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114 lines
4.4 KiB
114 lines
4.4 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 "paddle/framework/op_registry.h"
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#include "paddle/operators/net_op.h"
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namespace paddle {
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namespace operators {
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class InterpOp : public NetOp {
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public:
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InterpOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: NetOp(type, inputs, outputs, attrs) {
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PADDLE_ENFORCE_NE(Input("X"), framework::kEmptyVarName,
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"Input(X) of InterpOp should not be null.");
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PADDLE_ENFORCE_NE(Input("Y"), framework::kEmptyVarName,
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"Input(Y) of InterpOp should not be null.");
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PADDLE_ENFORCE_NE(Input("W"), framework::kEmptyVarName,
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"Input(W) of InterpOp should not be null.");
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PADDLE_ENFORCE_NE(Output("SubOut"), framework::kEmptyVarName,
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"Output(SubOut) of InterpOp should not be null.");
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PADDLE_ENFORCE_NE(Output("MulOut"), framework::kEmptyVarName,
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"Output(MulOut) of InterpOp should not be null.");
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PADDLE_ENFORCE_NE(Output("Out"), framework::kEmptyVarName,
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"Output(Out) of InterpOp should not be null.");
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// SubOut = X - Y
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auto x = Input("X");
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auto y = Input("Y");
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auto sub_out = Output("SubOut");
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AppendOp(framework::OpRegistry::CreateOp(
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"elementwise_sub", {{"X", {x}}, {"Y", {y}}}, {{"Out", {sub_out}}}, {}));
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// MulOut = SubOut * W = (X - Y) * W
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auto w = Input("W");
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auto mul_out = Output("MulOut");
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AppendOp(framework::OpRegistry::CreateOp(
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"elementwise_mul", {{"X", {sub_out}}, {"Y", {w}}}, {{"Out", {mul_out}}},
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{{"axis", 0}}));
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// Out = MulOut + Y = (X - Y) * W + Y = X * W + Y * (1 - W)
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AppendOp(framework::OpRegistry::CreateOp("elementwise_add",
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{{"X", {mul_out}}, {"Y", {y}}},
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{{"Out", {Output("Out")}}}, {}));
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CompleteAddOp(false);
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}
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};
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class InterpOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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InterpOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X",
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"(Tensor), 2-D Matrix of shape [batch_size, data_dim]"
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"containing data samples, the first input of interp_op");
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AddInput("Y",
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"(Tensor), 2-D Matrix of shape `[batch_size, data_dim]`"
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"containing data samples, the second input of interp_op");
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AddInput("W",
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"(Tensor), 1-D Vector of shape [batch_size],"
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"the interpolated values in the half-open interval [0.0, 1.0)");
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AddOutput("SubOut",
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"(Tensor), the intermediate subtraction outputs, saving X - Y.")
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.AsIntermediate();
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AddOutput("MulOut",
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"(Tensor), the intermediate multiplication outputs,"
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"saving the elementwise multiplication of (X - Y) and W.")
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.AsIntermediate();
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AddOutput("Out",
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"(Tensor), the output of interp_op, same shape with X,"
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"returns the first-dimensional piecewise linear interpolant "
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"between X and Y");
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AddComment(R"DOC(
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Linear Interpolation with two inputs, used in NEURAL TURING MACHINE.
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Equation:
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Out.row[i] = X.row[i] * W[i] + Y.row[i] * (1 - W[i])
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= (X.row[i] - Y.row[i]) * W[i] + Y.row[i]
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Example:
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X = [[1,2],[3,4]],
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Y = [[2,1],[4,3]],
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W = [0.3, 0.4]
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Then, Out = [[1.7,1.3],[3.6,3.4]]
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where 1.7 = 1*0.3+2*(1-0.3),
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1.3 = 2*0.3+1*(1-0.3),
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3.6 = 3*0.4+4*(1-0.4),
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3.4 = 4*0.4+3*(1-0.4)
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)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_WITHOUT_GRADIENT(interp, ops::InterpOp, ops::InterpOpMaker);
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