| .. _install icefall: | |
| 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. | |
| |yesno colab notebook| | |
| .. |yesno colab notebook| image:: https://colab.research.google.com/assets/colab-badge.svg | |
| :target: https://colab.research.google.com/drive/1tIjjzaJc3IvGyKiMCDWO-TSnBgkcuN3B?usp=sharing | |
| `icefall`_ depends on `k2`_ and `lhotse`_. | |
| We recommend that you use the following steps to install the dependencies. | |
| - (0) Install CUDA toolkit and cuDNN | |
| - (1) Install `torch`_ and `torchaudio`_ | |
| - (2) Install `k2`_ | |
| - (3) Install `lhotse`_ | |
| .. caution:: | |
| Installation order matters. | |
| (0) Install CUDA toolkit and cuDNN | |
| ---------------------------------- | |
| Please refer to | |
| `<https://k2-fsa.github.io/k2/installation/cuda-cudnn.html>`_ | |
| to install CUDA and cuDNN. | |
| (1) Install torch and torchaudio | |
| -------------------------------- | |
| Please refer `<https://pytorch.org/>`_ to install `torch`_ and `torchaudio`_. | |
| .. caution:: | |
| Please install torch and torchaudio at the same time. | |
| (2) Install k2 | |
| -------------- | |
| Please refer to `<https://k2-fsa.github.io/k2/installation/index.html>`_ | |
| to install `k2`_. | |
| .. caution:: | |
| Please don't change your installed PyTorch after you have installed k2. | |
| .. note:: | |
| 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`_. | |
| (3) Install lhotse | |
| ------------------ | |
| Please refer to `<https://lhotse.readthedocs.io/en/latest/getting-started.html#installation>`_ | |
| to install `lhotse`_. | |
| .. hint:: | |
| We strongly recommend you to use:: | |
| pip install git+https://github.com/lhotse-speech/lhotse | |
| to install the latest version of `lhotse`_. | |
| (4) Download icefall | |
| -------------------- | |
| `icefall`_ is a collection of Python scripts; what you need is to download it | |
| and set the environment variable ``PYTHONPATH`` to point to it. | |
| Assume you want to place `icefall`_ in the folder ``/tmp``. The | |
| following commands show you how to setup `icefall`_: | |
| .. code-block:: bash | |
| cd /tmp | |
| git clone https://github.com/k2-fsa/icefall | |
| cd icefall | |
| pip install -r requirements.txt | |
| export PYTHONPATH=/tmp/icefall:$PYTHONPATH | |
| .. HINT:: | |
| You can put several versions of `icefall`_ in the same virtual environment. | |
| To switch among different versions of `icefall`_, just set ``PYTHONPATH`` | |
| to point to the version you want. | |
| Installation example | |
| -------------------- | |
| The following shows an example about setting up the environment. | |
| (1) Create a virtual environment | |
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | |
| .. code-block:: bash | |
| kuangfangjun:~$ 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:~$ | |
| (2) Install CUDA toolkit and cuDNN | |
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | |
| You need to determine the version of CUDA toolkit to install. | |
| .. code-block:: bash | |
| (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 | | |
| |-------------------------------+----------------------+----------------------+ | |
| You can choose any CUDA version that is ``not`` greater than the version printed by ``nvidia-smi``. | |
| In our case, we can choose any version ``<= 11.6``. | |
| We will use ``CUDA 11.6`` in this example. Please follow | |
| `<https://k2-fsa.github.io/k2/installation/cuda-cudnn.html#cuda-11-6>`_ | |
| 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 | |
| (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 | |
| (3) Install torch and torchaudio | |
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | |
| Since we have selected CUDA toolkit ``11.6``, we have to install a version of `torch`_ | |
