blob: 83b106c096c7e34955d36efc5e7ffee39aa792b0 [file] [log] [blame]
/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* 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 "lstm_unit_op.h"
namespace caffe2 {
REGISTER_CPU_OPERATOR(LSTMUnit, LSTMUnitOp<CPUContext>);
OPERATOR_SCHEMA(LSTMUnit)
.NumInputs(5)
.NumOutputs(2)
.SetDoc(R"DOC(
LSTMUnit computes the activations of a standard LSTM (without peephole
connections), in a sequence-length aware fashion.
Concretely, given the (fused) inputs X (TxNxD), the previous cell
state (NxD), and the sequence lengths (N), computes the LSTM
activations, avoiding computation if the input is invalid (as in, the
value at X{t][n] >= seqLengths[n].
)DOC")
.Arg("forget_bias", "Bias term to add in while calculating forget gate");
REGISTER_CPU_OPERATOR(LSTMUnitGradient, LSTMUnitGradientOp<CPUContext>);
OPERATOR_SCHEMA(LSTMUnitGradient).NumInputs(9).NumOutputs(3);
class GetLSTMUnitGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"LSTMUnitGradient",
"",
vector<string>{I(0), I(1), I(2), I(3), I(4), O(0), O(1), GO(0), GO(1)},
vector<string>{GI(0), GI(1), GI(2)});
}
};
REGISTER_GRADIENT(LSTMUnit, GetLSTMUnitGradient);
}