tensor-tang
7 years ago
commit
f1f8327c31
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# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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if(APPLE)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-error=pessimizing-move")
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endif(APPLE)
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cc_library(tape_variable SRCS variable.cc DEPS ${FLUID_CORE_MODULES} device_context framework_proto proto_desc operator)
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cc_library(tape SRCS tape.cc DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB} tape_variable)
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cc_test(test_tape
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SRCS test_tape.cc
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DEPS tape tape_variable)
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <string>
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#include "paddle/contrib/tape/tape.h"
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#include "paddle/contrib/tape/variable.h"
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#include "paddle/fluid/framework/type_defs.h"
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namespace paddle {
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namespace tape {
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class Function {};
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class Fill {
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public:
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Fill(const std::string &initializer, const framework::AttributeMap &attrs)
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: initializer_(initializer), attrs_(attrs) {}
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void operator()(VariableHandle var) {
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get_global_tape().AddOp(initializer_, {}, {{"Out", {var}}}, attrs_);
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}
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private:
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const std::string initializer_;
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const framework::AttributeMap attrs_;
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};
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class Mean {
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public:
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VariableHandle operator()(VariableHandle var) {
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VariableHandle out(new Variable("mean"));
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get_global_tape().AddOp("mean", {{"X", {var}}}, {{"Out", {out}}}, {});
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return out;
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}
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};
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class Linear {
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public:
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Linear(int in_dim, int out_dim, const std::string &act)
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: w_(new Variable("LinearWeight")),
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b_(new Variable("LinearBias")),
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act_(act) {
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Tape init_tape;
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std::string initializer = "fill_constant";
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framework::AttributeMap attrs;
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attrs["dtype"] = paddle::framework::proto::VarType::Type::VarType_Type_FP32;
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attrs["shape"] = std::vector<int>{in_dim, out_dim};
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attrs["value"] = 1.0f;
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init_tape.AddOp(initializer, {}, {{"Out", {w_}}}, attrs);
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attrs["dtype"] = paddle::framework::proto::VarType::Type::VarType_Type_FP32;
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attrs["shape"] = std::vector<int>{out_dim};
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attrs["value"] = 1.0f;
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init_tape.AddOp(initializer, {}, {{"Out", {b_}}}, attrs);
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init_tape.Forward();
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}
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VariableHandle operator()(VariableHandle input) {
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VariableHandle pre_bias(new Variable("linear"));
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get_global_tape().AddOp("mul",
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{{"X", {input}}, {"Y", {w_}}},
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{{"Out", {pre_bias}}},
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{{"x_num_col_dims", 1}, {"y_num_col_dims", 1}});
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VariableHandle pre_act(new Variable("linear"));
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get_global_tape().AddOp("elementwise_add",
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{{"X", {pre_bias}}, {"Y", {b_}}},
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{{"Out", {pre_act}}},
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{{"axis", 1}});
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VariableHandle post_act(new Variable("linear"));
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get_global_tape().AddOp(
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act_, {{"X", {pre_act}}}, {{"Out", {post_act}}}, {});
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return post_act;
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}
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std::vector<VariableHandle> Params() { return {w_, b_}; }
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private:
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VariableHandle w_;
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VariableHandle b_;
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std::string act_;
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};
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class SGD {
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public:
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SGD(float learning_rate) : learning_rate_(new Variable("sgd")) {
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Tape init_tape;
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std::string initializer = "fill_constant";
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framework::AttributeMap attrs;
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attrs["dtype"] = paddle::framework::proto::VarType::Type::VarType_Type_FP32;
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attrs["shape"] = std::vector<int>{1};
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attrs["value"] = learning_rate;
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init_tape.AddOp(initializer, {}, {{"Out", {learning_rate_}}}, attrs);
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init_tape.Forward();
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}
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void operator()(VariableHandle input) {
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PADDLE_ENFORCE(get_global_tape().HasBeenBackwarded(),
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"optimization must happen after the backward");
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Tape temp_tape;
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temp_tape.AddOp("sgd",
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{{"Param", {input}},
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{"LearningRate", {learning_rate_}},