| that is compiled against CUDA ``11.6``. We select ``torch 1.13.0+cu116`` in this | |
| example. | |
| After selecting the version of `torch`_ to install, we need to also install | |
| a compatible version of `torchaudio`_, which is ``0.13.0+cu116`` 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==1.13.0+cu116 torchaudio==0.13.0+cu116 -f https://download.pytorch.org/whl/torch_stable.html | |
| Looking in links: https://download.pytorch.org/whl/torch_stable.html | |
| Collecting torch==1.13.0+cu116 | |
| Downloading https://download.pytorch.org/whl/cu116/torch-1.13.0%2Bcu116-cp38-cp38-linux_x86_64.whl (1983.0 MB) | |
| ________________________________________ 2.0/2.0 GB 764.4 kB/s eta 0:00:00 | |
| Collecting torchaudio==0.13.0+cu116 | |
| Downloading https://download.pytorch.org/whl/cu116/torchaudio-0.13.0%2Bcu116-cp38-cp38-linux_x86_64.whl (4.2 MB) | |
| ________________________________________ 4.2/4.2 MB 1.3 MB/s eta 0:00:00 | |
| Requirement already satisfied: typing-extensions in /star-fj/fangjun/test-icefall/lib/python3.8/site-packages (from torch==1.13.0+cu116) (4.7.1) | |
| Installing collected packages: torch, torchaudio | |
| Successfully installed torch-1.13.0+cu116 torchaudio-0.13.0+cu116 | |
| Verify that `torch`_ and `torchaudio`_ are successfully installed: | |
| .. code-block:: bash | |
| (test-icefall) kuangfangjun:~$ python3 -c "import torch; print(torch.__version__)" | |
| 1.13.0+cu116 | |
| (test-icefall) kuangfangjun:~$ python3 -c "import torchaudio; print(torchaudio.__version__)" | |
| 0.13.0+cu116 | |
| (4) Install k2 | |
| ~~~~~~~~~~~~~~ | |
| We will install `k2`_ from pre-compiled wheels by following | |
| `<https://k2-fsa.github.io/k2/installation/from_wheels.html>`_ | |
| .. code-block:: bash | |
| (test-icefall) kuangfangjun:~$ pip install k2==1.24.3.dev20230725+cuda11.6.torch1.13.0 -f https://k2-fsa.github.io/k2/cuda.html | |
| # For users from China | |
| # 中国国内用户，如果访问不了 huggingface, 请使用 | |
| # pip install k2==1.24.3.dev20230725+cuda11.6.torch1.13.0 -f https://k2-fsa.github.io/k2/cuda-cn.html | |
| Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple | |
| Looking in links: https://k2-fsa.github.io/k2/cuda.html | |
| Collecting k2==1.24.3.dev20230725+cuda11.6.torch1.13.0 | |
| Downloading https://huggingface.co/csukuangfj/k2/resolve/main/ubuntu-cuda/k2-1.24.3.dev20230725%2Bcuda11.6.torch1.13.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (104.3 MB) | |
| ________________________________________ 104.3/104.3 MB 5.1 MB/s eta 0:00:00 | |
| Requirement already satisfied: torch==1.13.0 in /star-fj/fangjun/test-icefall/lib/python3.8/site-packages (from k2==1.24.3.dev20230725+cuda11.6.torch1.13.0) (1.13.0+cu116) | |
| Collecting graphviz | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/de/5e/fcbb22c68208d39edff467809d06c9d81d7d27426460ebc598e55130c1aa/graphviz-0.20.1-py3-none-any.whl (47 kB) | |
| Requirement already satisfied: typing-extensions in /star-fj/fangjun/test-icefall/lib/python3.8/site-packages (from torch==1.13.0->k2==1.24.3.dev20230725+cuda11.6.torch1.13.0) (4.7.1) | |
| Installing collected packages: graphviz, k2 | |
| Successfully installed graphviz-0.20.1 k2-1.24.3.dev20230725+cuda11.6.torch1.13.0 | |
| .. hint:: | |
| Please refer to `<https://k2-fsa.github.io/k2/cuda.html>`_ for the available | |
| pre-compiled wheels about `k2`_. | |
| Verify that `k2`_ has been installed successfully: | |
| .. code-block:: bash | |
| (test-icefall) kuangfangjun:~$ python3 -m k2.version | |
| Collecting environment information... | |
| k2 version: 1.24.3 | |
| Build type: Release | |
| Git SHA1: 4c05309499a08454997adf500b56dcc629e35ae5 | |
| Git date: Tue Jul 25 16:23:36 2023 | |
| Cuda used to build k2: 11.6 | |
