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docs/source/installation/index.rst
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@ -4,7 +4,6 @@ Installation
============
``icefall`` depends on `k2 <https://github.com/k2-fsa/k2>`_ and
`lhotse <https://github.com/lhotse-speech/lhotse>`_.
@ -27,17 +26,6 @@ We recommend that you use the following steps to install the dependencies.
99% users who have issues about the installation are using conda.
.. hint::
We suggest that you use ``pip install`` to install PyTorch.
You can use the following command to create a virutal environment in Python:
.. code-block:: bash
python3 -m venv ./my_env
source ./my_env/bin/activate
.. caution::
Installation order matters.
@ -78,14 +66,12 @@ to install ``k2``.
.. note::
We suggest that you install k2 from source by following
`<https://k2-fsa.github.io/k2/installation/from_source.html>`_
or
`<https://k2-fsa.github.io/k2/installation/for_developers.html>`_.
We suggest that you install k2 from pre-compiled wheels by following
`<https://k2-fsa.github.io/k2/installation/from_wheels.html>`_
.. hint::
Please always install the latest version of k2.
Please always install the latest version of `k2`_.
(3) Install lhotse
------------------
@ -138,47 +124,68 @@ The following shows an example about setting up the environment.
.. code-block:: bash
$ virtualenv -p python3.8 test-icefall
kuangfangjun:~$ virtualenv -p python3.8 test-icefall
created virtual environment CPython3.8.0.final.0-64 in 9422ms
creator CPython3Posix(dest=/star-fj/fangjun/test-icefall, clear=False, no_vcs_ignore=False, global=False)
seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/star-fj/fangjun/.local/share/virtualenv)
added seed packages: pip==22.3.1, setuptools==65.6.3, wheel==0.38.4
activators BashActivator,CShellActivator,FishActivator,NushellActivator,PowerShellActivator,PythonActivator
kuangfangjun:~$ source test-icefall/bin/activate
(test-icefall) kuangfangjun:~$
created virtual environment CPython3.8.6.final.0-64 in 1540ms
creator CPython3Posix(dest=/ceph-fj/fangjun/test-icefall, clear=False, no_vcs_ignore=False, global=False)
seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/root/fangjun/.local/share/v
irtualenv)
added seed packages: pip==21.1.3, setuptools==57.4.0, wheel==0.36.2
activators BashActivator,CShellActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator
(2) Install CUDA toolkit and cuDNN
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
(2) Activate your virtual environment
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
You need to determine the version of CUDA toolkit to install.
.. code-block:: bash
$ source test-icefall/bin/activate
(test-icefall) kuangfangjun:~$ nvidia-smi | head -n 4
Wed Jul 26 21:57:49 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 510.47.03 Driver Version: 510.47.03 CUDA Version: 11.6 |
|-------------------------------+----------------------+----------------------+
(3) Install k2
~~~~~~~~~~~~~~
You can choose any version that is less than the version printed by ``nvidia-smi``.
In our case, we can choose any version ``<= 11.6``.
We will use ``CUDA 10.2`` in this example. Please follow
`<https://k2-fsa.github.io/k2/installation/cuda-cudnn.html#cuda-10-2>`_
to install CUDA toolkit and cuDNN if you have not done that before.
After installing CUDA toolkit, you can use the following command to verify it:
.. code-block:: bash
$ pip install k2==1.4.dev20210822+cpu.torch1.9.0 -f https://k2-fsa.org/nightly/index.html
(test-icefall) kuangfangjun:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89
Looking in links: https://k2-fsa.org/nightly/index.html
Collecting k2==1.4.dev20210822+cpu.torch1.9.0
Downloading https://k2-fsa.org/nightly/whl/k2-1.4.dev20210822%2Bcpu.torch1.9.0-cp38-cp38-linux_x86_64.whl (1.6 MB)
|________________________________| 1.6 MB 185 kB/s
Collecting graphviz
Downloading graphviz-0.17-py3-none-any.whl (18 kB)
Collecting torch==1.9.0
Using cached torch-1.9.0-cp38-cp38-manylinux1_x86_64.whl (831.4 MB)
Collecting typing-extensions
Using cached typing_extensions-3.10.0.0-py3-none-any.whl (26 kB)
Installing collected packages: typing-extensions, torch, graphviz, k2
Successfully installed graphviz-0.17 k2-1.4.dev20210822+cpu.torch1.9.0 torch-1.9.0 typing-extensions-3.10.0.0
(3) Install torch and torchaudio
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. WARNING::
Since we have selected CUDA toolkit 10.2, you need to install a version of ``torch``
that is compiled against CUDA 10.2. We select ``torch 1.10.0+cu102`` in this
example.
We choose to install a CPU version of k2 for testing. You would probably want to install
a CUDA version of k2.
After selecting the version of ``torch`` to install, we need to also install
a compatible version of ``torchaudio``, which is ``0.10.0`` in our case.
Please refer to `<https://pytorch.org/audio/stable/installation.html#compatibility-matrix>`_
to select an appropriate version of torchaudio to install if you use a different
version of ``torch``.
.. code-block:: bash
(test-icefall) kuangfangjun:~$ pip install torch==1.11.0+cu102 torchaudio==0.11.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html
Verify that ``torch`` and ``torchaudio`` are successfully installed:
.. code-block:: bash
aa
(4) Install lhotse