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{"Grad", {input->Grad()}}},
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{{"ParamOut", {input}}},
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{});
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temp_tape.Forward();
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}
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private:
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VariableHandle learning_rate_;
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};
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}
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}
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <map>
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#include <memory>
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#include <string>
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#include <vector>
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#include "paddle/contrib/tape/variable.h"
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namespace paddle {
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namespace tape {
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using VariableHandleMap = std::map<std::string, std::vector<VariableHandle>>;
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struct OpHandle {
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OpHandle(const std::string &type,
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const VariableHandleMap &in_vars,
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const VariableHandleMap &out_vars,
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const framework::AttributeMap &attrs)
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: type_(type), inputs_(in_vars), outputs_(out_vars), attrs_(attrs) {}
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std::string type_;
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VariableHandleMap inputs_;
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VariableHandleMap outputs_;
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framework::AttributeMap attrs_;
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};
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class Tape {
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public:
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void AddOp(const std::string &type,
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const VariableHandleMap &in_vars,
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VariableHandleMap out_vars,
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const framework::AttributeMap &attrs);
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void Forward();
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void Backward(VariableHandle target);
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bool HasBeenBackwarded() { return has_been_backwarded_; }
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private:
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bool has_been_backwarded_ = false;
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size_t current_position_ = 0;
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std::vector<OpHandle> tape_;
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std::shared_ptr<Tape> backward_tape_;
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};
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Tape &get_global_tape();
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void reset_global_tape();
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}
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}
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "gtest/gtest.h"
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#include "paddle/contrib/tape/function.h"
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using namespace paddle::tape;
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TEST(Tape, TestMLP) {
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LOG(INFO) << "TestMLP";
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Linear linear1(3, 3, "relu");
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Linear linear2(3, 3, "relu");
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Mean mean;
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SGD sgd(0.001);
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std::string initializer = "fill_constant";
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paddle::framework::AttributeMap attrs;
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attrs["dtype"] = paddle::framework::proto::VarType::Type::VarType_Type_FP32;
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attrs["shape"] = std::vector<int>{3, 3};
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attrs["value"] = 1.0f;
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Fill filler(initializer, attrs);
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for (int i = 0; i < 2; ++i) {
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reset_global_tape();
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VariableHandle input(new Variable("input"));
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filler(input);
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auto loss = mean(linear2(linear1(input)));
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get_global_tape().Backward(loss);
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for (auto w : linear1.Params()) {
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sgd(w);
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}
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for (auto w : linear2.Params()) {
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sgd(w);
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}
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}
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}
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int main(int argc, char** argv) {
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std::vector<paddle::platform::Place> places;
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places.emplace_back(paddle::platform::CPUPlace());
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paddle::platform::DeviceContextPool::Init(places);
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testing::InitGoogleTest(&argc, argv);
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return RUN_ALL_TESTS();
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}
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@ -1,85 +0,0 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <memory>
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#include "paddle/fluid/framework/operator.h" // framework::kGradVarSuffix
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/framework/variable.h"
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namespace paddle {
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namespace tape {
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class Variable;
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using VariableHandle = std::shared_ptr<Variable>;
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/*
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* Combination of
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* framework::VarDesc desc_;
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* framework::Variable var_;
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*/
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class Variable {
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public:
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Variable(const std::string pre_fix)
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: desc_(pre_fix + std::to_string(count())) {}
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Variable(const std::string pre_fix, bool is_grad)
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: desc_(pre_fix + (is_grad ? framework::kGradVarSuffix
