You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
132 lines
3.9 KiB
132 lines
3.9 KiB
// 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.
|
|
|
|
#pragma once
|
|
|
|
#include <string>
|
|
|
|
#include "paddle/contrib/tape/tape.h"
|
|
#include "paddle/contrib/tape/variable.h"
|
|
#include "paddle/fluid/framework/type_defs.h"
|
|
|
|
namespace paddle {
|
|
namespace tape {
|
|
|
|
class Function {};
|
|
|
|
class Fill {
|
|
public:
|
|
Fill(const std::string &initializer, const framework::AttributeMap &attrs)
|
|
: initializer_(initializer), attrs_(attrs) {}
|
|
|
|
void operator()(VariableHandle var) {
|
|
get_global_tape().AddOp(initializer_, {}, {{"Out", {var}}}, attrs_);
|
|
}
|
|
|
|
private:
|
|
const std::string initializer_;
|
|
const framework::AttributeMap attrs_;
|
|
};
|
|
|
|
class Mean {
|
|
public:
|
|
VariableHandle operator()(VariableHandle var) {
|
|
VariableHandle out(new Variable("mean"));
|
|
get_global_tape().AddOp("mean", {{"X", {var}}}, {{"Out", {out}}}, {});
|
|
return out;
|
|
}
|
|
};
|
|
|
|
class Linear {
|
|
public:
|
|
Linear(int in_dim, int out_dim, const std::string &act)
|
|
: w_(new Variable("LinearWeight")),
|
|
b_(new Variable("LinearBias")),
|
|
act_(act) {
|
|
Tape init_tape;
|
|
|
|
std::string initializer = "fill_constant";
|
|
framework::AttributeMap attrs;
|
|
attrs["dtype"] = paddle::framework::proto::VarType::Type::VarType_Type_FP32;
|
|
attrs["shape"] = std::vector<int>{in_dim, out_dim};
|
|
attrs["value"] = 1.0f;
|
|
init_tape.AddOp(initializer, {}, {{"Out", {w_}}}, attrs);
|
|
|
|
attrs["dtype"] = paddle::framework::proto::VarType::Type::VarType_Type_FP32;
|
|
attrs["shape"] = std::vector<int>{out_dim};
|
|
attrs["value"] = 1.0f;
|
|
init_tape.AddOp(initializer, {}, {{"Out", {b_}}}, attrs);
|
|
|
|
init_tape.Forward();
|
|
}
|
|
|
|
VariableHandle operator()(VariableHandle input) {
|
|
VariableHandle pre_bias(new Variable("linear"));
|
|
get_global_tape().AddOp("mul",
|
|
{{"X", {input}}, {"Y", {w_}}},
|
|
{{"Out", {pre_bias}}},
|
|
{{"x_num_col_dims", 1}, {"y_num_col_dims", 1}});
|
|
VariableHandle pre_act(new Variable("linear"));
|
|
get_global_tape().AddOp("elementwise_add",
|
|
{{"X", {pre_bias}}, {"Y", {b_}}},
|
|
{{"Out", {pre_act}}},
|
|
{{"axis", 1}});
|
|
VariableHandle post_act(new Variable("linear"));
|
|
get_global_tape().AddOp(
|
|
act_, {{"X", {pre_act}}}, {{"Out", {post_act}}}, {});
|
|
return post_act;
|
|
}
|
|
|
|
std::vector<VariableHandle> Params() { return {w_, b_}; }
|
|
|
|
private:
|
|
VariableHandle w_;
|
|
VariableHandle b_;
|
|
std::string act_;
|
|
};
|
|
|
|
class SGD {
|
|
public:
|
|
SGD(float learning_rate) : learning_rate_(new Variable("sgd")) {
|
|
Tape init_tape;
|
|
|
|
std::string initializer = "fill_constant";
|
|
framework::AttributeMap attrs;
|
|
attrs["dtype"] = paddle::framework::proto::VarType::Type::VarType_Type_FP32;
|
|
attrs["shape"] = std::vector<int>{1};
|
|
attrs["value"] = learning_rate;
|
|
init_tape.AddOp(initializer, {}, {{"Out", {learning_rate_}}}, attrs);
|
|
|
|
init_tape.Forward();
|
|
}
|
|
|
|
void operator()(VariableHandle input) {
|
|
PADDLE_ENFORCE(get_global_tape().HasBeenBackwarded(),
|
|
"optimization must happen after the backward");
|
|
Tape temp_tape;
|
|
temp_tape.AddOp("sgd",
|
|
{{"Param", {input}},
|
|
{"LearningRate", {learning_rate_}},
|
|
{"Grad", {input->Grad()}}},
|
|
{{"ParamOut", {input}}},
|
|
{});
|
|
temp_tape.Forward();
|
|
}
|
|
|
|
private:
|
|
VariableHandle learning_rate_;
|
|
};
|
|
}
|
|
}
|