Add doc describing how to run icefall within a docker container (#1194)

docs/source/docker/index.rst

@@ -0,0 +1,17 @@
+.. _icefall_docker:
+
+Docker
+======
+
+This section describes how to use pre-built docker images to run `icefall`_.
+
+.. hint::
+
+   If you only have CPUs available, you can still use the pre-built docker
+   images.
+
+.. toctree::
+   :maxdepth: 2
+
+   ./intro.rst
+

docs/source/docker/intro.rst

@@ -0,0 +1,171 @@
+Introduction
+=============
+
+We have pre-built docker images hosted at the following address:
+
+  `<https://hub.docker.com/repository/docker/k2fsa/icefall/general>`_
+
+.. figure:: img/docker-hub.png
+   :width: 600
+   :align: center
+
+You can find the ``Dockerfile`` at `<https://github.com/k2-fsa/icefall/tree/master/docker>`_.
+
+We describe the following items in this section:
+
+  - How to view available tags
+  - How to download pre-built docker images
+  - How to run the `yesno`_ recipe within a docker container on ``CPU``
+
+View available tags
+===================
+
+You can use the following command to view available tags:
+
+.. code-block:: bash
+
+   curl -s 'https://registry.hub.docker.com/v2/repositories/k2fsa/icefall/tags/'|jq '."results"[]["name"]'
+
+which will give you something like below:
+
+.. code-block:: bash
+
+  "torch2.0.0-cuda11.7"
+  "torch1.12.1-cuda11.3"
+  "torch1.9.0-cuda10.2"
+  "torch1.13.0-cuda11.6"
+
+.. hint::
+
+   Available tags will be updated when there are new releases of `torch`_.
+
+Please select an appropriate combination of `torch`_ and  CUDA.
+
+Download a docker image
+=======================
+
+Suppose that you select the tag ``torch1.13.0-cuda11.6``, you can use
+the following command to download it:
+
+.. code-block:: bash
+
+   sudo docker image pull k2fsa/icefall:torch1.13.0-cuda11.6
+
+Run a docker image with GPU
+===========================
+
+.. code-block:: bash
+
+  sudo docker run --gpus all --rm -it k2fsa/icefall:torch1.13.0-cuda11.6 /bin/bash
+
+Run a docker image with CPU
+===========================
+
+.. code-block:: bash
+
+  sudo docker run --rm -it k2fsa/icefall:torch1.13.0-cuda11.6 /bin/bash
+
+Run yesno within a docker container
+===================================
+
+After starting the container, the following interface is presented:
+
+.. code-block:: bash
+
+  root@60c947eac59c:/workspace/icefall#
+
+It shows the current user is ``root`` and the current working directory
+is ``/workspace/icefall``.
+
+Update the code
+---------------
+
+Please first run:
+
+.. code-block:: bash
+
+  root@60c947eac59c:/workspace/icefall# git pull
+
+so that your local copy contains the latest code.
+
+Data preparation
+----------------
+
+Now we can use
+
+.. code-block:: bash
+
+  root@60c947eac59c:/workspace/icefall# cd egs/yesno/ASR/
+
+to switch to the ``yesno`` recipe and run
+
+.. code-block:: bash
+
+  root@60c947eac59c:/workspace/icefall/egs/yesno/ASR# ./prepare.sh
+
+.. hint::
+
+   If you are running without GPU, it may report the following error:
+
+    .. code-block:: bash
+
+        File "/opt/conda/lib/python3.9/site-packages/k2/__init__.py", line 23, in <module>
+          from _k2 import DeterminizeWeightPushingType
+        ImportError: libcuda.so.1: cannot open shared object file: No such file or directory
+
+  We can use the following command to fix it:
+
+    .. code-block:: bash
+
+      root@60c947eac59c:/workspace/icefall/egs/yesno/ASR# ln -s /opt/conda/lib/stubs/libcuda.so /opt/conda/lib/stubs/libcuda.so.1
+
+The logs of running ``./prepare.sh`` are listed below:
+
+.. literalinclude:: ./log/log-preparation.txt
+
+Training
+--------
+
+After preparing the data, we can start training with the following command
