("set_type", &OpDesc::SetType)
.def("input", &OpDesc::Input)
.def("input_names", &OpDesc::InputNames)
.def("set_input", &OpDesc::SetInput)
.def("output", &OpDesc::Output)
.def("output_names", &OpDesc::OutputNames)
.def("set_output", &OpDesc::SetOutput)
.def("has_attr", &OpDesc::HasAttr)
.def("attr_type", &OpDesc::GetAttrType)
.def("attr_names", &OpDesc::AttrNames)
.def("set_attr", &OpDesc::SetAttr)
.def("attr", &OpDesc::GetAttr)
.def("set_block_attr", &OpDesc::SetBlockAttr)
.def("block_attr", &OpDesc::GetBlockAttr)
.def("check_attrs", &OpDesc::CheckAttrs)
.def("infer_shape", &OpDesc::InferShape)
.def("infer_var_type", &OpDesc::InferVarType)
.def("serialize_to_string", SerializeMessage<OpDesc>);
}
} // namespace pybind
......
paddle/pybind/pybind.cc
浏览文件 @ 09189732
......@@ -266,36 +266,36 @@ All parameter, weight, gradient are variables in Paddle.
return ret_values;
});
m.def("get_grad_op_descs",
[](const OpDescBind &op_desc,
[](const OpDesc &op_desc,
const std::unordered_set<std::string> &no_grad_set,
std::unordered_map<std::string, std::string> &grad_to_var,
const std::vector<BlockDescBind *> &grad_sub_block) {
std::vector<std::unique_ptr<OpDescBind>> grad_op_descs =
const std::vector<BlockDesc *> &grad_sub_block) {
std::vector<std::unique_ptr<OpDesc>> grad_op_descs =
framework::OpInfoMap::Instance()
.Get(op_desc.Type())
.GradOpMaker()(op_desc, no_grad_set, &grad_to_var,
grad_sub_block);
std::vector<OpDescBind *> grad_op_desc_ptrs(grad_op_descs.size());
std::vector<OpDesc *> grad_op_desc_ptrs(grad_op_descs.size());
std::transform(
grad_op_descs.begin(), grad_op_descs.end(),
grad_op_desc_ptrs.begin(),
[](std::unique_ptr<OpDescBind> &p) { return p.release(); });
[](std::unique_ptr<OpDesc> &p) { return p.release(); });
return grad_op_desc_ptrs;
});
m.def("prune", [](const ProgramDescBind &origin,
m.def("prune", [](const ProgramDesc &origin,
const std::vector<std::array<size_t, 2>> &targets) {
ProgramDescBind prog_with_targets(origin);
ProgramDesc prog_with_targets(origin);
for (const auto &t : targets) {
prog_with_targets.MutableBlock(t[0])->Op(t[1])->MarkAsTarget();
}
proto::ProgramDesc pruned_desc;
Prune(*prog_with_targets.Proto(), &pruned_desc);
return new ProgramDescBind(pruned_desc);
return new ProgramDesc(pruned_desc);
});
m.def("inference_optimize", [](ProgramDescBind &origin) {
m.def("inference_optimize", [](ProgramDesc &origin) {
proto::ProgramDesc pruned_desc;
InferenceOptimize(*(origin.Proto()), &pruned_desc);
return new ProgramDescBind(pruned_desc);
return new ProgramDesc(pruned_desc);
});
m.def_submodule(
"var_names",
......
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