| cuDNN used to build k2: 8.3.2 | |
| Python version used to build k2: 3.8 | |
| OS used to build k2: CentOS Linux release 7.9.2009 (Core) | |
| CMake version: 3.27.0 | |
| GCC version: 9.3.1 | |
| CMAKE_CUDA_FLAGS: -Wno-deprecated-gpu-targets -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_35,code=sm_35 -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_50,code=sm_50 -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_60,code=sm_60 -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_61,code=sm_61 -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_70,code=sm_70 -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_75,code=sm_75 -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_80,code=sm_80 -lineinfo --expt-extended-lambda -use_fast_math -Xptxas=-w --expt-extended-lambda -gencode arch=compute_86,code=sm_86 -DONNX_NAMESPACE=onnx_c2 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=integer_sign_change,--diag_suppress=useless_using_declaration,--diag_suppress=set_but_not_used,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=implicit_return_from_non_void_function,--diag_suppress=unsigned_compare_with_zero,--diag_suppress=declared_but_not_referenced,--diag_suppress=bad_friend_decl --expt-relaxed-constexpr --expt-extended-lambda -D_GLIBCXX_USE_CXX11_ABI=0 --compiler-options -Wall --compiler-options -Wno-strict-overflow --compiler-options -Wno-unknown-pragmas | |
| CMAKE_CXX_FLAGS: -D_GLIBCXX_USE_CXX11_ABI=0 -Wno-unused-variable -Wno-strict-overflow | |
| PyTorch version used to build k2: 1.13.0+cu116 | |
| PyTorch is using Cuda: 11.6 | |
| NVTX enabled: True | |
| With CUDA: True | |
| Disable debug: True | |
| Sync kernels : False | |
| Disable checks: False | |
| Max cpu memory allocate: 214748364800 bytes (or 200.0 GB) | |
| k2 abort: False | |
| __file__: /star-fj/fangjun/test-icefall/lib/python3.8/site-packages/k2/version/version.py | |
| _k2.__file__: /star-fj/fangjun/test-icefall/lib/python3.8/site-packages/_k2.cpython-38-x86_64-linux-gnu.so | |
| (5) Install lhotse | |
| ~~~~~~~~~~~~~~~~~~ | |
| .. code-block:: bash | |
| (test-icefall) kuangfangjun:~$ pip install git+https://github.com/lhotse-speech/lhotse | |
| Collecting git+https://github.com/lhotse-speech/lhotse | |
| Cloning https://github.com/lhotse-speech/lhotse to /tmp/pip-req-build-vq12fd5i | |
| Running command git clone --filter=blob:none --quiet https://github.com/lhotse-speech/lhotse /tmp/pip-req-build-vq12fd5i | |
| Resolved https://github.com/lhotse-speech/lhotse to commit 7640d663469b22cd0b36f3246ee9b849cd25e3b7 | |
| Installing build dependencies ... done | |
| Getting requirements to build wheel ... done | |
| Preparing metadata (pyproject.toml) ... done | |
| Collecting cytoolz>=0.10.1 | |
| Downloading https://pypi.tuna.tsinghua.edu.cn/packages/1e/3b/a7828d575aa17fb7acaf1ced49a3655aa36dad7e16eb7e6a2e4df0dda76f/cytoolz-0.12.2-cp38-cp38- | |
| manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0 MB) | |
| ________________________________________ 2.0/2.0 MB 33.2 MB/s eta 0:00:00 | |
| Collecting pyyaml>=5.3.1 | |
| Downloading https://pypi.tuna.tsinghua.edu.cn/packages/c8/6b/6600ac24725c7388255b2f5add93f91e58a5d7efaf4af244fdbcc11a541b/PyYAML-6.0.1-cp38-cp38-ma | |
| nylinux_2_17_x86_64.manylinux2014_x86_64.whl (736 kB) | |
| ________________________________________ 736.6/736.6 kB 38.6 MB/s eta 0:00:00 | |
| Collecting dataclasses | |
| Downloading https://pypi.tuna.tsinghua.edu.cn/packages/26/2f/1095cdc2868052dd1e64520f7c0d5c8c550ad297e944e641dbf1ffbb9a5d/dataclasses-0.6-py3-none- | |
| any.whl (14 kB) | |
| Requirement already satisfied: torchaudio in ./test-icefall/lib/python3.8/site-packages (from lhotse==1.16.0.dev0+git.7640d66.clean) (0.13.0+cu116) | |
| Collecting lilcom>=1.1.0 | |
