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#include "caffe2/opt/custom/concat_elim.h"
#include "caffe2/core/logging.h"
#include "caffe2/opt/nql/graphmatcher.h"
#include "caffe2/opt/passes.h"
#include "nomnigraph/Representations/NeuralNet.h"
#include "nomnigraph/Support/Common.h"
#include "nomnigraph/Transformations/SubgraphMatcher.h"
namespace caffe2 {
namespace opt {
void concatElim(NNModule* nn) {
using namespace nom::matcher;
using namespace nom::repr::nn;
using namespace nom::repr;
auto mg = NNMatchGraph();
auto matchConcatInputs =
mg.createNode(std::move(matchExternalTensorNode().starCount()));
auto matchConcat = mg.createNode([](NNGraph::NodeRef nodeRef) {
NOM_REQUIRE_OR_RET_FALSE(nn::is<Concat>(nodeRef));
NOM_REQUIRE_OR_RET_FALSE(nn::hasUniqueConsumer(nodeRef));
auto node = nn::get<Concat>(nodeRef);
return node->getAxis() == 1 && node->getAddAxis();
});
mg.createEdge(matchConcatInputs, matchConcat);
auto matchConcatOutput = mg.createNode(nn::is<nom::repr::Tensor>);
mg.createEdge(matchConcat, matchConcatOutput);
auto matchBatchMatmul = mg.createNode([](NNGraph::NodeRef nodeRef) {
NOM_REQUIRE_OR_RET_FALSE(nn::is<BatchMatMul>(nodeRef));
NOM_REQUIRE_OR_RET_FALSE(nn::hasSingleOutputAndConsumer(nodeRef));
auto node = nn::get<BatchMatMul>(nodeRef);
return node->getTransA() == 0 && node->getTransB() == 1 &&
node->getBroadcast() == 0;
});
mg.createEdge(matchConcatOutput, matchBatchMatmul);
mg.createEdge(matchConcatOutput, matchBatchMatmul);
auto matchBmmOutput = mg.createNode(nn::is<nom::repr::Tensor>);
mg.createEdge(matchBatchMatmul, matchBmmOutput);
auto matchFlatten = mg.createNode([](NNGraph::NodeRef nodeRef) {
NOM_REQUIRE_OR_RET_FALSE(nn::is<Flatten>(nodeRef));
return nn::hasSingleOutputAndConsumer(nodeRef);
});
mg.createEdge(matchBmmOutput, matchFlatten);
auto matchFlattenOutput = mg.createNode(nn::is<nom::repr::Tensor>);
mg.createEdge(matchFlatten, matchFlattenOutput);
auto matchIndices = mg.createNode(matchExternalTensorNode());
auto matchBatchGather = mg.createNode(nn::is<BatchGather>);
mg.createEdge(matchFlattenOutput, matchBatchGather);
mg.createEdge(matchIndices, matchBatchGather);
mg.replaceSubgraph(
nn->dataFlow,
matchBatchGather,
[matchConcatOutput](
NNGraph& g,
NNGraph::NodeRef batchGatherNode,
const NNMatchGraph::SubgraphMatchResultType& matchResult) {
auto fusedNode =
g.createNode(make_unique<ConcatBatchMatMulBatchGatherOp>());
auto batchGatherNodeOutputs = nn::getOutputs(batchGatherNode);
for (const auto& output : batchGatherNodeOutputs) {
auto tensor = nn::get<nom::repr::Tensor>(output);
// Handle cases where blob names are reused - D9113128.
