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gru_unit_op.cc
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gru_unit_op.cc
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#include "gru_unit_op.h"
namespace caffe2 {
REGISTER_CPU_OPERATOR(GRUUnit, GRUUnitOp<float, CPUContext>);
OPERATOR_SCHEMA(GRUUnit)
.NumInputs(3, 4)
.NumOutputs(1)
.SetDoc(R"DOC(
GRUUnit computes the activations of a standard GRU,
in a sequence-length aware fashion.
Concretely, given the (fused) inputs X (TxNxD), the previous hidden
state (NxD), and the sequence lengths (N), computes the GRU
activations, avoiding computation if the input is invalid (as in, the
value at X[t][n] >= seqLengths[n].
)DOC")
.Arg(
"drop_states",
"Bool to determine if hidden state is zeroes or passed "
"along for timesteps past the given sequence_length.")
.Arg(
"sequence_lengths",
"When false, the sequence lengths input is left out, "
"and all following inputs are shifted left by one.")
.Output(0, "hidden", "The new GRU hidden state calculated by this op.");
REGISTER_CPU_OPERATOR(GRUUnitGradient, GRUUnitGradientOp<float, CPUContext>);
OPERATOR_SCHEMA(GRUUnitGradient)
.NumInputs(5, 6)
.NumOutputs(2)
.Arg(
"sequence_lengths",
"When false, the sequence lengths input is left out, "
"and all following inputs are shifted left by one.");
class GetGRUUnitGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
vector<OperatorDef> GetGradientDefs() override {
if (GetFlagArgument(def_, "sequence_lengths", true)) {
return SingleGradientDef(
"GRUUnitGradient",
"",
vector<string>{I(0), I(1), I(2), I(3), O(0), GO(0)},
vector<string>{GI(0), GI(1)});
} else {
return SingleGradientDef(
"GRUUnitGradient",
"",
vector<string>{I(0), I(1), I(2), O(0), GO(0)},
vector<string>{GI(0), GI(1)});
}
}
};
REGISTER_GRADIENT(GRUUnit, GetGRUUnitGradient);
} // namespace caffe2