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Natural Language Processing with Representation Learning

Machine Translation for Vietnamese → English and Chinese → English

Members:

  • Mihir Rana
  • Kenil Tanna
  • Diogo Mesquita
  • Yassine Kadiri

Requirements

For ease of setup, we have created a requirements.yaml file which will create a conda environment with the name nlp_project and install all dependencies and requirements into that environment. To do this:

  • Install Anaconda and run:
conda env create -f requirements.yaml
  • Optionally, if you want to run it on a GPU, install CUDA and cuDNN

Installation

Again, for simplicity, we have created a module with the name seq2seq-nlp which can be installed directly into pip by running the following command from the main project directory:

pip install -e .

Note: Please uncomment these lines for getting results on the test set.

Usage

usage: main.py [-h] [--project-dir PROJECT_DIR] [--data-dir DATA_DIR]
               [--source-dataset SOURCE_DATASET]
               [--target-dataset TARGET_DATASET]
               [--checkpoints-dir CHECKPOINTS_DIR]
               [--load-ckpt LOAD_CHECKPOINT] [--load-enc-ckpt LOAD_ENC_CKPT]
               [--load-dec-ckpt LOAD_DEC_CKPT] [--source-vocab SOURCE_VOCAB]
               [--target-vocab TARGET_VOCAB] [--max-len-source MAX_LEN_SOURCE]
               [--max-len-target MAX_LEN_TARGET]
               [--unk-threshold UNK_THRESHOLD] [--batch-size BATCH_SIZE]
               [--epochs EPOCHS] [--device DEVICE] [--device-id DEVICE_ID]
               [--ngpu NGPU] [--parallel] [--lr LR]
               [--encoder-type ENCODER_TYPE] [--decoder-type DECODER_TYPE]
               [--num-directions NUM_DIRECTIONS]
               [--encoder-num-layers ENCODER_NUM_LAYERS]
               [--decoder-num-layers DECODER_NUM_LAYERS]
               [--encoder-emb-size ENCODER_EMB_SIZE]
               [--decoder-emb-size DECODER_EMB_SIZE]
               [--encoder-hid-size ENCODER_HID_SIZE]
               [--encoder-dropout ENCODER_DROPOUT]
               [--decoder-dropout DECODER_DROPOUT] [--clip-param CLIP_PARAM]
               [--beam-size BEAM_SIZE] [--force]
               [--teacher-forcing-prob TEACHER_FORCING_PROB] [--use-attn]

optional arguments:
  -h, --help                                    show this help message and exit
  --project-dir PROJECT_DIR                     path to project directory
  --source-dataset SOURCE_DATASET               name of source dataset file in data directory, default='vi'
  --target-dataset TARGET_DATASET               name of target dataset file in data directory, default='en'
  --data-dir DATA_DIR                           path to data directory, default="data"
  --checkpoints-dir CHECKPOINTS_DIR             path to checkpoints directory
  --load-ckpt LOAD_CHECKPOINT                   name of checkpoint file to load
    --load-enc-ckpt LOAD_ENC_CKPT               name of encoder file to load
  --load-dec-ckpt LOAD_DEC_CKPT                 name of decoder file to load
  --source-vocab SOURCE_VOCAB                   source dataset vocabulary size, default=50000
  --target-vocab TARGET_VOCAB                   target dataset vocabulary size, default=50000
  --max-len-source MAX_LEN_SOURCE               max sentence length of source, default=100
  --max-len-target MAX_LEN_TARGET               max sentence length of target, default=100
  --unk-threshold UNK_THRESHOLD                 count threshold below which words are to be treated as UNK
  --batch-size BATCH_SIZE                       batch size, default=32
  --epochs EPOCHS                               number of epochs, default=10
  --device DEVICE                               cuda | cpu, default=cuda
                                                device to train on
  --device-id DEVICE_ID                         device id of gpu, default=0
  --ngpu NGPU                                   number of GPUs to use (0,1,...,ngpu-1)
  --parallel                                    use all GPUs available
  --lr LR                                       learning rate, default=1e-4
  --encoder-type ENCODER_TYPE                   type of encoder model (gru | lstm), default="gru"
  --decoder-type DECODER_TYPE                   type of decoder model (gru | lstm), default="gru"
  --num-directions NUM_DIRECTIONS               number of directions in encoder, default=2
  --encoder-num-layers ENCODER_NUM_LAYERS       number of layers in encoder, default=2
  --decoder-num-layers DECODER_NUM_LAYERS       number of layers in decoder, default=2
  --encoder-emb-size ENCODER_EMB_SIZE           embedding size of encoder, default=256
  --decoder-emb-size DECODER_EMB_SIZE           embedding size of decoder, default=256
  --encoder-hid-size ENCODER_HID_SIZE           hidden size of encoder, default=256
  --encoder-dropout ENCODER_DROPOUT             dropout rate in encoder, default=0.
  --decoder-dropout DECODER_DROPOUT             dropout rate in decoder FC layer, default=0.
  --clip-param CLIP_PARAM                       clip parameter value for exploding gradients
    --beam-size BEAM_SIZE                       Beam size to use during beam search
  --teacher-forcing-prob TEACHER_FORCING_PROB   clip parameter value for exploding gradients
  --use-attn                                    Use attention in the encoder decoder architecture
  --force                                       overwrites all existing dumped data sets