diff --git a/paddle/framework/backward.cc b/paddle/framework/backward.cc index c226e4e3d2a58d1a647e204c4cd26f4eb6bcd968..9d30887224fe0020ff5665f362e7403bf5c724ee 100644 --- a/paddle/framework/backward.cc +++ b/paddle/framework/backward.cc @@ -15,6 +15,8 @@ #include "paddle/framework/backward.h" #include +#include + #include "paddle/framework/op_registry.h" #include "paddle/operators/net_op.h" #include "paddle/operators/recurrent_op.h" @@ -43,11 +45,11 @@ static bool AllInSet( return all_in_set; } -static std::shared_ptr NOP() { - auto net_op = std::make_shared(); +static std::unique_ptr NOP() { + auto net_op = new operators::NetOp(); net_op->SetType("@NOP@"); net_op->CompleteAddOp(); - return net_op; + return std::unique_ptr(net_op); } // Get backward operator from a forward operator, a recursive implementation. @@ -62,11 +64,7 @@ static std::shared_ptr NOP() { // operator, in a complex situation, it maybe a NetOp. // // See Backward.h for details -static std::shared_ptr BackwardRecursive( - const OperatorBase& forwardOp, - std::unordered_set& no_grad_names, size_t& uniq_id); - -std::shared_ptr BackwardRecursive( +static std::unique_ptr BackwardRecursive( const OperatorBase& forwardOp, std::unordered_set& no_grad_names, size_t& uniq_id) { // If all input gradients of forwarding operator do not need to calculate, @@ -91,7 +89,7 @@ std::shared_ptr BackwardRecursive( } // Returned gradient network - auto net = std::make_shared(); + auto net = std::unique_ptr(new operators::NetOp()); if (forwardOp.IsNetOp()) { // Because forwardOp is a net op, it can static_cast. @@ -105,14 +103,14 @@ std::shared_ptr BackwardRecursive( // reversely travel forwardNet and collect all duplicate outputs. for (auto it = forwardNet.ops_.rbegin(); it != forwardNet.ops_.rend(); ++it, ++local_op_id) { - auto fwd = *it; + auto& fwd = *it; auto bwd = BackwardRecursive(*fwd, no_grad_names, uniq_id); - net->AddOp(bwd); ForEachVarName(bwd->Outputs(), [&dup_output_ops, local_op_id](const std::string& out) { dup_output_ops[out].emplace_back(local_op_id); return false; }); + net->AddOp(std::move(bwd)); } // Get unique ID for this method. auto uid = uniq_id++; @@ -122,7 +120,7 @@ std::shared_ptr BackwardRecursive( // to handle this case. For each duplicate output, rename it to an alias // (original name with a offset), append an `add` op for its operator, // and finally sum all the alias variable to the final output variable y. - using Pos = std::pair>; + using Pos = std::pair>; std::list insert_position; for (auto& dup_output_op : dup_output_ops) { const std::string& name = dup_output_op.first; @@ -150,13 +148,13 @@ std::shared_ptr BackwardRecursive( [](const Pos& l, const Pos& r) { return l.first > r.first; }); for (auto& pos : insert_position) { - net->InsertOp(pos.first + 1, pos.second); + net->InsertOp(pos.first + 1, std::move(pos.second)); } } else { - std::shared_ptr grad_op = OpRegistry::CreateGradOp(forwardOp); + std::unique_ptr grad_op(OpRegistry::CreateGradOp(forwardOp)); - ForEachVarName(grad_op->Inputs(), [&no_grad_names, &net, - grad_op](const std::string& grad_input) { + ForEachVarName(grad_op->Inputs(), [&no_grad_names, &net, &grad_op]( + const std::string& grad_input) { if (no_grad_names.count(grad_input)) { // +1 for \0 std::string prefix = grad_input.substr( @@ -190,23 +188,23 @@ std::shared_ptr BackwardRecursive( const auto& stepnet_op = *static_cast(&rnnop.stepnet()); // create