| Downloading https://pypi.tuna.tsinghua.edu.cn/packages/a8/65/df0a69c52bd085ca1ad4e5c4c1a5c680e25f9477d8e49316c4ff1e5084a4/lilcom-1.7-cp38-cp38-many | |
| linux_2_17_x86_64.manylinux2014_x86_64.whl (87 kB) | |
| ________________________________________ 87.1/87.1 kB 8.7 MB/s eta 0:00:00 | |
| Collecting tqdm | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/e6/02/a2cff6306177ae6bc73bc0665065de51dfb3b9db7373e122e2735faf0d97/tqdm-4.65.0-py3-none-any | |
| .whl (77 kB) | |
| Requirement already satisfied: numpy>=1.18.1 in ./test-icefall/lib/python3.8/site-packages (from lhotse==1.16.0.dev0+git.7640d66.clean) (1.24.4) | |
| Collecting audioread>=2.1.9 | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/5d/cb/82a002441902dccbe427406785db07af10182245ee639ea9f4d92907c923/audioread-3.0.0.tar.gz ( | |
| 377 kB) | |
| Preparing metadata (setup.py) ... done | |
| Collecting tabulate>=0.8.1 | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/40/44/4a5f08c96eb108af5cb50b41f76142f0afa346dfa99d5296fe7202a11854/tabulate-0.9.0-py3-none- | |
| any.whl (35 kB) | |
| Collecting click>=7.1.1 | |
| Downloading https://pypi.tuna.tsinghua.edu.cn/packages/1a/70/e63223f8116931d365993d4a6b7ef653a4d920b41d03de7c59499962821f/click-8.1.6-py3-none-any. | |
| whl (97 kB) | |
| ________________________________________ 97.9/97.9 kB 8.4 MB/s eta 0:00:00 | |
| Collecting packaging | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/ab/c3/57f0601a2d4fe15de7a553c00adbc901425661bf048f2a22dfc500caf121/packaging-23.1-py3-none- | |
| any.whl (48 kB) | |
| Collecting intervaltree>=3.1.0 | |
| Downloading https://pypi.tuna.tsinghua.edu.cn/packages/50/fb/396d568039d21344639db96d940d40eb62befe704ef849b27949ded5c3bb/intervaltree-3.1.0.tar.gz | |
| (32 kB) | |
| Preparing metadata (setup.py) ... done | |
| Requirement already satisfied: torch in ./test-icefall/lib/python3.8/site-packages (from lhotse==1.16.0.dev0+git.7640d66.clean) (1.13.0+cu116) | |
| Collecting SoundFile>=0.10 | |
| Downloading https://pypi.tuna.tsinghua.edu.cn/packages/ad/bd/0602167a213d9184fc688b1086dc6d374b7ae8c33eccf169f9b50ce6568c/soundfile-0.12.1-py2.py3- | |
| none-manylinux_2_17_x86_64.whl (1.3 MB) | |
| ________________________________________ 1.3/1.3 MB 46.5 MB/s eta 0:00:00 | |
| Collecting toolz>=0.8.0 | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7f/5c/922a3508f5bda2892be3df86c74f9cf1e01217c2b1f8a0ac4841d903e3e9/toolz-0.12.0-py3-none-any.whl (55 kB) | |
| Collecting sortedcontainers<3.0,>=2.0 | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/32/46/9cb0e58b2deb7f82b84065f37f3bffeb12413f947f9388e4cac22c4621ce/sortedcontainers-2.4.0-py2.py3-none-any.whl (29 kB) | |
| Collecting cffi>=1.0 | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/8b/06f30caa03b5b3ac006de4f93478dbd0239e2a16566d81a106c322dc4f79/cffi-1.15.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (442 kB) | |
| Requirement already satisfied: typing-extensions in ./test-icefall/lib/python3.8/site-packages (from torch->lhotse==1.16.0.dev0+git.7640d66.clean) (4.7.1) | |
| Collecting pycparser | |
| Using cached https://pypi.tuna.tsinghua.edu.cn/packages/62/d5/5f610ebe421e85889f2e55e33b7f9a6795bd982198517d912eb1c76e1a53/pycparser-2.21-py2.py3-none-any.whl (118 kB) | |
| Building wheels for collected packages: lhotse, audioread, intervaltree | |
| Building wheel for lhotse (pyproject.toml) ... done | |
| Created wheel for lhotse: filename=lhotse-1.16.0.dev0+git.7640d66.clean-py3-none-any.whl size=687627 sha256=cbf0a4d2d0b639b33b91637a4175bc251d6a021a069644ecb1a9f2b3a83d072a | |
| Stored in directory: /tmp/pip-ephem-wheel-cache-wwtk90_m/wheels/7f/7a/8e/a0bf241336e2e3cb573e1e21e5600952d49f5162454f2e612f | |
| Building wheel for audioread (setup.py) ... done | |
