94 lines
2.7 KiB
C++
94 lines
2.7 KiB
C++
// sherpa-onnx/csrc/offline-moonshine-greedy-search-decoder.cc
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#include "sherpa-onnx/csrc/offline-moonshine-greedy-search-decoder.h"
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#include <algorithm>
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#include <utility>
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#include "sherpa-onnx/csrc/macros.h"
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#include "sherpa-onnx/csrc/onnx-utils.h"
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namespace sherpa_onnx {
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std::vector<OfflineMoonshineDecoderResult>
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OfflineMoonshineGreedySearchDecoder::Decode(Ort::Value encoder_out) {
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auto encoder_out_shape = encoder_out.GetTensorTypeAndShapeInfo().GetShape();
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if (encoder_out_shape[0] != 1) {
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SHERPA_ONNX_LOGE("Support only batch size == 1. Given: %d\n",
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static_cast<int32_t>(encoder_out_shape[0]));
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return {};
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}
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auto memory_info =
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Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
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// encoder_out_shape[1] * 384 is the number of audio samples
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// 16000 is the sample rate
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//
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//
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// 384 is from the moonshine paper
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int32_t max_len =
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static_cast<int32_t>(encoder_out_shape[1] * 384 / 16000.0 * 6);
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int32_t sos = 1;
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int32_t eos = 2;
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int32_t seq_len = 1;
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std::vector<int32_t> tokens;
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std::array<int64_t, 2> token_shape = {1, 1};
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int64_t seq_len_shape = 1;
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Ort::Value token_tensor = Ort::Value::CreateTensor(
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memory_info, &sos, 1, token_shape.data(), token_shape.size());
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Ort::Value seq_len_tensor =
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Ort::Value::CreateTensor(memory_info, &seq_len, 1, &seq_len_shape, 1);
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Ort::Value logits{nullptr};
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std::vector<Ort::Value> states;
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std::tie(logits, states) = model_->ForwardUnCachedDecoder(
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std::move(token_tensor), std::move(seq_len_tensor), View(&encoder_out));
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int32_t vocab_size = logits.GetTensorTypeAndShapeInfo().GetShape()[2];
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for (int32_t i = 0; i != max_len; ++i) {
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const float *p = logits.GetTensorData<float>();
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int32_t max_token_id = static_cast<int32_t>(
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std::distance(p, std::max_element(p, p + vocab_size)));
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if (max_token_id == eos) {
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break;
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}
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tokens.push_back(max_token_id);
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seq_len += 1;
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token_tensor = Ort::Value::CreateTensor(
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memory_info, &tokens.back(), 1, token_shape.data(), token_shape.size());
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seq_len_tensor =
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Ort::Value::CreateTensor(memory_info, &seq_len, 1, &seq_len_shape, 1);
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// To fix the false alarm of clang-tidy
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// error: 'states' used after it was moved
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// [bugprone-use-after-move,-warnings-as-errors]
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// we use a tmp_states here
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std::vector<Ort::Value> tmp_states{std::move(states)};
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std::tie(logits, states) = model_->ForwardCachedDecoder(
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std::move(token_tensor), std::move(seq_len_tensor), View(&encoder_out),
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std::move(tmp_states));
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}
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OfflineMoonshineDecoderResult ans;
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ans.tokens = std::move(tokens);
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return {ans};
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}
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} // namespace sherpa_onnx
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