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: std::to_string(count()))) {}
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~Variable() { LOG(INFO) << "Deleting " << Name(); }
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// Instantiate LoDTensor/SelectedRow
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void InitializeVariable();
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VariableHandle Grad() {
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if (grad_.expired()) {
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VariableHandle new_grad(new Variable(desc_.Name(), true));
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grad_ = new_grad;
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return new_grad;
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} else {
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return VariableHandle(grad_);
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}
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}
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// Stochastic Gradient Descent with Momentum
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// VariableHandle Momentum ();
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// void init(const std::string& initializer,
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// const framework::AttributeMap& attrs);
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// void value() {};
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const framework::VarDesc& Desc() const { return desc_; }
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framework::VarDesc* MutableDesc() { return &desc_; }
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// TODO(tonyyang-svail): No need to expose name
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std::string Name() const { return desc_.Name(); }
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framework::Variable* Var() { return &var_; }
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private:
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int count() {
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static int counter = 0;
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return counter++;
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}
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framework::VarDesc desc_;
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framework::Variable var_;
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std::weak_ptr<Variable> grad_;
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};
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}
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}
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@ -1,23 +1,32 @@
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set(FLUID_CORE_MODULES proto_desc memory lod_tensor executor init)
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cc_library(analysis SRCS dot.cc node.cc data_flow_graph.cc graph_traits.cc subgraph_splitter.cc fluid_to_data_flow_graph_pass.cc
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DEPS paddle_fluid)
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cc_library(analysis SRCS pass_manager.cc dot.cc node.cc data_flow_graph.cc graph_traits.cc subgraph_splitter.cc
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fluid_to_data_flow_graph_pass.cc
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data_flow_graph_to_fluid_pass.cc
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tensorrt_subgraph_pass.cc
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dfg_graphviz_draw_pass.cc
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DEPS framework_proto)
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cc_test(test_node SRCS node_tester.cc DEPS analysis)
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cc_test(test_dot SRCS dot_tester.cc DEPS analysis)
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set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests)
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cc_test(test_data_flow_graph SRCS data_flow_graph_tester.cc DEPS analysis ${FLUID_CORE_MODULES} paddle_fluid
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ARGS --inference_model_dir=${PYTHON_TESTS_DIR}/book/word2vec.inference.model)
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set_tests_properties(test_data_flow_graph PROPERTIES DEPENDS test_word2vec)
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function (inference_analysis_test TARGET)
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set(options "")
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set(oneValueArgs "")
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set(multiValueArgs SRCS)
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cmake_parse_arguments(analysis_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
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cc_test(test_subgraph_splitter
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SRCS subgraph_splitter_tester.cc
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DEPS analysis paddle_fluid tensor
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ARGS --inference_model_dir=${PYTHON_TESTS_DIR}/book/word2vec.inference.model)
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set_tests_properties(test_subgraph_splitter PROPERTIES DEPENDS test_word2vec)
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cc_test(${TARGET}
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SRCS "${analysis_test_SRCS}"
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DEPS analysis
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ARGS --inference_model_dir=${PYTHON_TESTS_DIR}/book/word2vec.inference.model --fraction_of_gpu_memory_to_use=0.5)
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set_tests_properties(${TARGET} PROPERTIES DEPENDS test_word2vec)
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endfunction(inference_analysis_test)
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cc_test(test_dfg_graphviz_draw_pass
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SRCS dfg_graphviz_draw_pass_tester.cc
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DEPS analysis
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ARGS --inference_model_dir=${PYTHON_TESTS_DIR}/book/word2vec.inference.model)
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set_tests_properties(test_dfg_graphviz_draw_pass PROPERTIES DEPENDS test_word2vec)
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inference_analysis_test(test_data_flow_graph SRCS data_flow_graph_tester.cc)
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inference_analysis_test(test_data_flow_graph_to_fluid_pass SRCS data_flow_graph_to_fluid_pass_tester.cc)
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inference_analysis_test(test_fluid_to_data_flow_graph_pass SRCS fluid_to_data_flow_graph_pass_tester.cc)
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inference_analysis_test(test_subgraph_splitter SRCS subgraph_splitter_tester.cc)
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inference_analysis_test(test_dfg_graphviz_draw_pass SRCS dfg_graphviz_draw_pass_tester.cc)
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#inference_analysis_test(test_tensorrt_subgraph_pass SRCS tensorrt_subgraph_pass_tester.cc)
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inference_analysis_test(test_pass_manager SRCS pass_manager_tester.cc)
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@ -0,0 +1,55 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
|
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//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
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/*
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* This file defines the class Argument, which is the input and output of the
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* analysis module. All the fields that needed either by Passes or PassManagers
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* are contained in Argument.