auto newOutput = g.createNode(
make_unique<nom::repr::Tensor>(tensor->getName() + "_cc_bmm_bg"));
g.createEdge(fusedNode, newOutput);
g.replaceOutEdges(output, newOutput);
}
auto concatNode =
getProducer(matchResult.getMatchNodeMap()->at(matchConcatOutput));
g.replaceInEdges(batchGatherNode, fusedNode);
g.replaceInEdges(concatNode, fusedNode);
g.deleteNodes(matchResult.getMatchedSubgraph()->getNodes());
return true;
});
}
REGISTER_OPT_PASS_FROM_FUNC(ConcatElim, concatElim);
void concatAddMulNaNClipElim(NNModule* nn) {
using namespace nom::repr;
nom::nql::GraphMatcher gm;
gm.initFromString(R"NQL(def query {
%concat_out, %split_info = Concat(*)
%add = Add(%concat_out, %add_in)
%mul = Mul(%add, %mul_in)
%replace = ReplaceNaN(%mul)
%out = Clip(%replace)
})NQL");
CAFFE_ENFORCE(gm.getMatcher(), "Unable to parse NQL query.");
// Iterate through each match and replace them
for (const auto& match : gm.getMatches(nn->dataFlow)) {
// Various attributes we care about for this fusion
NOM_REQUIRE_OR_CONT(nn::get<Concat>(match["Concat"])->getAxis() == 1);
NOM_REQUIRE_OR_CONT(nn::get<Add>(match["Add"])->getBroadcast() == 1);
NOM_REQUIRE_OR_CONT(nn::get<Mul>(match["Mul"])->getBroadcast() == 1);
NOM_REQUIRE_OR_CONT(
std::abs(nn::get<ReplaceNaN>(match["ReplaceNaN"])->getValue()) < 0.01);
// Figure out the input/output order (creating new nodes if needed)
std::vector<NNGraph::NodeRef> inputs, outputs;
// First set up the inputs
inputs.emplace_back(match["\%add_in"]);
inputs.emplace_back(match["\%mul_in"]);
for (const auto& concat_input : nn::getInputs(match["Concat"])) {
inputs.emplace_back(concat_input);
}
// Set up the outputs
outputs.emplace_back(match["\%out"]);
// TODO(duc): The subgraph matcher doesn't yet handle patterns
// that are not trees, meaning the %split_info node is not yet
// matched.
outputs.emplace_back(nn::getOutputs(match["Concat"]).at(1));
auto min = nn::get<Clip>(match["Clip"])->getMin();
auto max = nn::get<Clip>(match["Clip"])->getMax();
// This will do all the work
nn->replaceSubgraphWithOperator<ConcatAddMulReplaceNaNClip>(
match.subgraph, inputs, outputs, min, max);
}
}
REGISTER_OPT_PASS_FROM_FUNC(ConcatAddMulNaNClipElim, concatAddMulNaNClipElim);
void gatherFuse8BitRowwiseQuantFloatMulLengthsSumElim(NNModule* nn) {
using namespace nom::repr;
nom::nql::GraphMatcher gm;
gm.initFromString(R"NQL(def query {
%gather = Gather(%a, %b)
%ff = Fused8BitRowwiseQuantizedToFloat(%gather)
%mu = Mul(%ff, %mul_in)
%out = LengthsSum(%mu, %len_in)
})NQL");
CAFFE_ENFORCE(gm.getMatcher(), "Unable to parse NQL query.");
// Iterate through each match and replace them
for (const auto& match : gm.getMatches(nn->dataFlow)) {
NOM_REQUIRE_OR_CONT(nn::get<Mul>(match["Mul"])->getBroadcast() == 1);
NOM_REQUIRE_OR_CONT(nn::get<Mul>(match["Mul"])->getAxis() == 0);
// Figure out the input/output order (creating new nodes if needed)
std::vector<NNGraph::NodeRef> inputs, outputs;
// First set up the inputs
const auto& gather_inputs = nn::getInputs(match["Gather"]);
inputs.emplace_back(gather_inputs.at(0));
inputs.emplace_back(match["\%mul_in"]);
inputs.emplace_back(gather_inputs.at(1));
inputs.emplace_back(match["\%len_in"]);
// Set up the outputs
outputs.emplace_back(match["\%out"]);
// Check if outputs of the subgraph contain intermediate tensors
// If so, abort fusion.
std::unordered_set<NNGraph::NodeRef> internal;
for (const auto& output : nn::getOutputs(match["Gather"])) {
internal.emplace(output);
}
for (const auto& output :
nn::getOutputs(match["Fused8BitRowwiseQuantizedToFloat"])) {
internal.emplace(output);
}
for (const auto& output : nn::getOutputs(match["Mul"])) {
internal.emplace(output);
}
for (const auto& output : nn::getOutputs(match.subgraph)) {
if (internal.count(output)) {
LOG(INFO) << "Skip fusing Gather-Fused8BitRowwiseQuantizedToFloat"
<< "-Mul-LengthsSum as internal tensor "
<< nn::getName(output)
<< " is used as external output of the subgraph.";
return;
}
}
// This will do all the work
nn->replaceSubgraphWithOperator<SparseLengthsWeightedSumFused8BitRowwise>(
match.subgraph, inputs, outputs);
}
}
REGISTER_OPT_PASS_FROM_FUNC(
GatherFuse8BitRowwiseQuantFloatMulLengthsSumElim,
gatherFuse8BitRowwiseQuantFloatMulLengthsSumElim);
} // namespace opt
} // namespace caffe2
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