// rnnlmbin/rnnlm-sentence-probs.cc
  
  // Copyright 2015-2017  Johns Hopkins University (author: Daniel Povey)
  //           2017 Hainan Xu
  
  // See ../../COPYING for clarification regarding multiple authors
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  //
  //  http://www.apache.org/licenses/LICENSE-2.0
  //
  // THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  // KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
  // WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
  // MERCHANTABLITY OR NON-INFRINGEMENT.
  // See the Apache 2 License for the specific language governing permissions and
  // limitations under the License.
  
  #include "base/kaldi-common.h"
  #include "util/common-utils.h"
  #include "rnnlm/rnnlm-training.h"
  #include "rnnlm/rnnlm-example-utils.h"
  #include "rnnlm/rnnlm-core-compute.h"
  #include "rnnlm/rnnlm-compute-state.h"
  #include "nnet3/nnet-utils.h"
  #include <fstream>
  #include <sstream>
  
  int main(int argc, char *argv[]) {
    try {
      using namespace kaldi;
      using namespace kaldi::rnnlm;
      typedef kaldi::int32 int32;
      typedef kaldi::int64 int64;
  
      const char *usage =
          "This program takes input of a text corpus (with words represented by
  "
          "symbol-id's), and an already trained RNNLM model, and prints the log
  "
          "-probabilities of each word in the corpus. The RNNLM resets its hidden
  "
          "state for each new line. This is used in n-best rescoring with RNNLMs
  "
          "An example the n-best rescoring usage is at "
          "egs/swbd/s5c$ vi local/rnnlm/run_tdnn_lstm.sh"
          "
  "
          "Usage:
  "
          " rnnlm-sentence-probs [options] <rnnlm> <word-embedding-matrix> "
          "<input-text-file> 
  "
          "e.g.:
  "
          " rnnlm-sentence-probs rnnlm/final.raw rnnlm/final.word_embedding "
          "dev_corpus.txt > output_logprobs.txt
  ";
  
      std::string use_gpu = "no";
      bool batchnorm_test_mode = true, dropout_test_mode = true;
  
      ParseOptions po(usage);
      rnnlm::RnnlmComputeStateComputationOptions opts;
      po.Register("use-gpu", &use_gpu,
                  "yes|no|optional|wait, only has effect if compiled with CUDA");
      po.Register("batchnorm-test-mode", &batchnorm_test_mode,
                  "If true, set test-mode to true on any BatchNormComponents.");
      po.Register("dropout-test-mode", &dropout_test_mode,
                  "If true, set test-mode to true on any DropoutComponents and "
                  "DropoutMaskComponents.");
      opts.Register(&po);
  
      po.Read(argc, argv);
  
      if (po.NumArgs() != 3) {
        po.PrintUsage();
        exit(1);
      }
  
      if (opts.bos_index == -1 || opts.eos_index == -1) {
        KALDI_ERR << "You must set --bos-symbol and --eos-symbol options";
      }
  
      std::string rnnlm_rxfilename = po.GetArg(1),
                  word_embedding_rxfilename = po.GetArg(2),
                  text_filename = po.GetArg(3);
  
  #if HAVE_CUDA==1
      CuDevice::Instantiate().SelectGpuId(use_gpu);
      CuDevice::Instantiate().AllowMultithreading();
  #endif
  
      kaldi::nnet3::Nnet rnnlm;
      ReadKaldiObject(rnnlm_rxfilename, &rnnlm);
  
      KALDI_ASSERT(IsSimpleNnet(rnnlm));
      if (batchnorm_test_mode)
        SetBatchnormTestMode(true, &rnnlm);
      if (dropout_test_mode)
        SetDropoutTestMode(true, &rnnlm);
  
      CuMatrix<BaseFloat> word_embedding_mat;
      ReadKaldiObject(word_embedding_rxfilename, &word_embedding_mat);
  
      const rnnlm::RnnlmComputeStateInfo info(opts, rnnlm, word_embedding_mat);
  
      std::ifstream ifile(text_filename.c_str());
  
      std::string key, line;
      while (ifile >> key) {
        getline(ifile, line);
        std::vector<int32> v;
        if (!SplitStringToIntegers(line, " ", true, &v)) {
          KALDI_ERR << "Input file should contain only integers.";
        }
        RnnlmComputeState rnnlm_compute_state(info, opts.bos_index);
  
        std::cout << key << " ";
        for (int32 i = 0; i < v.size(); i++) {
          int32 word_id = v[i];
          std::cout << rnnlm_compute_state.LogProbOfWord(word_id) << " ";
  
          rnnlm_compute_state.AddWord(word_id);
        }
        // add the </s> symbol
        int32 word_id = opts.eos_index;
        std::cout << rnnlm_compute_state.LogProbOfWord(word_id) << std::endl;
      }
  
  #if HAVE_CUDA==1
      CuDevice::Instantiate().PrintProfile();
  #endif
      return 0;
    } catch(const std::exception &e) {
      std::cerr << e.what() << '
  ';
      return -1;
    }
  }