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*
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* TODO(Superjomn) Find some way better to contain the fields when it grow too
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* big.
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*/
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#pragma once
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/inference/analysis/data_flow_graph.h"
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namespace paddle {
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namespace inference {
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namespace analysis {
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/*
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* The argument definition of both Pass and PassManagers.
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*
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* All the fields should be registered here for clearness.
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*/
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struct Argument {
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// The graph that process by the Passes or PassManagers.
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std::unique_ptr<DataFlowGraph> main_dfg;
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// The original program desc.
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std::unique_ptr<framework::proto::ProgramDesc> origin_program_desc;
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};
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#define UNLIKELY(condition) __builtin_expect(static_cast<bool>(condition), 0)
|
||||
#define ANALYSIS_ARGUMENT_CHECK_FIELD(field__) \
|
||||
if (UNLIKELY(!(field__))) { \
|
||||
LOG(ERROR) << "field " << #field__ << " should be set."; \
|
||||
return false; \
|
||||
}
|
||||
|
||||
} // namespace analysis
|
||||
} // namespace inference
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,77 @@
|
||||
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
#include "paddle/fluid/inference/analysis/data_flow_graph_to_fluid_pass.h"
|
||||
#include "paddle/fluid/framework/proto_desc.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace inference {
|
||||
namespace analysis {
|
||||
|
||||
bool DataFlowGraphToFluidPass::Initialize(Argument* argument) {
|
||||
ANALYSIS_ARGUMENT_CHECK_FIELD(argument)
|
||||
ANALYSIS_ARGUMENT_CHECK_FIELD(argument->origin_program_desc)
|
||||
desc_ = argument->origin_program_desc.get();
|
||||
// Here some logic from program_desc.cc and will not add new interfaces into
|
||||
// framework::ProgramDesc class, use some UT to assure the correctness.
|
||||
auto* block = desc_->mutable_blocks()->Add();
|
||||
block->set_idx(framework::kRootBlockIndex);
|
||||
block->set_parent_idx(framework::kNoneBlockIndex);
|
||||
return true;
|
||||
}
|
||||
|
||||
bool DataFlowGraphToFluidPass::Finalize() { return true; }
|
||||
|
||||
void DataFlowGraphToFluidPass::Run(DataFlowGraph* graph) {
|
||||
auto traits = GraphTraits<DataFlowGraph>(graph);
|
||||
for (auto it = traits.nodes().begin(); it != traits.nodes().end(); ++it) {
|
||||
if (it->deleted()) continue;
|
||||
switch (it->type()) {
|
||||
case Node::Type::kFunction:
|
||||
LOG(INFO) << "add function " << it->name();
|
||||
AddFluidOp(&(*it));
|
||||
break;
|
||||
case Node::Type::kFunctionBlock:
|
||||
AddEngineOp(&(*it));
|
||||
break;
|
||||
default:
|
||||
continue;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void DataFlowGraphToFluidPass::AddFluidOp(Node* node) {
|
||||
LOG(INFO) << "processing func " << node->name();
|
||||
auto* ori_op = static_cast<framework::proto::OpDesc*>(node->pb_desc());
|
||||
// currently only the main block is analyzed.
|
||||
auto* main_block = desc_->mutable_blocks(framework::kRootBlockIndex);
|
||||
auto* op = main_block->add_ops();
|
||||
LOG(INFO) << "to copy the op";
|
||||
*op = *ori_op; // copy the attributes, by default, these will not be changed
|
||||
// by analysis phrase.
|
||||
// The inputs and outputs of the existing ops are not changed by tensorrt
|
||||
// subgraph pass.
