* fix doc link

* fix install

* fix install doc

* fix typo

* fix lm doc

* when loss div batchsize, change lr, more epoch, loss can reduce more and cer lower than before

* since loss reduce more when loss div batchsize,  less lm alpha can be better.

* less lm alpha, more cer reduce

* alpha 2.2, cer 0.077478

* alpha 1.9, cer 0.077249

* large librispeech lr for batch_average ctc loss

* since loss reduce and model more confidence, then less lm alpha

* fix egs

* fix log

* add acts, refactor ctc, add pos embed

* fix export, dataloader time log

* fix egs

* fix libri readme

* 2.x model

* model test pass

* fix data

* fix soundfile with flac support

* one thread dataloader test pass

* export feasture size
add trainer and utils
add setup model and dataloader
update travis using Bionic dist

* add venv; test under venv

* fix unittest; train and valid

* add train and config

* add config and train script

* fix ctc cuda memcopy error

* fix imports

* fix train valid log

* fix dataset batch shuffle shift start from 1
fix rank_zero_only decreator error
close tensorboard when train over
add decoding config and code

* test process can run

* test with decoding

* test and infer with decoding

* fix infer

* fix ctc loss
lr schedule
sortagrad
logger

* aishell egs

* refactor train
add aishell egs

* fix dataset batch shuffle and add batch sampler log
print model parameter

* fix model and ctc

* sequence_mask make all inputs zeros, which cause grad be zero, this is a bug of LessThanOp
add grad clip by global norm
add model train test notebook

* ctc loss
remove run prefix
using ord value as text id

* using unk when training
compute_loss need text ids
ord id using in test mode, which compute wer/cer

* fix tester

* add lr_deacy
refactor code

* fix tools

* fix ci
add tune
fix gru model bugs
add dataset and model test

* fix decoding

* refactor repo
fix decoding

* fix musan and rir dataset

* refactor io, loss, conv, rnn, gradclip, model, utils

* fix ci and import

* refactor model
add export jit model

* add deploy bin and test it

* rm uselss egs

* add layer tools

* refactor socket server
new model from pretrain

* remve useless

* fix instability loss and grad nan or inf for librispeech training

* fix sampler

* fix libri train.sh

* fix doc

* add license on cpp

* fix doc

* fix libri script

* fix install

* clip 5 wer 7.39, clip 400 wer 7.54, 1.8 clip 400 baseline 7.49

refactor egs & add licences

upgrade to python3

update data source and remove useless code