+
+.. code-block:: bash
+
+  root@60c947eac59c:/workspace/icefall/egs/yesno/ASR# ./tdnn/train.py
+
+All of the training logs are given below:
+
+.. hint::
+
+   It is running on CPU and it takes only 16 seconds for this run.
+
+.. literalinclude:: ./log/log-train-2023-08-01-01-55-27
+
+
+Decoding
+--------
+
+After training, we can decode the trained model with
+
+.. code-block:: bash
+
+  root@60c947eac59c:/workspace/icefall/egs/yesno/ASR# ./tdnn/decode.py
+
+The decoding logs are given below:
+
+.. code-block:: bash
+
+  2023-08-01 02:06:22,400 INFO [decode.py:263] Decoding started
+  2023-08-01 02:06:22,400 INFO [decode.py:264] {'exp_dir': PosixPath('tdnn/exp'), 'lang_dir': PosixPath('data/lang_phone'), 'lm_dir': PosixPath('data/lm'), 'feature_dim': 23, 'search_beam': 20, 'output_beam': 8, 'min_active_states': 30, 'max_active_states': 10000, 'use_double_scores': True, 'epoch': 14, 'avg': 2, 'export': False, 'feature_dir': PosixPath('data/fbank'), 'max_duration': 30.0, 'bucketing_sampler': False, 'num_buckets': 10, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': False, 'return_cuts': True, 'num_workers': 2, 'env_info': {'k2-version': '1.24.3', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '4c05309499a08454997adf500b56dcc629e35ae5', 'k2-git-date': 'Tue Jul 25 16:23:36 2023', 'lhotse-version': '1.16.0.dev+git.7640d663.clean', 'torch-version': '1.13.0', 'torch-cuda-available': False, 'torch-cuda-version': '11.6', 'python-version': '3.9', 'icefall-git-branch': 'master', 'icefall-git-sha1': '375520d-clean', 'icefall-git-date': 'Fri Jul 28 07:43:08 2023', 'icefall-path': '/workspace/icefall', 'k2-path': '/opt/conda/lib/python3.9/site-packages/k2/__init__.py', 'lhotse-path': '/opt/conda/lib/python3.9/site-packages/lhotse/__init__.py', 'hostname': '60c947eac59c', 'IP address': '172.17.0.2'}}
+  2023-08-01 02:06:22,401 INFO [lexicon.py:168] Loading pre-compiled data/lang_phone/Linv.pt
+  2023-08-01 02:06:22,403 INFO [decode.py:273] device: cpu
+  2023-08-01 02:06:22,406 INFO [decode.py:291] averaging ['tdnn/exp/epoch-13.pt', 'tdnn/exp/epoch-14.pt']
+  2023-08-01 02:06:22,424 INFO [asr_datamodule.py:218] About to get test cuts
+  2023-08-01 02:06:22,425 INFO [asr_datamodule.py:252] About to get test cuts
+  2023-08-01 02:06:22,504 INFO [decode.py:204] batch 0/?, cuts processed until now is 4
+  [W NNPACK.cpp:53] Could not initialize NNPACK! Reason: Unsupported hardware.
+  2023-08-01 02:06:22,687 INFO [decode.py:241] The transcripts are stored in tdnn/exp/recogs-test_set.txt
+  2023-08-01 02:06:22,688 INFO [utils.py:564] [test_set] %WER 0.42% [1 / 240, 0 ins, 1 del, 0 sub ]
+  2023-08-01 02:06:22,690 INFO [decode.py:249] Wrote detailed error stats to tdnn/exp/errs-test_set.txt
+  2023-08-01 02:06:22,690 INFO [decode.py:316] Done!
+
+Congratulations! You have finished successfully running `icefall`_ within a docker container.

docs/source/index.rst

@@ -21,9 +21,11 @@ speech recognition recipes using `k2 <https://github.com/k2-fsa/k2>`_.
    :caption: Contents:
 
    installation/index
+   docker/index
    faqs
    model-export/index
 
+
 .. toctree::
    :maxdepth: 3
 
@@ -38,4 +40,4 @@ speech recognition recipes using `k2 <https://github.com/k2-fsa/k2>`_.
 .. toctree::
    :maxdepth: 2
    
-   decoding-with-langugage-models/index
+   decoding-with-langugage-models/index

docs/source/installation/index.rst

@@ -3,6 +3,11 @@
 Installation
 ============
 
+.. hint::
+
+   We also provide :ref:`icefall_docker` support, which has already setup
+   the environment for you.
+
 .. hint::
 
   We have a colab notebook guiding you step by step to setup the environment.