Skip to content

Commit

Permalink
Merge pull request #1 from david-ryan-snyder/xvector
Browse files Browse the repository at this point in the history
Xvector
  • Loading branch information
pegahgh committed Feb 22, 2016
2 parents c5e78c7 + fbfc27b commit 33206a0
Show file tree
Hide file tree
Showing 94 changed files with 3,337 additions and 1,390 deletions.
49 changes: 25 additions & 24 deletions egs/ami/s5/cmd.sh
Original file line number Diff line number Diff line change
@@ -1,37 +1,38 @@
# "queue.pl" uses qsub. The options to it are
# options to qsub. If you have GridEngine installed,
# change this to a queue you have access to.
# Otherwise, use "run.pl", which will run jobs locally
# (make sure your --num-jobs options are no more than
# the number of cpus on your machine.
# you can change cmd.sh depending on what type of queue you are using.
# If you have no queueing system and want to run on a local machine, you
# can change all instances 'queue.pl' to run.pl (but be careful and run
# commands one by one: most recipes will exhaust the memory on your
# machine). queue.pl works with GridEngine (qsub). slurm.pl works
# with slurm. Different queues are configured differently, with different
# queue names and different ways of specifying things like memory;
# to account for these differences you can create and edit the file
# conf/queue.conf to match your queue's configuration. Search for
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.

export train_cmd="queue.pl --mem 1G"
export decode_cmd="queue.pl --mem 2G"
# the use of cuda_cmd is deprecated but it is sometimes still used in nnet1
# scripts.
export cuda_cmd="queue.pl --gpu 1 --mem 20G"

# the rest of this file is present for historical reasons.
# In general it's best to rely on conf/queue.conf for cluster-specific
# configuration.

# On Eddie use:
#export train_cmd="queue.pl -P inf_hcrc_cstr_nst -l h_rt=08:00:00"
#export decode_cmd="queue.pl -P inf_hcrc_cstr_nst -l h_rt=05:00:00 -pe memory-2G 4"
#export highmem_cmd="queue.pl -P inf_hcrc_cstr_nst -l h_rt=05:00:00 -pe memory-2G 4"
#export scoring_cmd="queue.pl -P inf_hcrc_cstr_nst -l h_rt=00:20:00"

# JSALT2015 workshop, cluster AWS-EC2, (setup from Vijay)
export train_cmd="queue.pl -l arch=*64* --mem 1G"
export decode_cmd="queue.pl -l arch=*64* --mem 2G"
export highmem_cmd="queue.pl -l arch=*64* --mem 4G"
export scoring_cmd="queue.pl -l arch=*64*"
export cuda_cmd="queue.pl --gpu 1 -l mem_free=20G,ram_free=20G"
export cntk_decode_cmd="queue.pl -l arch=*64* --mem 1G -pe smp 2"

# To run locally, use:
#export train_cmd=run.pl
#export decode_cmd=run.pl
#export highmem_cmd=run.pl
#export cuda_cmd=run.pl

if [ "$(hostname -d)" == "fit.vutbr.cz" ]; then
# BUT cluster:
queue="all.q@@blade,all.q@@speech"
gpu_queue="long.q@supergpu*,long.q@dellgpu*,long.q@pcspeech-gpu,long.q@pcgpu*"
gpu_queue="long.q@@gpu"
storage="matylda5"
export train_cmd="queue.pl -q $queue -l ram_free=1500M,mem_free=1500M,${storage}=1"
export decode_cmd="queue.pl -q $queue -l ram_free=2500M,mem_free=2500M,${storage}=0.5"
export train_cmd="queue.pl -q $queue -l ram_free=1.5G,mem_free=1.5G,${storage}=1"
export decode_cmd="queue.pl -q $queue -l ram_free=2.5G,mem_free=2.5G,${storage}=0.5"
export cuda_cmd="queue.pl -q $gpu_queue -l gpu=1"
fi
fi

26 changes: 13 additions & 13 deletions egs/ami/s5/run_ihm.sh
Original file line number Diff line number Diff line change
Expand Up @@ -10,13 +10,13 @@ mic=ihm
stage=0
. utils/parse_options.sh

# Set bash to 'debug' mode, it prints the commands (option '-x') and exits on :
# Set bash to 'debug' mode, it prints the commands (option '-x') and exits on :
# -e 'error', -u 'undefined variable', -o pipefail 'error in pipeline',
set -euxo pipefail

