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#include "ctranslate2/models/language_model.h"
#include "ctranslate2/decoding.h"
namespace ctranslate2 {
namespace models {
const Vocabulary& LanguageModel::get_vocabulary() const {
return *_vocabulary;
}
void LanguageModel::initialize(ModelReader& model_reader) {
if (binary_version() < 6) {
config["unk_token"] = get_attribute_with_default<std::string>("unk_token", "<unk>");
config["bos_token"] = get_attribute_with_default<std::string>("bos_token", "<s>");
config["eos_token"] = get_attribute_with_default<std::string>("eos_token", "</s>");
}
VocabularyInfo vocab_info;
vocab_info.unk_token = config["unk_token"];
vocab_info.bos_token = config["bos_token"];
vocab_info.eos_token = config["eos_token"];
_vocabulary = std::make_shared<Vocabulary>(*model_reader.get_required_file("vocabulary.txt"),
std::move(vocab_info));
}
std::vector<ScoringResult>
SequenceGeneratorReplica::score(const std::vector<std::vector<std::string>>& tokens,
const ScoringOptions& options) {
PROFILE("SequenceGeneratorReplica::score");
const auto scoped_device_setter = model()->get_scoped_device_setter();
return get_batch_results_helper<ScoringResult>(
tokens.size(),
[this, &tokens, &options](size_t i, ScoringResult& result) {
return skip_scoring(tokens[i], options, result);
},
[this, &tokens, &options](const std::vector<size_t>& index_to_run) {
return run_scoring(index_vector(tokens, index_to_run), options);
});
}
std::vector<GenerationResult>
SequenceGeneratorReplica::generate(const std::vector<std::vector<std::string>>& start_tokens,
const GenerationOptions& options) {
PROFILE("SequenceGeneratorReplica::generate");
const auto scoped_device_setter = model()->get_scoped_device_setter();
if (start_tokens.empty())
return {};
return run_generation(start_tokens, options);
}
StorageView
SequenceGeneratorReplica::forward(const std::vector<std::vector<std::string>>& tokens,
const bool return_log_probs) {
const auto& vocabulary = _model->get_vocabulary();
return forward(vocabulary.to_ids(tokens), return_log_probs);
}
StorageView
SequenceGeneratorReplica::forward(const std::vector<std::vector<size_t>>& ids,
const bool return_log_probs) {
StorageView lengths;
StorageView input_ids = layers::make_sequence_inputs(ids, Device::CPU, 1, &lengths);
return forward(input_ids, lengths, return_log_probs);
}
StorageView
SequenceGeneratorReplica::forward(const StorageView& ids,
const StorageView& lengths,
const bool return_log_probs) {
PROFILE("SequenceGeneratorReplica::forward");
const auto& model = *this->model();
const auto device = model.device();
const auto scoped_device_setter = model.get_scoped_device_setter();
StorageView output;
if (ids.device() != device)
output = forward(ids.to(device), lengths.to(device));
else
output = forward(ids, lengths);
if (return_log_probs)
ops::LogSoftMax()(output);
// Ensure all operations are finished before returning the output.
synchronize_stream(model.device());
return output;
}
DecoderReplica::DecoderReplica(const std::shared_ptr<const LanguageModel>& model,
std::unique_ptr<layers::Decoder> decoder)
: SequenceGeneratorReplica(model)
, _model(model)
, _decoder(std::move(decoder))
{
}
std::vector<ScoringResult>
DecoderReplica::run_scoring(const std::vector<std::vector<std::string>>& tokens,
const ScoringOptions& options) {
const auto& vocabulary = _model->get_vocabulary();
const auto ids = vocabulary.to_ids(tokens, options.max_input_length);
layers::DecoderState state = _decoder->initial_state(/*iterative_decoding=*/false);
return score_sequences(*_decoder,
state,
ids,
vocabulary,
_model->preferred_size_multiple());
}
bool DecoderReplica::skip_scoring(const std::vector<std::string>& tokens,
const ScoringOptions&,
ScoringResult&) {
return tokens.size() < 2;
}
std::vector<GenerationResult>
DecoderReplica::run_generation(const std::vector<std::vector<std::string>>& start_tokens,
const GenerationOptions& options) {
const auto& vocabulary = _model->get_vocabulary();
_decoder->update_output_layer(_model->preferred_size_multiple());
DecodingOptions decoding_options;
decoding_options.beam_size = options.beam_size;
decoding_options.length_penalty = options.length_penalty;
decoding_options.repetition_penalty = options.repetition_penalty;
decoding_options.no_repeat_ngram_size = options.no_repeat_ngram_size;
decoding_options.allow_early_exit = options.allow_early_exit;
decoding_options.max_length = options.max_length;
decoding_options.min_length = options.min_length;
decoding_options.sampling_topk = options.sampling_topk;
decoding_options.sampling_temperature = options.sampling_temperature;
decoding_options.num_hypotheses = options.num_hypotheses;
decoding_options.normalize_scores = options.normalize_scores;
decoding_options.return_scores = options.return_scores;
decoding_options.return_alternatives = options.return_alternatives;
decoding_options.min_alternative_expansion_prob = options.min_alternative_expansion_prob;
if (options.disable_unk)
decoding_options.disable_ids.push_back(vocabulary.unk_id());
const auto start_ids = vocabulary.to_ids(start_tokens);
layers::DecoderState state = _decoder->initial_state();
std::vector<DecodingResult> results = decode(*_decoder,
state,
start_ids,
vocabulary.eos_id(),
decoding_options);
std::vector<GenerationResult> final_results;
final_results.reserve(results.size());
for (size_t i = 0; i < results.size(); ++i) {
auto& result = results[i];
// Forward the start token to the output if it is not the special BOS token.
if (!start_ids[i].empty() && start_ids[i][0] != vocabulary.bos_id()) {
for (auto& sequence : result.hypotheses)
sequence.insert(sequence.begin(), start_ids[i][0]);
}
final_results.emplace_back(vocabulary.to_tokens(result.hypotheses),
std::move(result.scores));
}
return final_results;
}
StorageView DecoderReplica::forward(const StorageView& ids, const StorageView& lengths) {
if (ids.rank() != 2)
throw std::invalid_argument("Expected input ids to have 2 dimensions, but got "
+ std::to_string(ids.rank())
+ " dimension(s) instead");
if (lengths.size() != ids.dim(0))
throw std::invalid_argument("Expected lengths vector to have size "
+ std::to_string(ids.dim(0))
+ ", but got size "
+ std::to_string(lengths.size())
+ " instead");
auto& decoder = *_decoder;
decoder.update_output_layer(_model->preferred_size_multiple());
auto state = decoder.initial_state(/*iterative_decoding=*/false);
StorageView logits(decoder.output_type(), decoder.device());
decoder(ids, lengths, state, logits);
return logits;
}
}
}
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