Custom dataset training

(Hema Sree543) #1

I have the importer ready for my custom dataset. Could somebody assist me with the training part.

i run ./bin/
it says fle does not exist though it’s present

Am i doing it right?

(kdavis) #2

Could you show us and the error you are getting?

(Hema Sree543) #3

I could fix that. But now i’m getting a new error when i run the same command

  • [ ! -f ]
  • [ ! -f data/ldc93s1/finalimport.csv ]
  • [ -d ]
  • python -c from xdg import BaseDirectory as xdg; print(xdg.save_data_path(“deepspeech/ldc93s1”))
  • checkpoint_dir=/home/ubuntu/.local/share/deepspeech/ldc93s1
  • python -u --train_files data/ldc93s1/finalimport.csv --dev_files data/ldc93s1/finalimport.csv --test_files data/ldc93s1/finalimport.csv --train_batch_size 1 --dev_batch_size 1 --test_batch_size 1 --n_hidden 494 --epoch 50 --checkpoint_dir /home/ubuntu/.local/share/deepspeech/ldc93s1
    Traceback (most recent call last):
    File “”, line 1838, in
    File “/home/ubuntu/saii/local/lib/python2.7/site-packages/tensorflow/python/platform/”, line 124, in run
    File “”, line 1790, in main
    File “”, line 180, in initialize_globals
    COORD = TrainingCoordinator()
    File “”, line 1130, in init
    self._httpd = BaseHTTPServer.HTTPServer((FLAGS.coord_host, FLAGS.coord_port), TrainingCoordinator.TrainingCoordinationHandler)
    File “/usr/lib/python2.7/”, line 417, in init
    File “/usr/lib/python2.7/”, line 108, in server_bind
    File “/usr/lib/python2.7/”, line 431, in server_bind
    File “/usr/lib/python2.7/”, line 228, in meth
    return getattr(self._sock,name)(*args)
    socket.error: [Errno 98] Address already in use

My content:

set -xe
if [ ! -f ]; then
echo "Please make sure you run this from DeepSpeech’s top level directory."
exit 1

if [ ! -f “data/ldc93s1/finalimport.csv” ]; then
echo "Downloading and preprocessing LDC93S1 example data, saving in ./data/ldc93s1."
python -u bin/ ./data/ldc93s1

if [ -d “${COMPUTE_KEEP_DIR}” ]; then
checkpoint_dir=$(python -c ‘from xdg import BaseDirectory as xdg; print(xdg.save_data_path(“deepspeech/ldc93s1”))’)

python -u
–train_files data/ldc93s1/finalimport.csv
–dev_files data/ldc93s1/finalimport.csv
–test_files data/ldc93s1/finalimport.csv
–train_batch_size 1308
–dev_batch_size 1308
–test_batch_size 1308
–n_hidden 494
–epoch 50
–checkpoint_dir “$checkpoint_dir”

(kdavis) #4

It looks like the default port 2500 is in use.

Try using another port, say 3247, by passing the --coord_port 3247 argument to

(kdavis) #5

As a follow-on comment, are you sure all old runs of have completed?