| Created wheel for audioread: filename=audioread-3.0.0-py3-none-any.whl size=23704 sha256=5e2d3537c96ce9cf0f645a654c671163707bf8cb8d9e358d0e2b0939a85ff4c2 | |
| Stored in directory: /star-fj/fangjun/.cache/pip/wheels/e2/c3/9c/f19ae5a03f8862d9f0776b0c0570f1fdd60a119d90954e3f39 | |
| Building wheel for intervaltree (setup.py) ... done | |
| Created wheel for intervaltree: filename=intervaltree-3.1.0-py2.py3-none-any.whl size=26098 sha256=2604170976cfffe0d2f678cb1a6e5b525f561cd50babe53d631a186734fec9f9 | |
| Stored in directory: /star-fj/fangjun/.cache/pip/wheels/f3/ed/2b/c179ebfad4e15452d6baef59737f27beb9bfb442e0620f7271 | |
| Successfully built lhotse audioread intervaltree | |
| Installing collected packages: sortedcontainers, dataclasses, tqdm, toolz, tabulate, pyyaml, pycparser, packaging, lilcom, intervaltree, click, audioread, cytoolz, cffi, SoundFile, lhotse | |
| Successfully installed SoundFile-0.12.1 audioread-3.0.0 cffi-1.15.1 click-8.1.6 cytoolz-0.12.2 dataclasses-0.6 intervaltree-3.1.0 lhotse-1.16.0.dev0+git.7640d66.clean lilcom-1.7 packaging-23.1 pycparser-2.21 pyyaml-6.0.1 sortedcontainers-2.4.0 tabulate-0.9.0 toolz-0.12.0 tqdm-4.65.0 | |
| Verify that `lhotse`_ has been installed successfully: | |
| .. code-block:: bash | |
| (test-icefall) kuangfangjun:~$ python3 -c "import lhotse; print(lhotse.__version__)" | |
| 1.16.0.dev+git.7640d66.clean | |
| (6) Download icefall | |
| ~~~~~~~~~~~~~~~~~~~~ | |
| .. code-block:: bash | |
| (test-icefall) kuangfangjun:~$ cd /tmp/ | |
| (test-icefall) kuangfangjun:tmp$ git clone https://github.com/k2-fsa/icefall | |
| Cloning into 'icefall'... | |
| remote: Enumerating objects: 12942, done. | |
| remote: Counting objects: 100% (67/67), done. | |
| remote: Compressing objects: 100% (56/56), done. | |
| remote: Total 12942 (delta 17), reused 35 (delta 6), pack-reused 12875 | |
| Receiving objects: 100% (12942/12942), 14.77 MiB | 9.29 MiB/s, done. | |
| Resolving deltas: 100% (8835/8835), done. | |
| (test-icefall) kuangfangjun:tmp$ cd icefall/ | |
| (test-icefall) kuangfangjun:icefall$ pip install -r ./requirements.txt | |
| Test Your Installation | |
| ---------------------- | |
| To test that your installation is successful, let us run | |
| the `yesno recipe <https://github.com/k2-fsa/icefall/tree/master/egs/yesno/ASR>`_ | |
| on ``CPU``. | |
| Data preparation | |
| ~~~~~~~~~~~~~~~~ | |
| .. code-block:: bash | |
| (test-icefall) kuangfangjun:icefall$ export PYTHONPATH=/tmp/icefall:$PYTHONPATH | |
| (test-icefall) kuangfangjun:icefall$ cd /tmp/icefall | |
| (test-icefall) kuangfangjun:icefall$ cd egs/yesno/ASR | |
| (test-icefall) kuangfangjun:ASR$ ./prepare.sh | |
| The log of running ``./prepare.sh`` is: | |
| .. code-block:: | |
| 2023-07-27 12:41:39 (prepare.sh:27:main) dl_dir: /tmp/icefall/egs/yesno/ASR/download | |
| 2023-07-27 12:41:39 (prepare.sh:30:main) Stage 0: Download data | |
| /tmp/icefall/egs/yesno/ASR/download/waves_yesno.tar.gz: 100%|___________________________________________________| 4.70M/4.70M [00:00<00:00, 11.1MB/s] | |
| 2023-07-27 12:41:46 (prepare.sh:39:main) Stage 1: Prepare yesno manifest | |
| 2023-07-27 12:41:50 (prepare.sh:45:main) Stage 2: Compute fbank for yesno | |
| 2023-07-27 12:41:55,718 INFO [compute_fbank_yesno.py:65] Processing train | |
| Extracting and storing features: 100%|_______________________________________________________________________________| 90/90 [00:01<00:00, 87.82it/s] | |
| 2023-07-27 12:41:56,778 INFO [compute_fbank_yesno.py:65] Processing test | |
| Extracting and storing features: 100%|______________________________________________________________________________| 30/30 [00:00<00:00, 256.92it/s] | |
| 2023-07-27 12:41:57 (prepare.sh:51:main) Stage 3: Prepare lang | |