# Path where AMI gets downloaded (or where locally available):
AMI_DIR=$PWD/wav_db # Default,
case $(hostname -d) in
AMI_DIR=$PWD/wav_db # Default,
case $(hostname -d) in
fit.vutbr.cz) AMI_DIR=/mnt/scratch05/iveselyk/KALDI_AMI_WAV ;; # BUT,
clsp.jhu.edu) AMI_DIR=/export/corpora4/ami/amicorpus ;; # JHU,
cstr.ed.ac.uk) AMI_DIR= ;; # Edinburgh,
Expand Down Expand Up @@ -86,7 +86,7 @@ if [ $stage -le 5 ]; then
data/$mic/train data/lang exp/$mic/tri2a exp/$mic/tri2_ali
# Decode,
graph_dir=exp/$mic/tri2a/graph_${LM}
$highmem_cmd $graph_dir/mkgraph.log \
$cmd --mem 4G $graph_dir/mkgraph.log \
utils/mkgraph.sh data/lang_${LM} exp/$mic/tri2a $graph_dir
steps/decode.sh --nj $nj --cmd "$decode_cmd" --config conf/decode.conf \
$graph_dir data/$mic/dev exp/$mic/tri2a/decode_dev_${LM}
Expand All @@ -104,26 +104,26 @@ if [ $stage -le 6 ]; then
data/$mic/train data/lang exp/$mic/tri3a exp/$mic/tri3a_ali
# Decode,
graph_dir=exp/$mic/tri3a/graph_${LM}
$highmem_cmd $graph_dir/mkgraph.log \
$cmd --mem 4G $graph_dir/mkgraph.log \
utils/mkgraph.sh data/lang_${LM} exp/$mic/tri3a $graph_dir
steps/decode.sh --nj $nj --cmd "$decode_cmd" --config conf/decode.conf \
$graph_dir data/$mic/dev exp/$mic/tri3a/decode_dev_${LM}
$graph_dir data/$mic/dev exp/$mic/tri3a/decode_dev_${LM}
steps/decode.sh --nj $nj --cmd "$decode_cmd" --config conf/decode.conf \
$graph_dir data/$mic/eval exp/$mic/tri3a/decode_eval_${LM}
fi
fi

if [ $stage -le 7 ]; then
# Train tri4a, which is LDA+MLLT+SAT,
steps/train_sat.sh --cmd "$train_cmd" \
5000 80000 data/$mic/train data/lang exp/$mic/tri3a_ali exp/$mic/tri4a
# Decode,
# Decode,
graph_dir=exp/$mic/tri4a/graph_${LM}
$highmem_cmd $graph_dir/mkgraph.log \
utils/mkgraph.sh data/lang_${LM} exp/$mic/tri4a $graph_dir
steps/decode_fmllr.sh --nj $nj --cmd "$decode_cmd" --config conf/decode.conf \
$graph_dir data/$mic/dev exp/$mic/tri4a/decode_dev_${LM}
$graph_dir data/$mic/dev exp/$mic/tri4a/decode_dev_${LM}
steps/decode_fmllr.sh --nj $nj --cmd "$decode_cmd" --config conf/decode.conf \
$graph_dir data/$mic/eval exp/$mic/tri4a/decode_eval_${LM}
$graph_dir data/$mic/eval exp/$mic/tri4a/decode_eval_${LM}
fi

nj_mmi=80
Expand Down Expand Up @@ -160,11 +160,11 @@ if [ $stage -le 11 ]; then
decode_dir=exp/$mic/tri4a_mmi_b0.1/decode_dev_${i}.mdl_${LM}
steps/decode.sh --nj $nj --cmd "$decode_cmd" --config conf/decode.conf \
--transform-dir exp/$mic/tri4a/decode_dev_${LM} --iter $i \
$graph_dir data/$mic/dev $decode_dir
$graph_dir data/$mic/dev $decode_dir
decode_dir=exp/$mic/tri4a_mmi_b0.1/decode_eval_${i}.mdl_${LM}
steps/decode.sh --nj $nj --cmd "$decode_cmd" --config conf/decode.conf \
--transform-dir exp/$mic/tri4a/decode_eval_${LM} --iter $i \
$graph_dir data/$mic/eval $decode_dir
$graph_dir data/$mic/eval $decode_dir
done
fi