stepnet's gradient op - auto grad_stepnet = BackwardRecursive(stepnet_op, no_grad_names, uniq_id); rnn_grad_op->set_stepnet( - std::static_pointer_cast(grad_stepnet)); + BackwardRecursive(stepnet_op, no_grad_names, uniq_id)); } if (net->ops_.empty()) { // Current no aux op is added to network return grad_op; } - net->AddOp(grad_op); + net->AddOp(std::move(grad_op)); } net->SetType("@GENERATED_BACKWARD@"); net->CompleteAddOp(); - return net; -} // namespace framework + return std::unique_ptr( + static_cast(net.release())); +} // See header for comments -std::shared_ptr Backward( +std::unique_ptr Backward( const OperatorBase& forwardOp, const std::unordered_set& no_grad_vars) { std::unordered_set no_grad_names; diff --git a/paddle/framework/backward.h b/paddle/framework/backward.h index c181919dc165cf0b49362f85e22ceb4131bbd387..1ecf69881b3126c2904920b9f4b77bfcccc9cf86 100644 --- a/paddle/framework/backward.h +++ b/paddle/framework/backward.h @@ -20,7 +20,7 @@ namespace framework { // Create the backward operator from a forward operator. // TODO(yuyang18): Add more API reference comment. -extern std::shared_ptr Backward( +extern std::unique_ptr Backward( const OperatorBase& forwardOp, const std::unordered_set& no_grad_vars); } // namespace framework diff --git a/paddle/framework/backward_test.cc b/paddle/framework/backward_test.cc index d942604bf05998ab9e1ee147b28586e7e4e9777d..1003b1ccd83c85c54f07c8d2b84f993203408941 100644 --- a/paddle/framework/backward_test.cc +++ b/paddle/framework/backward_test.cc @@ -180,8 +180,7 @@ TEST(Backward, simple_op_not_need_grad) { auto no_input_gop = f::Backward(*fwd, {"x", "b"}); ASSERT_NE(no_input_gop, nullptr); ASSERT_TRUE(no_input_gop->IsNetOp()); - ASSERT_EQ(0UL, - std::static_pointer_cast(no_input_gop)->ops_.size()); + ASSERT_EQ(0UL, static_cast(no_input_gop.get())->ops_.size()); } TEST(Backward, net_fc_backward_normal) { diff --git a/paddle/framework/op_registry.cc b/paddle/framework/op_registry.cc index f801f970f2576452dfa440af78443edf7cfd6be0..8eae86e9605da74cdc37caeb9569e7500aac2a63 100644 --- a/paddle/framework/op_registry.cc +++ b/paddle/framework/op_registry.cc @@ -19,7 +19,7 @@ limitations under the License. */ namespace paddle { namespace framework { -std::shared_ptr OpRegistry::CreateOp(const std::string& type, +std::unique_ptr OpRegistry::CreateOp(const std::string& type, const VarNameMap& inputs, const VarNameMap& outputs, AttributeMap attrs) { @@ -28,10 +28,10 @@ std::shared_ptr OpRegistry::CreateOp(const std::string& type, "Operator '%s' has not been registered.", type); it->second.checker_->Check(attrs); auto op = it->second.creator_(type, inputs, outputs, attrs); - return std::shared_ptr(op); + return std::unique_ptr(op); } -std::shared_ptr OpRegistry::CreateOp(const OpDesc& op_desc) { +std::unique_ptr OpRegistry::CreateOp(const OpDesc& op_desc) { VarNameMap inputs = ConvertOpDescVarsToVarNameMap(op_desc.inputs()); VarNameMap outputs = ConvertOpDescVarsToVarNameMap(op_desc.outputs()); AttributeMap attrs; @@ -55,10 +55,9 @@ OperatorBase::VarNameMap OpRegistry::ConvertOpDescVarsToVarNameMap( return ret_val; } -std::shared_ptr OpRegistry::CreateGradOp(const OperatorBase& op) { +std::unique_ptr OpRegistry::CreateGradOp(const OperatorBase& op) { PADDLE_ENFORCE(!op.IsNetOp(), "Use framework::Backward to get backward ops"); - std::shared_ptr grad_op(BuildGradOp(&op)); - return grad_op; + return