| 2023-07-27 12:42:02 (prepare.sh:66:main) Stage 4: Prepare G | |
| /project/kaldilm/csrc/arpa_file_parser.cc:void kaldilm::ArpaFileParser::Read(std::istream&):79 | |
| [I] Reading \data\ section. | |
| /project/kaldilm/csrc/arpa_file_parser.cc:void kaldilm::ArpaFileParser::Read(std::istream&):140 | |
| [I] Reading \1-grams: section. | |
| 2023-07-27 12:42:02 (prepare.sh:92:main) Stage 5: Compile HLG | |
| 2023-07-27 12:42:07,275 INFO [compile_hlg.py:124] Processing data/lang_phone | |
| 2023-07-27 12:42:07,276 INFO [lexicon.py:171] Converting L.pt to Linv.pt | |
| 2023-07-27 12:42:07,309 INFO [compile_hlg.py:48] Building ctc_topo. max_token_id: 3 | |
| 2023-07-27 12:42:07,310 INFO [compile_hlg.py:52] Loading G.fst.txt | |
| 2023-07-27 12:42:07,314 INFO [compile_hlg.py:62] Intersecting L and G | |
| 2023-07-27 12:42:07,323 INFO [compile_hlg.py:64] LG shape: (4, None) | |
| 2023-07-27 12:42:07,323 INFO [compile_hlg.py:66] Connecting LG | |
| 2023-07-27 12:42:07,323 INFO [compile_hlg.py:68] LG shape after k2.connect: (4, None) | |
| 2023-07-27 12:42:07,323 INFO [compile_hlg.py:70] <class 'torch.Tensor'> | |
| 2023-07-27 12:42:07,323 INFO [compile_hlg.py:71] Determinizing LG | |
| 2023-07-27 12:42:07,341 INFO [compile_hlg.py:74] <class '_k2.ragged.RaggedTensor'> | |
| 2023-07-27 12:42:07,341 INFO [compile_hlg.py:76] Connecting LG after k2.determinize | |
| 2023-07-27 12:42:07,341 INFO [compile_hlg.py:79] Removing disambiguation symbols on LG | |
| 2023-07-27 12:42:07,354 INFO [compile_hlg.py:91] LG shape after k2.remove_epsilon: (6, None) | |
| 2023-07-27 12:42:07,445 INFO [compile_hlg.py:96] Arc sorting LG | |
| 2023-07-27 12:42:07,445 INFO [compile_hlg.py:99] Composing H and LG | |
| 2023-07-27 12:42:07,446 INFO [compile_hlg.py:106] Connecting LG | |
| 2023-07-27 12:42:07,446 INFO [compile_hlg.py:109] Arc sorting LG | |
| 2023-07-27 12:42:07,447 INFO [compile_hlg.py:111] HLG.shape: (8, None) | |
| 2023-07-27 12:42:07,447 INFO [compile_hlg.py:127] Saving HLG.pt to data/lang_phone | |
| Training | |
| ~~~~~~~~ | |
| Now let us run the training part: | |
| .. code-block:: | |
| (test-icefall) kuangfangjun:ASR$ export CUDA_VISIBLE_DEVICES="" | |
| (test-icefall) kuangfangjun:ASR$ ./tdnn/train.py | |
| .. CAUTION:: | |
| We use ``export CUDA_VISIBLE_DEVICES=""`` so that `icefall`_ uses CPU | |
| even if there are GPUs available. | |
| .. hint:: | |
| In case you get a ``Segmentation fault (core dump)`` error, please use: | |
| .. code-block:: bash | |
| export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python | |
| See more at `<https://github.com/k2-fsa/icefall/issues/674>` if you are | |
| interested. | |
| The training log is given below: | |
| .. code-block:: | |
| 2023-07-27 12:50:51,936 INFO [train.py:481] Training started | |
| 2023-07-27 12:50:51,936 INFO [train.py:482] {'exp_dir': PosixPath('tdnn/exp'), 'lang_dir': PosixPath('data/lang_phone'), 'lr': 0.01, 'feature_dim': 23, 'weight_decay': 1e-06, 'start_epoch': 0, 'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 10, 'reset_interval': 20, 'valid_interval': 10, 'beam_size': 10, 'reduction': 'sum', 'use_double_scores': True, 'world_size': 1, 'master_port': 12354, 'tensorboard': True, 'num_epochs': 15, 'seed': 42, '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.7640d66.clean', 'torch-version': '1.13.0+cu116', 'torch-cuda-available': False, 'torch-cuda-version': '11.6', 'python-version': '3.8', 'icefall-git-branch': 'master', 'icefall-git-sha1': '3fb0a43-clean', 'icefall-git-date': 'Thu Jul 27 12:36:05 2023', 'icefall-path': '/tmp/icefall', 'k2-path': '/star-fj/fangjun/test-icefall/lib/python3.8/site-packages/k2/__init__.py', 'lhotse-path': '/star-fj/fangjun/test-icefall/lib/python3.8/site-packages/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-1-1220091118-57c4d55446-sph26', 'IP address': '10.177.77.20'}} | |
