Authors:
Introduction
The code contains different implementations of sequence to sequence models:
DataSet
To prepare the dataset, see ExampleGen in data.py about the data format.
data/data contains a toy example. Also see data/vocab
for example vocabulary format.
data/data_convert_example.py contains example of convert between binary and text.
How To Run
Pre-requesite:
Install TensorFlow and Bazel.
# cd to your workspace
# 1. Clone the text2text code to your workspace 'text2text' directory.
# 2. Create an empty 'WORKSPACE' file in your workspace.
# 3. Preapre the config file wrt the model you wish to run and put it in the
# config directory.
ls -R
.:
text2text WORKSPACE
./text2text:
batch_reader beam_search.py BUILD config data data.py decode.py
__init__.py library.py main.py metrics.py model README.md
./text2text/batch_reader:
copynet_batcher.py __init__.py vocab_batcher.py
./text2text/config:
cfg_copynet.py cfg_seq2seq.py cfg_bow2seq.py
__init__.py
./text2text/model:
copynet.py __init__.py seq2seq.py bow2seq.py
./text2text/data:
data data_convert_example.py text_data vocab
bazel build -c opt --copt=-mavx --config=cuda text2text:main
# Run the training.
bazel-bin/text2text/main \
--mode=train \
--config="cfg_seq2seq" \
--log_root="text2text/log_root" \
--override="eval_interval_secs=0" \
--logtostderr
# Run the eval. Try to avoid running on the same machine as training.
bazel-bin/text2text/main \
--mode=eval \
--config="cfg_seq2seq" \
--log_root="text2text/log_root" \
--logtostderr
# Run the decode. Run it when the model is mostly converged.
bazel-bin/text2text/main \
--mode=decode \
--config="cfg_seq2seq" \
--log_root="text2text/log_root" \
--logtostderr--config="config_file_name" determines the config file from the config dir
in which the model you wish to run, paths to data, and
hyperparameters of the model are specified. There are sample config files for
each models in config directory. The output of the code and summaries will be
written to a text2text/config_file_name directory.