|
||||
// NOTE It might be changed by other passes in the long run.
|
||||
}
|
||||
|
||||
void DataFlowGraphToFluidPass::AddEngineOp(Node* node) {
|
||||
// auto* ori_op = static_cast<framework::proto::OpDesc*>(node->extra_info());
|
||||
// auto* main_block = desc_->mutable_blocks(framework::kRootBlockIndex);
|
||||
// auto* op = main_block->add_ops();
|
||||
// TODO(Superjomn) Here need to expose some arguments for default setting.
|
||||
}
|
||||
|
||||
} // namespace analysis
|
||||
} // namespace inference
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,59 @@
|
||||
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License. */
|
||||
|
||||
/*
|
||||
* This file implements the transformation from fluid ProgramDesc to data flow
|
||||
* graph.
|
||||
*/
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "paddle/fluid/framework/program_desc.h"
|
||||
#include "paddle/fluid/inference/analysis/data_flow_graph.h"
|
||||
#include "paddle/fluid/inference/analysis/pass.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace inference {
|
||||
namespace analysis {
|
||||
class DataFlowGraphToFluidPass final : public DataFlowGraphPass {
|
||||
public:
|
||||
DataFlowGraphToFluidPass() = default;
|
||||
|
||||
bool Initialize(Argument *argument) override;
|
||||
bool Finalize() override;
|
||||
|
||||
void Run(DataFlowGraph *graph) override;
|
||||
|
||||
std::string repr() const override { return "DFG to fluid"; }
|
||||
std::string description() const override {
|
||||
return "Transform a DFG to a Fluid ProgramDesc";
|
||||
}
|
||||
|
||||
Pass *CreatePrinterPass(std::ostream &os,
|
||||
const std::string &banner) const override {
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
protected:
|
||||
// Add a Fluid Op into the ProgramDesc.
|
||||
void AddFluidOp(Node *node);
|
||||
// Add a EngineOp into the ProgramDesc.
|
||||
void AddEngineOp(Node *node);
|
||||
|
||||
private:
|
||||
framework::proto::ProgramDesc *desc_;
|
||||
};
|
||||
} // namespace analysis
|
||||
} // namespace inference
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,54 @@
|
||||
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License. */
|
||||
|
||||
#include "paddle/fluid/inference/analysis/dfg_graphviz_draw_pass.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace inference {
|
||||
namespace analysis {
|
||||
|
||||
void DFG_GraphvizDrawPass::Run(DataFlowGraph *graph) {
|
||||
auto content = Draw(graph);
|
||||
std::ofstream file(GenDotPath());
|
||||
file.write(content.c_str(), content.size());
|
||||
file.close();
|
||||
LOG(INFO) << "draw dot to " << GenDotPath();
|
||||
}
|
||||
|
||||
std::string DFG_GraphvizDrawPass::Draw(DataFlowGraph *graph) {
|
||||
Dot dot;
|
||||
// Add nodes
|
||||
for (size_t i = 0; i < graph->nodes.size(); i++) {
|
||||
const Node &node = graph->nodes.Get(i);
|
||||
if (config_.display_deleted_node || !node.deleted()) {
|
||||
dot.AddNode(node.repr(), node.dot_attrs());
|
||||
}
|
||||
}
|
||||
// Add edges
|
||||
for (size_t i = 0; i < graph->nodes.size(); i++) {
|
||||
const Node &node = graph->nodes.Get(i);
|
||||
if (!config_.display_deleted_node && node.deleted()) continue;
|
||||
for (auto &in : node.inlinks) {
|
||||
if (!config_.display_deleted_node && in->deleted()) continue;
|
||||
for (auto &in : node.inlinks) {
|
||||
dot.AddEdge(in->repr(), node.repr(), {});
|
||||
}
|
||||
}
|
||||
}
|
||||
return dot.Build();
|
||||
}
|
||||
|
||||
} // namespace analysis
|
||||
} // namespace inference
|
||||
} // namespace paddle
|
||||
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Reference in new issue