Expand All @@ -181,7 +181,7 @@ if [ $stage -le 13 ]; then
--hidden-dim 950 \
--splice-indexes "layer0/-2:-1:0:1:2 layer1/-1:2 layer2/-3:3 layer3/-7:2 layer4/-3:3" \
--use-sat-alignments true

local/online/run_nnet2_ms_sp_disc.sh \
--mic $mic \
--gmm-dir exp/$mic/tri4a \
Expand Down
43 changes: 16 additions & 27 deletions egs/aurora4/s5/cmd.sh
Original file line number Diff line number Diff line change
@@ -1,29 +1,18 @@
# "queue.pl" uses qsub. The options to it are
# options to qsub. If you have GridEngine installed,
# change this to a queue you have access to.
# Otherwise, use "run.pl", which will run jobs locally
# (make sure your --num-jobs options are no more than
# the number of cpus on your machine.
# you can change cmd.sh depending on what type of queue you are using.
# If you have no queueing system and want to run on a local machine, you
# can change all instances 'queue.pl' to run.pl (but be careful and run
# commands one by one: most recipes will exhaust the memory on your
# machine). queue.pl works with GridEngine (qsub). slurm.pl works
# with slurm. Different queues are configured differently, with different
# queue names and different ways of specifying things like memory;
# to account for these differences you can create and edit the file
# conf/queue.conf to match your queue's configuration. Search for
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.

#a) JHU cluster options
export train_cmd="queue.pl -l arch=*64"
export decode_cmd="queue.pl -l arch=*64 --mem 2G"
export mkgraph_cmd="queue.pl -l arch=*64 --mem 4G"
export big_memory_cmd="queue.pl -l arch=*64 --mem 8G"
export train_cmd="queue.pl --mem 4G"
export decode_cmd="queue.pl --mem 4G"
export mkgraph_cmd="queue.pl --mem 8G"
# the use of cuda_cmd is deprecated but it's still used in some example scripts
# here.
export cuda_cmd="queue.pl --gpu 1"


#b) BUT cluster options
#export train_cmd="queue.pl -q all.q@@blade -l ram_free=1200M,mem_free=1200M"
#export decode_cmd="queue.pl -q all.q@@blade -l ram_free=1700M,mem_free=1700M"
#export decodebig_cmd="queue.pl -q all.q@@blade -l ram_free=4G,mem_free=4G"

#export cuda_cmd="queue.pl -q long.q@@pco203 -l gpu=1"
#export cuda_cmd="queue.pl -q long.q@pcspeech-gpu"
#export mkgraph_cmd="queue.pl -q all.q@@servers -l ram_free=4G,mem_free=4G"

#c) run it locally...
#export train_cmd=run.pl
#export decode_cmd=run.pl
#export cuda_cmd=run.pl
#export mkgraph_cmd=run.pl
44 changes: 15 additions & 29 deletions egs/babel/s5/cmd.sh
Original file line number Diff line number Diff line change
@@ -1,29 +1,15 @@
# "queue.pl" uses qsub. The options to it are
# options to qsub. If you have GridEngine installed,
# change this to a queue you have access to.
# Otherwise, use "run.pl", which will run jobs locally
# (make sure your --num-jobs options are no more than
# the number of cpus on your machine.

#a) JHU cluster options
export train_cmd="queue.pl -l arch=*64"
export decode_cmd="queue.pl -l arch=*64,mem_free=2G,ram_free=2G"
export mkgraph_cmd="queue.pl -l arch=*64,ram_free=4G,mem_free=4G"

#export cuda_cmd="..."


#b) BUT cluster options
#export train_cmd="queue.pl -q all.q@@blade -l ram_free=1200M,mem_free=1200M"
#export decode_cmd="queue.pl -q all.q@@blade -l ram_free=1700M,mem_free=1700M"
#export decodebig_cmd="queue.pl -q all.q@@blade -l ram_free=4G,mem_free=4G"

#export cuda_cmd="queue.pl -q long.q@@pco203 -l gpu=1"
#export cuda_cmd="queue.pl -q long.q@pcspeech-gpu"
#export mkgraph_cmd="queue.pl -q all.q@@servers -l ram_free=4G,mem_free=4G"