std::unique_ptr(BuildGradOp(&op)); } } // namespace framework diff --git a/paddle/framework/op_registry.h b/paddle/framework/op_registry.h index a76a4d60b4107dfa3b2a3cea09a443d7b136bcdc..4c2d13d639005d2d2710c19f63988333d89bce13 100644 --- a/paddle/framework/op_registry.h +++ b/paddle/framework/op_registry.h @@ -77,17 +77,17 @@ class OpRegistry { } } - static std::shared_ptr CreateOp(const std::string& type, + static std::unique_ptr CreateOp(const std::string& type, const VarNameMap& inputs, const VarNameMap& outputs, AttributeMap attrs); - static std::shared_ptr CreateOp(const OpDesc& op_desc); + static std::unique_ptr CreateOp(const OpDesc& op_desc); static VarNameMap ConvertOpDescVarsToVarNameMap( const google::protobuf::RepeatedPtrField& op_desc_vars); - static std::shared_ptr CreateGradOp(const OperatorBase& op); + static std::unique_ptr CreateGradOp(const OperatorBase& op); static std::unordered_map& op_info_map() { static std::unordered_map op_info_map_; diff --git a/paddle/framework/op_registry_test.cc b/paddle/framework/op_registry_test.cc index 1a85d568350dc04ca1df28129de19cd45b5204b8..50c45919c53af22665feeeebe753da283ded2b0c 100644 --- a/paddle/framework/op_registry_test.cc +++ b/paddle/framework/op_registry_test.cc @@ -76,8 +76,7 @@ TEST(OpRegistry, CreateOp) { attr->set_type(paddle::framework::AttrType::FLOAT); attr->set_f(scale); - std::shared_ptr op = - paddle::framework::OpRegistry::CreateOp(op_desc); + auto op = paddle::framework::OpRegistry::CreateOp(op_desc); paddle::framework::Scope scope; paddle::platform::CPUDeviceContext dev_ctx; op->Run(scope, dev_ctx); @@ -118,8 +117,7 @@ TEST(OpRegistry, DefaultValue) { ASSERT_TRUE(op_desc.IsInitialized()); - std::shared_ptr op = - paddle::framework::OpRegistry::CreateOp(op_desc); + auto op = paddle::framework::OpRegistry::CreateOp(op_desc); paddle::framework::Scope scope; paddle::platform::CPUDeviceContext dev_ctx; op->Run(scope, dev_ctx); diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index fe0c87bc570825014222807cb90a3bb341b44e8e..f0114b9e4908d65b3fddb493230777f9e500b4e1 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -48,29 +48,6 @@ namespace framework { using Tensor = framework::Tensor; -template -void ExposeOperator(ClassType &m) { - m.def("infer_shape", &ClassType::type::InferShape) - .def("run", &ClassType::type::Run) - .def("type", - [](const typename ClassType::type &op) -> std::string { - return op.Type(); - }) - .def("outputs", - [](const typename ClassType::type &op) - -> std::map> { - return op.Outputs(); - }) - .def("inputs", - [](const typename ClassType::type &op) { return op.Inputs(); }) - .def("__str__", &ClassType::type::DebugString) - .def("no_intermediate_outputs", - [](const typename ClassType::type &op) { - return op.OutputVars(false); - }) - .def("support_gpu", &ClassType::type::SupportGPU); -} - static size_t UniqueIntegerGenerator() { static std::atomic generator; return generator.fetch_add(1); @@ -207,75 +184,69 @@ All parameter, weight, gradient are variables in Paddle. .def(py::init<>()) .def("__str__", string::to_string); - py::class_> operator_base( - m, "Operator"); - - operator_base.def_static("create", [](py::bytes protobin) { - OpDesc desc; - PADDLE_ENFORCE(desc.ParsePartialFromString(protobin), - "Cannot parse user input to OpDesc"); - PADDLE_ENFORCE(desc.IsInitialized(), - "User OpDesc is not initialized, reason %s", - desc.InitializationErrorString()); - return OpRegistry::CreateOp(desc); - }); - - operator_base.def("backward", - [](const OperatorBase &forwardOp, - const std::unordered_set &no_grad_vars) { - return Backward(forwardOp, no_grad_vars); - }); - - ExposeOperator(operator_base); - - py::class_> net(m, "Net"); - - net.def_static("create", - []() -> std::shared_ptr { - auto retv = std::make_shared(); - retv->SetType("plain_net"); - return retv; - }) - .def("add_op", &operators::NetOp::AddOp) - .def("add_op", - [](operators::NetOp &self, - const std::shared_ptr &net) -> void { - self.AddOp(std::static_pointer_cast(net)); - }) - .def("add_op", - [](operators::NetOp &self, - const std::shared_ptr &rnn) -> void { - self.AddOp(std::static_pointer_cast(rnn)); + py::class_(m, "Operator") + .def_static("create", + [](py::bytes protobin) { + OpDesc desc; + PADDLE_ENFORCE(desc.ParsePartialFromString(protobin), + "Cannot parse user input to OpDesc"); + PADDLE_ENFORCE(desc.IsInitialized(), + "User OpDesc is not initialized, reason %s", + desc.InitializationErrorString()); + return OpRegistry::CreateOp(desc); + }) + .def("backward", + [](const OperatorBase &forwardOp, + const std::unordered_set &no_grad_vars) { + return Backward(forwardOp, no_grad_vars).release(); }) + .def("infer_shape", &OperatorBase::InferShape) + .def("run", &OperatorBase::Run) + .def("type", + [](const OperatorBase &op) -> std::string { return op.Type(); }) + .def("outputs", + [](const OperatorBase &op) + -> std::map> { + return op.Outputs(); + }) + .def("inputs", [](const OperatorBase &op) { return op.Inputs(); }) + .def("__str__", &OperatorBase::DebugString) + .def("no_intermediate_outputs", + [](const OperatorBase &op) { return op.OutputVars(false); }) + .def("support_gpu", &OperatorBase::SupportGPU); + + py::class_(m, "Net") + .def_static("create", + []() -> operators::NetOp * { + auto *retv = new operators::NetOp; + retv->SetType("plain_net"); + return retv; + }) + .def("add_op", [](operators::NetOp &self, + const OperatorBase &op) { self.AddOp(op); }) .def("complete_add_op", &operators::NetOp::CompleteAddOp) .def("complete_add_op", [](std::shared_ptr &self) { self->CompleteAddOp(); }); - ExposeOperator(net); - // recurrent_op - py::class_> - rnn(m, "RecurrentOp"); - - rnn.def_static( - "create", - [](py::bytes protobin) -> std::shared_ptr { - OpDesc desc; - PADDLE_ENFORCE(desc.ParsePartialFromString(protobin), - "Cannot parse user input to OpDesc"); - PADDLE_ENFORCE(desc.IsInitialized(), - "User OpDesc is not initialized, reason %s", - desc.InitializationErrorString()); - auto rnn_op = OpRegistry::CreateOp(desc); - return std::dynamic_pointer_cast(rnn_op); - }) - .def("set_stepnet", - [](operators::RecurrentOp &self, - const std::shared_ptr &net) -> void { - self.set_stepnet(net); - }); - ExposeOperator(rnn); + py::class_(m, "RecurrentOp") + .def_static( + "create", + [](py::bytes protobin) -> operators::RecurrentOp * { + OpDesc desc; + PADDLE_ENFORCE(desc.ParsePartialFromString(protobin), + "Cannot parse user input to OpDesc"); + PADDLE_ENFORCE(desc.IsInitialized(), + "User OpDesc is not initialized, reason %s", + desc.InitializationErrorString()); + auto rnn_op = OpRegistry::CreateOp(desc); + return static_cast(rnn_op.release()); + }) + .def("set_stepnet", [](operators::RecurrentOp &self, + const operators::NetOp &net) -> void { + self.set_stepnet(net.Clone()); + }); m.def("unique_integer", UniqueIntegerGenerator); diff --git a/paddle/operators/net_op.h b/paddle/operators/net_op.h index 743f0e67dbeaab2de97a6cf635aad0ee90b2cef1..885ac6eeca65998dea62c1db40b9261cceb97805 100644 --- a/paddle/operators/net_op.h +++ b/paddle/operators/net_op.h @@ -41,15 +41,13 @@ class NetOp : public framework::OperatorBase { NetOp(const std::string& type, const VarNameMap& inputs, const VarNameMap& outputs, const framework::AttributeMap& attrs); - NetOp(const NetOp& o) - : framework::OperatorBase( - static_cast(o)) { + NetOp(const NetOp& o) : framework::OperatorBase(o.type_, {}, {}, o.attrs_) { this->ops_.reserve(o.ops_.size()); - std::transform(o.ops_.begin(), o.ops_.end(), std::back_inserter(this->ops_), - [](const std::shared_ptr& op) - -> std::shared_ptr { - return std::shared_ptr(op->Clone()); - }); + std::transform( + o.ops_.begin(), o.ops_.end(), std::back_inserter(this->ops_), + [](const std::unique_ptr& op) { + return std::unique_ptr(op->Clone()); + }); this->CompleteAddOp(); } @@ -86,21 +84,27 @@ class NetOp : public framework::OperatorBase { return true; } + void AddOp(const framework::OperatorBase& op) { AddOp(op.Clone()); } + /** * @brief Add an operator by ptr */ - void AddOp(const std::shared_ptr& op) { + void AddOp(std::unique_ptr op) { PADDLE_ENFORCE(!add_op_done_, "Cannot AddOp when this network is sealed"); PADDLE_ENFORCE_NOT_NULL(op, "Cannot Insert Null op"); - ops_.push_back(op); + ops_.push_back(std::move(op)); } - void InsertOp(size_t pos, const std::shared_ptr& op) { + void InsertOp(size_t pos, std::unique_ptr op) { PADDLE_ENFORCE(!add_op_done_, "Cannot InsertOp when this network is sealed"); PADDLE_ENFORCE_NOT_NULL(op, "Cannot Insert Null op"); PADDLE_ENFORCE_LE(pos, ops_.size(), "Out of range"); - ops_.insert(ops_.begin() + pos, op); + ops_.insert(ops_.begin() + pos, std::move(op)); + } + + void InsertOp(size_t pos, const framework::OperatorBase& op) { + InsertOp(pos, op.Clone()); } void CompleteAddOp(bool calculate = true); @@ -112,7 +116,7 @@ class NetOp : public framework::OperatorBase { std::unique_ptr Clone() const override; - std::vector> ops_; + std::vector> ops_; private: bool add_op_done_{false}; diff --git a/paddle/operators/net_op_test.cc b/paddle/operators/net_op_test.cc index e28d4df6a570968205851c2e5b630a14c0492535..e9598610c0a74e08a613a397109ad65994821498 100644 --- a/paddle/operators/net_op_test.cc +++ b/paddle/operators/net_op_test.cc @@ -38,15 +38,12 @@ TEST(OpKernel, all) { auto net = std::make_shared(); ASSERT_NE(net, nullptr); - auto op1 = std::shared_ptr( + net->AddOp(std::unique_ptr( new TestOp("test", {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}}, - {{"Out", {"y"}}}, {})); - net->AddOp(op1); - - auto op2 = std::shared_ptr( + {{"Out", {"y"}}}, {}))); + net->AddOp(std::unique_ptr( new TestOp("test", {{"X", {"y"}}, {"W", {"w2"}}, {"b", {"b2"}}}, - {{"Out", {"z"}}}, {})); - net->AddOp(op2); + {{"Out", {"z"}}}, {}))); net->CompleteAddOp(); AssertSameVectorWithoutOrder({"x", "w1", "b1", "w2", "b2"}, @@ -61,21 +58,21 @@ TEST(OpKernel, all) { TEST(NetOp, insert_op) { NetOp net; - auto op1 = std::shared_ptr( + auto op1 = std::unique_ptr( new framework::NOP("empty", {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}}, {{"Out", {"y"}}}, {})); - net.AddOp(op1); - net.InsertOp(0, op1); + net.AddOp(*op1); + net.InsertOp(0, *op1); ASSERT_EQ(2UL, net.ops_.size()); - net.InsertOp(2, op1); + net.InsertOp(2, std::move(op1)); ASSERT_EQ(3UL, net.ops_.size()); } TEST(NetOp, Clone) { NetOp