| 2023-07-27 12:50:51,941 INFO [lexicon.py:168] Loading pre-compiled data/lang_phone/Linv.pt | |
| 2023-07-27 12:50:51,949 INFO [train.py:495] device: cpu | |
| 2023-07-27 12:50:51,965 INFO [asr_datamodule.py:146] About to get train cuts | |
| 2023-07-27 12:50:51,965 INFO [asr_datamodule.py:244] About to get train cuts | |
| 2023-07-27 12:50:51,967 INFO [asr_datamodule.py:149] About to create train dataset | |
| 2023-07-27 12:50:51,967 INFO [asr_datamodule.py:199] Using SingleCutSampler. | |
| 2023-07-27 12:50:51,967 INFO [asr_datamodule.py:205] About to create train dataloader | |
| 2023-07-27 12:50:51,968 INFO [asr_datamodule.py:218] About to get test cuts | |
| 2023-07-27 12:50:51,968 INFO [asr_datamodule.py:252] About to get test cuts | |
| 2023-07-27 12:50:52,565 INFO [train.py:422] Epoch 0, batch 0, loss[loss=1.065, over 2436.00 frames. ], tot_loss[loss=1.065, over 2436.00 frames. ], batch size: 4 | |
| 2023-07-27 12:50:53,681 INFO [train.py:422] Epoch 0, batch 10, loss[loss=0.4561, over 2828.00 frames. ], tot_loss[loss=0.7076, over 22192.90 frames.], batch size: 4 | |
| 2023-07-27 12:50:54,167 INFO [train.py:444] Epoch 0, validation loss=0.9002, over 18067.00 frames. | |
| 2023-07-27 12:50:55,011 INFO [train.py:422] Epoch 0, batch 20, loss[loss=0.2555, over 2695.00 frames. ], tot_loss[loss=0.484, over 34971.47 frames. ], batch size: 5 | |
| 2023-07-27 12:50:55,331 INFO [train.py:444] Epoch 0, validation loss=0.4688, over 18067.00 frames. | |
| 2023-07-27 12:50:55,368 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-0.pt | |
| 2023-07-27 12:50:55,633 INFO [train.py:422] Epoch 1, batch 0, loss[loss=0.2532, over 2436.00 frames. ], tot_loss[loss=0.2532, over 2436.00 frames. ], | |
| batch size: 4 | |
| 2023-07-27 12:50:56,242 INFO [train.py:422] Epoch 1, batch 10, loss[loss=0.1139, over 2828.00 frames. ], tot_loss[loss=0.1592, over 22192.90 frames.], batch size: 4 | |
| 2023-07-27 12:50:56,522 INFO [train.py:444] Epoch 1, validation loss=0.1627, over 18067.00 frames. | |
| 2023-07-27 12:50:57,209 INFO [train.py:422] Epoch 1, batch 20, loss[loss=0.07055, over 2695.00 frames. ], tot_loss[loss=0.1175, over 34971.47 frames.], batch size: 5 | |
| 2023-07-27 12:50:57,600 INFO [train.py:444] Epoch 1, validation loss=0.07091, over 18067.00 frames. | |
| 2023-07-27 12:50:57,640 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-1.pt | |
| 2023-07-27 12:50:57,847 INFO [train.py:422] Epoch 2, batch 0, loss[loss=0.07731, over 2436.00 frames. ], tot_loss[loss=0.07731, over 2436.00 frames.], batch size: 4 | |
| 2023-07-27 12:50:58,427 INFO [train.py:422] Epoch 2, batch 10, loss[loss=0.04391, over 2828.00 frames. ], tot_loss[loss=0.05341, over 22192.90 frames. ], batch size: 4 | |
| 2023-07-27 12:50:58,884 INFO [train.py:444] Epoch 2, validation loss=0.04384, over 18067.00 frames. | |
| 2023-07-27 12:50:59,387 INFO [train.py:422] Epoch 2, batch 20, loss[loss=0.03458, over 2695.00 frames. ], tot_loss[loss=0.04616, over 34971.47 frames. ], batch size: 5 | |
| 2023-07-27 12:50:59,707 INFO [train.py:444] Epoch 2, validation loss=0.03379, over 18067.00 frames. | |
| 2023-07-27 12:50:59,758 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-2.pt | |
| ... ... | |
| 2023-07-27 12:51:23,433 INFO [train.py:422] Epoch 13, batch 0, loss[loss=0.01054, over 2436.00 frames. ], tot_loss[loss=0.01054, over 2436.00 frames. ], batch size: 4 | |
| 2023-07-27 12:51:23,980 INFO [train.py:422] Epoch 13, batch 10, loss[loss=0.009014, over 2828.00 frames. ], tot_loss[loss=0.009974, over 22192.90 frames. ], batch size: 4 | |
| 2023-07-27 12:51:24,489 INFO [train.py:444] Epoch 13, validation loss=0.01085, over 18067.00 frames. | |