#c) run it locally...
#export train_cmd=run.pl
#export decode_cmd=run.pl
#export cuda_cmd=run.pl
#export mkgraph_cmd=run.pl
# you can change cmd.sh depending on what type of queue you are using.
# If you have no queueing system and want to run on a local machine, you
# can change all instances 'queue.pl' to run.pl (but be careful and run
# commands one by one: most recipes will exhaust the memory on your
# machine). queue.pl works with GridEngine (qsub). slurm.pl works
# with slurm. Different queues are configured differently, with different
# queue names and different ways of specifying things like memory;
# to account for these differences you can create and edit the file
# conf/queue.conf to match your queue's configuration. Search for
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.

export train_cmd="queue.pl --mem 2G"
export decode_cmd="queue.pl --mem 4G"
export mkgraph_cmd="queue.pl --mem 8G"
44 changes: 15 additions & 29 deletions egs/babel/s5b/cmd.sh
Original file line number Diff line number Diff line change
@@ -1,29 +1,15 @@
# "queue.pl" uses qsub. The options to it are
# options to qsub. If you have GridEngine installed,
# change this to a queue you have access to.
# Otherwise, use "run.pl", which will run jobs locally
# (make sure your --num-jobs options are no more than
# the number of cpus on your machine.

#a) JHU cluster options
export train_cmd="queue.pl -l arch=*64"
export decode_cmd="queue.pl -l arch=*64,mem_free=2G,ram_free=2G"
export mkgraph_cmd="queue.pl -l arch=*64,ram_free=4G,mem_free=4G"

#export cuda_cmd="..."


#b) BUT cluster options
#export train_cmd="queue.pl -q all.q@@blade -l ram_free=1200M,mem_free=1200M"
#export decode_cmd="queue.pl -q all.q@@blade -l ram_free=1700M,mem_free=1700M"
#export decodebig_cmd="queue.pl -q all.q@@blade -l ram_free=4G,mem_free=4G"

#export cuda_cmd="queue.pl -q long.q@@pco203 -l gpu=1"
#export cuda_cmd="queue.pl -q long.q@pcspeech-gpu"
#export mkgraph_cmd="queue.pl -q all.q@@servers -l ram_free=4G,mem_free=4G"

#c) run it locally...
#export train_cmd=run.pl
#export decode_cmd=run.pl
#export cuda_cmd=run.pl
#export mkgraph_cmd=run.pl
# you can change cmd.sh depending on what type of queue you are using.
# If you have no queueing system and want to run on a local machine, you
# can change all instances 'queue.pl' to run.pl (but be careful and run
# commands one by one: most recipes will exhaust the memory on your
# machine). queue.pl works with GridEngine (qsub). slurm.pl works
# with slurm. Different queues are configured differently, with different
# queue names and different ways of specifying things like memory;
# to account for these differences you can create and edit the file
# conf/queue.conf to match your queue's configuration. Search for
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.

export train_cmd="queue.pl --mem 4G"
export decode_cmd="queue.pl --mem 4G"
export mkgraph_cmd="queue.pl --mem 8G"
44 changes: 15 additions & 29 deletions egs/babel/s5c/cmd.sh
Original file line number Diff line number Diff line change
@@ -1,29 +1,15 @@
# "queue.pl" uses qsub. The options to it are
# options to qsub. If you have GridEngine installed,
# change this to a queue you have access to.
# Otherwise, use "run.pl", which will run jobs locally
# (make sure your --num-jobs options are no more than
# the number of cpus on your machine.

#a) JHU cluster options
export train_cmd="queue.pl -l arch=*64"
export decode_cmd="queue.pl -l arch=*64,mem_free=2G,ram_free=2G"
export mkgraph_cmd="queue.pl -l arch=*64,ram_free=4G,mem_free=4G"

#export cuda_cmd="..."


#b) BUT cluster options
#export train_cmd="queue.pl -q all.q@@blade -l ram_free=1200M,mem_free=1200M"
#export decode_cmd="queue.pl -q all.q@@blade -l ram_free=1700M,mem_free=1700M"
#export decodebig_cmd="queue.pl -q all.q@@blade -l ram_free=4G,mem_free=4G"

#export cuda_cmd="queue.pl -q long.q@@pco203 -l gpu=1"
#export cuda_cmd="queue.pl -q long.q@pcspeech-gpu"
#export mkgraph_cmd="queue.pl -q all.q@@servers -l ram_free=4G,mem_free=4G"

