Document Reader

python scripts/reader/preprocess.py data/datasets data/datasets --split SQuAD-v1.1-train

python scripts/reader/preprocess.py data/datasets data/datasets --split SQuAD-v1.1-dev

python scripts/reader/train.py --embedding-file glove.840B.300d.txt --tune-partial 1000

Environment:
--no-cuda           Train on CPU, even if GPUs are available. (default: False)
--gpu               Run on a specific GPU (default: -1)
--data-workers      Number of subprocesses for data loading (default: 5)
--parallel          Use DataParallel on all available GPUs (default: False)
--random-seed       Random seed for all numpy/torch/cuda operations (for reproducibility).
--num-epochs        Train data iterations.
--batch-size        Batch size for training.
--test-batch-size   Batch size during validation/testing.

Filesystem:
--model-dir         Directory for saved models/checkpoints/logs (default: /tmp/drqa-models).
--model-name        Unique model identifier (.mdl, .txt, .checkpoint) (default: <generated uuid>).
--data-dir          Directory of training/validation data (default: data/datasets).
--train-file        Preprocessed train file (default: SQuAD-v1.1-train-processed-corenlp.txt).
--dev-file          Preprocessed dev file (default: SQuAD-v1.1-dev-processed-corenlp.txt).
--dev-json          Unprocessed dev file to run validation while training on (used to get original text for getting spans and answer texts) (default: SQuAD-v1.1-dev.json).
--embed-dir         Directory of pre-trained embedding files (default: data/embeddings).
--embedding-file    Space-separated pretrained embeddings file (default: None).

Saving/Loading:
--checkpoint        Save model + optimizer state after each epoch (default: False).
--pretrained        Path to a pretrained model to warm-start with (default: <empty>).
--expand-dictionary Expand dictionary of pretrained (--pretrained) model to include training/dev words of new data (default: False).

Preprocessing:
--uncased-question  Question words will be lower-cased (default: False).
--uncased-doc       Document words will be lower-cased (default: False).
--restrict-vocab    Only use pre-trained words in embedding_file (default: True).

General:
--official-eval     Validate with official SQuAD eval (default: True).
--valid-metric      The evaluation metric used for model selection (default: f1).
--display-iter      Log state after every <display_iter> epochs (default: 25).
--sort-by-len       Sort batches by length for speed (default: True).

DrQA Reader Model Architecture:
--model-type        Model architecture type (default: rnn).
--embedding-dim     Embedding size if embedding_file is not given (default: 300).
--hidden-size       Hidden size of RNN units (default: 128).
--doc-layers        Number of encoding layers for document (default: 3).
--question-layers   Number of encoding layers for question (default: 3).
--rnn-type          RNN type: LSTM, GRU, or RNN (default: lstm).

DrQA Reader Model Details:
--concat-rnn-layers Combine hidden states from each encoding layer (default: True).
--question-merge    The way of computing the question representation (default: self_attn).
--use-qemb          Whether to use weighted question embeddings (default: True).
--use-in-question   Whether to use in_question_* (cased, uncased, lemma) features (default: True).
--use-pos           Whether to use pos features (default: True).
--use-ner           Whether to use ner features (default: True).
--use-lemma         Whether to use lemma features (default: True).
--use-tf            Whether to use term frequency features (default: True).

DrQA Reader Optimization:
--dropout-emb           Dropout rate for word embeddings (default: 0.4).
--dropout-rnn           Dropout rate for RNN states (default: 0.4).
--dropout-rnn-output    Whether to dropout the RNN output (default: True).
--optimizer             Optimizer: sgd or adamax (default: adamax).
--learning-rate         Learning rate for SGD only (default: 0.1).
--grad-clipping         Gradient clipping (default: 10).
--weight-decay          Weight decay factor (default: 0).
--momentum              Momentum factor (default: 0).
--fix-embeddings        Keep word embeddings fixed (use pretrained) (default: True).
--tune-partial          Backprop through only the top N question words (default: 0).
--rnn-padding           Explicitly account for padding (and skip it) in RNN encoding (default: False).
--max-len MAX_LEN       The max span allowed during decoding (default: 15).

dataset               SQuAD-like dataset to evaluate on (format B).

--model             Path to model to use.
--embedding-file    Expand dictionary to use all pretrained embeddings in this file.
--out-dir           Directory to write prediction file to (<dataset>-<model>.preds).
--tokenizer         String option specifying tokenizer type to use (e.g. 'corenlp').
--num-workers       Number of CPU processes (for tokenizing, etc).
--no-cuda           Use CPU only.
--gpu               Specify GPU device id to use.
--batch-size        Example batching size (Reduce in case of OOM).
--top-n             Store top N predicted spans per example.
--official          Only store single top span instead of top N list. (The SQuAD eval script takes a dict of qid: span).

python scripts/reader/official_eval.py /path/to/format/B/dataset.json /path/to/predictions/with/--official/flag/set.json

python scripts/reader/interactive.py --model /path/to/model

>>> text = "Mary had a little lamb, whose fleece was white as snow. And everywhere that Mary went the lamb was sure to go."
>>> question = "What color is Mary's lamb?"
>>> process(text, question)

+------+-------+---------+
| Rank |  Span |  Score  |
+------+-------+---------+
|  1   | white | 0.78002 |
+------+-------+---------+