| 2023-07-27 12:51:25,258 INFO [train.py:422] Epoch 13, batch 20, loss[loss=0.01172, over 2695.00 frames. ], tot_loss[loss=0.01055, over 34971.47 frames. ], batch size: 5 | |
| 2023-07-27 12:51:25,621 INFO [train.py:444] Epoch 13, validation loss=0.01074, over 18067.00 frames. | |
| 2023-07-27 12:51:25,699 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-13.pt | |
| 2023-07-27 12:51:25,866 INFO [train.py:422] Epoch 14, batch 0, loss[loss=0.01044, over 2436.00 frames. ], tot_loss[loss=0.01044, over 2436.00 frames. ], batch size: 4 | |
| 2023-07-27 12:51:26,844 INFO [train.py:422] Epoch 14, batch 10, loss[loss=0.008942, over 2828.00 frames. ], tot_loss[loss=0.01, over 22192.90 frames. ], batch size: 4 | |
| 2023-07-27 12:51:27,221 INFO [train.py:444] Epoch 14, validation loss=0.01082, over 18067.00 frames. | |
| 2023-07-27 12:51:27,970 INFO [train.py:422] Epoch 14, batch 20, loss[loss=0.01169, over 2695.00 frames. ], tot_loss[loss=0.01054, over 34971.47 frames. ], batch size: 5 | |
| 2023-07-27 12:51:28,247 INFO [train.py:444] Epoch 14, validation loss=0.01073, over 18067.00 frames. | |
| 2023-07-27 12:51:28,323 INFO [checkpoint.py:75] Saving checkpoint to tdnn/exp/epoch-14.pt | |
| 2023-07-27 12:51:28,326 INFO [train.py:555] Done! | |
| Decoding | |
| ~~~~~~~~ | |
| Let us use the trained model to decode the test set: | |
| .. code-block:: | |
| (test-icefall) kuangfangjun:ASR$ ./tdnn/decode.py | |
| 2023-07-27 12:55:12,840 INFO [decode.py:263] Decoding started | |
| 2023-07-27 12:55:12,840 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.7640d66.clean', 'torch-version': '1.13.0+cu116', 'torch-cuda-available': False, 'torch-cuda-version': '11.6', 'python-version': '3.8', 'icefall-git-branch': 'master', 'icefall-git-sha1': '3fb0a43-clean', 'icefall-git-date': 'Thu Jul 27 12:36:05 2023', 'icefall-path': '/tmp/icefall', 'k2-path': '/star-fj/fangjun/test-icefall/lib/python3.8/site-packages/k2/__init__.py', 'lhotse-path': '/star-fj/fangjun/test-icefall/lib/python3.8/site-packages/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-1-1220091118-57c4d55446-sph26', 'IP address': '10.177.77.20'}} | |
| 2023-07-27 12:55:12,841 INFO [lexicon.py:168] Loading pre-compiled data/lang_phone/Linv.pt | |
| 2023-07-27 12:55:12,855 INFO [decode.py:273] device: cpu | |
| 2023-07-27 12:55:12,868 INFO [decode.py:291] averaging ['tdnn/exp/epoch-13.pt', 'tdnn/exp/epoch-14.pt'] | |
| 2023-07-27 12:55:12,882 INFO [asr_datamodule.py:218] About to get test cuts | |
| 2023-07-27 12:55:12,883 INFO [asr_datamodule.py:252] About to get test cuts | |
| 2023-07-27 12:55:13,157 INFO [decode.py:204] batch 0/?, cuts processed until now is 4 | |
| 2023-07-27 12:55:13,701 INFO [decode.py:241] The transcripts are stored in tdnn/exp/recogs-test_set.txt | |
| 2023-07-27 12:55:13,702 INFO [utils.py:564] [test_set] %WER 0.42% [1 / 240, 0 ins, 1 del, 0 sub ] | |
| 2023-07-27 12:55:13,704 INFO [decode.py:249] Wrote detailed error stats to tdnn/exp/errs-test_set.txt | |
| 2023-07-27 12:55:13,704 INFO [decode.py:316] Done! | |
| **Congratulations!** You have successfully setup the environment and have run the first recipe in `icefall`_. | |
| Have fun with ``icefall``! | |
| YouTube Video | |
| ------------- | |
| We provide the following YouTube video showing how to install `icefall`_. | |
| It also shows how to debug various problems that you may encounter while | |
| using `icefall`_. | |
| .. note:: | |
| To get the latest news of `next-gen Kaldi <https://github.com/k2-fsa>`_, please subscribe | |
| the following YouTube channel by `Nadira Povey <https://www.youtube.com/channel/UC_VaumpkmINz1pNkFXAN9mw>`_: | |
| `<https://www.youtube.com/channel/UC_VaumpkmINz1pNkFXAN9mw>`_ | |
| .. youtube:: LVmrBD0tLfE | |