net; net.AddOp( - std::shared_ptr(new framework::NOP{"empty", {}, {}, {}})); - net.AddOp(std::shared_ptr( + std::unique_ptr(new framework::NOP{"empty", {}, {}, {}})); + net.AddOp(std::unique_ptr( new framework::NOP{"empty2", {}, {}, {}})); net.CompleteAddOp(true); auto new_net_op = net.Clone(); diff --git a/paddle/operators/recurrent_op.h b/paddle/operators/recurrent_op.h index 1d8a6973955cf0b4ab372412fbb5428ff2622a0a..bcfa817de8242153b164fa091309f19a6ad8a246 100644 --- a/paddle/operators/recurrent_op.h +++ b/paddle/operators/recurrent_op.h @@ -34,7 +34,8 @@ class RecurrentAlgorithm { void Run(const framework::Scope& scope, const platform::DeviceContext& dev_ctx) const; - void Init(rnn::Argument* arg, std::shared_ptr* stepnet) { + void Init(rnn::Argument* arg, + std::unique_ptr* stepnet) { PADDLE_ENFORCE_NOT_NULL(stepnet, "stepnet should be set before."); arg_ = arg; stepnet_ = stepnet; @@ -63,7 +64,7 @@ class RecurrentAlgorithm { void InitMemories(framework::Scope* step_scopes, bool infer_shape_mode) const; private: - std::shared_ptr* stepnet_; + std::unique_ptr* stepnet_; rnn::Argument* arg_; mutable size_t seq_len_; }; @@ -80,7 +81,8 @@ class RecurrentGradientAlgorithm { * operator. */ public: - void Init(rnn::Argument* arg, std::shared_ptr* stepnet) { + void Init(rnn::Argument* arg, + std::unique_ptr* stepnet) { PADDLE_ENFORCE_NOT_NULL(stepnet, "stepnet should be set before."); arg_ = std::move(arg); stepnet_ = stepnet; @@ -107,7 +109,7 @@ class RecurrentGradientAlgorithm { private: rnn::Argument* arg_; mutable size_t seq_len_; - std::shared_ptr* stepnet_; + std::unique_ptr* stepnet_; }; class RecurrentOp : public framework::OperatorBase { @@ -133,15 +135,17 @@ class RecurrentOp : public framework::OperatorBase { alg_.Run(scope, dev_ctx); } - void set_stepnet(std::shared_ptr net) { stepnet_ = net; } - const NetOp& stepnet() const { return *stepnet_; } + void set_stepnet(std::unique_ptr net) { + stepnet_ = std::move(net); + } + const OperatorBase& stepnet() const { return *stepnet_; } static const rnn::ArgumentName kArgName; private: RecurrentAlgorithm alg_; rnn::Argument arg_; - std::shared_ptr stepnet_; + std::unique_ptr stepnet_; }; class RecurrentGradientOp : public framework::OperatorBase { @@ -171,12 +175,14 @@ class RecurrentGradientOp : public framework::OperatorBase { static const rnn::ArgumentName kArgName; - void set_stepnet(const std::shared_ptr& net) { stepnet_ = net; } - const NetOp& stepnet() const { return *stepnet_; } + void set_stepnet(std::unique_ptr net) { + stepnet_ = std::move(net); + } + const OperatorBase& stepnet() const { return *stepnet_; } private: RecurrentGradientAlgorithm alg_; - std::shared_ptr stepnet_; + std::unique_ptr stepnet_; rnn::Argument arg_; }; diff --git a/python/paddle/v2/framework/tests/gradient_checker.py b/python/paddle/v2/framework/tests/gradient_checker.py index 501cf6110ff745b8a6022b463bc9cc3a70145c60..831c0f0f2a9096cd78ae0a0ffd9b515110c6fa06 100644 --- a/python/paddle/v2/framework/tests/gradient_checker.py +++ b/python/paddle/v2/framework/tests/gradient_checker.py @@ -165,7 +165,6 @@ class GradientChecker(unittest.TestCase): for no_grad in no_grad_set: if no_grad not in in_names: raise ValueError("no_grad should be in in_names") - backward_op = core.Operator.backward(forward_op, no_grad_set) bwd_outputs = backward_op.outputs()