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TargetGenerationConfig targetGenConfig(
FLAGS_wordseparator,
FLAGS_sampletarget,
FLAGS_criterion,
FLAGS_surround,
false /* isSeq2seqCrit */,
FLAGS_replabel,
true /* skip unk */,
FLAGS_usewordpiece /* fallback2LetterWordSepLeft */,
!FLAGS_usewordpiece /* fallback2LetterWordSepLeft */);
const auto sfxConf = (FLAGS_sfx_config.empty())
? std::vector<sfx::SoundEffectConfig>()
: sfx::readSoundEffectConfigFile(FLAGS_sfx_config);
auto inputTransform = inputFeatures(
featParams,
featType,
{FLAGS_localnrmlleftctx, FLAGS_localnrmlrightctx},
sfxConf);
auto targetTransform = targetFeatures(tokenDict, lexicon, targetGenConfig);
auto wordTransform = wordFeatures(wordDict);
int targetpadVal = kTargetPadValue;
int wordpadVal = kTargetPadValue;
std::vector<std::string> trainSplits = fl::lib::split(",", FLAGS_train, true);
auto trainds = createDataset(
trainSplits,
FLAGS_datadir,
FLAGS_batchsize,
inputTransform,
targetTransform,
wordTransform,
std::make_tuple(0, targetpadVal, wordpadVal),
worldRank,
worldSize,
false // allowEmpty
);
std::map<std::string, std::shared_ptr<fl::Dataset>> validds;
int64_t validBatchSize =
FLAGS_validbatchsize == -1 ? FLAGS_batchsize : FLAGS_validbatchsize;
for (const auto& s : validTagSets) {
validds[s.first] = createDataset(
{s.second},
FLAGS_datadir,
validBatchSize,
inputTransform,
targetTransform,
wordTransform,
std::make_tuple(0, targetpadVal, wordpadVal),
worldRank,
worldSize,
true // allowEmpty
);
}
/* =========== Create Network & Optimizers / Reload Snapshot ============ */
std::shared_ptr<fl::Module> network;
auto archfile = FLAGS_arch;
FL_LOG_MASTER(INFO) << "Loading architecture file from " << archfile;
// Encoder network, works on audio
if (fl::lib::endsWith(archfile, ".so")) {
network = fl::pkg::runtime::ModulePlugin(archfile).arch(numFeatures, numClasses);
} else {
network = fl::pkg::runtime::buildSequentialModule(archfile, numFeatures, numClasses);
}
std::shared_ptr<fl::Module> forkingNetwork;
Serializer::load(reloadPath, version, cfg, forkingNetwork);
if (version != FL_APP_ASR_VERSION) {
LOG(WARNING) << "Model version " << version << " and code version "
<< FL_APP_ASR_VERSION;
}
// override params
if (forkingNetwork->params().size() != network->params().size()) {
LOG(FATAL)
<< "Mismatch in # parameters for the model specificied by archfile and forking model.";
}
for (int i = 0; i < forkingNetwork->params().size(); ++i) {
if (network->param(i).dims() != forkingNetwork->param(i).dims()) {
LOG(FATAL) << "Mismatch in parameter dims for position " << i
<< ". Expected: " << network->param(i).dims()
<< " Got: " << forkingNetwork->param(i).dims();
}
network->setParams(forkingNetwork->param(i), i);
}
FL_LOG_MASTER(INFO) << "[Network] " << network->prettyString();
FL_LOG_MASTER(INFO) << "[Network Params: " << numTotalParams(network) << "]";
auto scalemode = getCriterionScaleMode(FLAGS_onorm, FLAGS_sqnorm);
std::shared_ptr<SequenceCriterion> criterion =
std::make_shared<CTCLoss>(scalemode);
FL_LOG_MASTER(INFO) << "[Criterion] " << criterion->prettyString();
std::shared_ptr<fl::FirstOrderOptimizer> netoptim = initOptimizer(
{network}, FLAGS_netoptim, FLAGS_lr, FLAGS_momentum, FLAGS_weightdecay);