#c) run it locally...
#export train_cmd=run.pl
#export decode_cmd=run.pl
#export cuda_cmd=run.pl
#export mkgraph_cmd=run.pl
# you can change cmd.sh depending on what type of queue you are using.
# If you have no queueing system and want to run on a local machine, you
# can change all instances 'queue.pl' to run.pl (but be careful and run
# commands one by one: most recipes will exhaust the memory on your
# machine). queue.pl works with GridEngine (qsub). slurm.pl works
# with slurm. Different queues are configured differently, with different
# queue names and different ways of specifying things like memory;
# to account for these differences you can create and edit the file
# conf/queue.conf to match your queue's configuration. Search for
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.

export train_cmd="queue.pl --mem 2G"
export decode_cmd="queue.pl --mem 4G"
export mkgraph_cmd="queue.pl --mem 8G"
28 changes: 13 additions & 15 deletions egs/bn_music_speech/v1/cmd.sh
Original file line number Diff line number Diff line change
@@ -1,17 +1,15 @@
# "queue.pl" uses qsub. The options to it are
# options to qsub. If you have GridEngine installed,
# change this to a queue you have access to.
# Otherwise, use "run.pl", which will run jobs locally
# (make sure your --num-jobs options are no more than
# the number of cpus on your machine.

#a) JHU cluster options
export train_cmd="queue.pl -l arch=*64*"

#b) BUT cluster options
#export train_cmd="queue.pl -q all.q@@blade -l ram_free=1200M,mem_free=1200M"

#c) run it locally...
#export train_cmd=run.pl
# you can change cmd.sh depending on what type of queue you are using.
# If you have no queueing system and want to run on a local machine, you
# can change all instances 'queue.pl' to run.pl (but be careful and run
# commands one by one: most recipes will exhaust the memory on your
# machine). queue.pl works with GridEngine (qsub). slurm.pl works
# with slurm. Different queues are configured differently, with different
# queue names and different ways of specifying things like memory;
# to account for these differences you can create and edit the file
# conf/queue.conf to match your queue's configuration. Search for
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.

export train_cmd="queue.pl --mem 4G"


33 changes: 15 additions & 18 deletions egs/callhome_egyptian/s5/cmd.sh
Original file line number Diff line number Diff line change
@@ -1,18 +1,15 @@
# "queue.pl" uses qsub. The options to it are
# options to qsub. If you have GridEngine installed,
# change this to a queue you have access to.
# Otherwise, use "run.pl", which will run jobs locally
# (make sure your --num-jobs options are no more than
# the number of cpus on your machine.

#train_cmd='queue.pl -q all.q@a03.clsp.jhu.edu,all.q@a06.clsp.jhu.edu,all.q@a05.clsp.jhu.edu,all.q@v01.clsp.jhu.edu,all.q@a10.clsp.jhu.edu,all.q@a04.clsp.jhu.edu,all.q@a13.clsp.jhu.edu,all.q@a11.clsp.jhu.edu -l arch=*64'
#decode_cmd='queue.pl -q all.q@a03.clsp.jhu.edu,all.q@a06.clsp.jhu.edu,all.q@a05.clsp.jhu.edu,all.q@v01.clsp.jhu.edu,all.q@a10.clsp.jhu.edu,all.q@a04.clsp.jhu.edu,all.q@a13.clsp.jhu.edu,all.q@a11.clsp.jhu.edu -l arch=*64'
train_cmd="queue.pl -l arch=*64"
decode_cmd="queue.pl -l arch=*64"
#train_cmd="run.pl"
# Do training locally. Note: for jobs on smallish subsets,
# it's way faster to run on a single machine with a handful of CPUs, as
# you avoid the latency of starting GridEngine jobs.



# you can change cmd.sh depending on what type of queue you are using.
# If you have no queueing system and want to run on a local machine, you
# can change all instances 'queue.pl' to run.pl (but be careful and run
# commands one by one: most recipes will exhaust the memory on your
# machine). queue.pl works with GridEngine (qsub). slurm.pl works
# with slurm. Different queues are configured differently, with different
# queue names and different ways of specifying things like memory;
# to account for these differences you can create and edit the file
# conf/queue.conf to match your queue's configuration. Search for
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information,
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl.

export train_cmd="queue.pl --mem 2G"
export decode_cmd="queue.pl --mem 4G"
export mkgraph_cmd="queue.pl --mem 8G"
Loading

0 comments on commit 33206a0

Please sign in to comment.