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Update readme.
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name: Nightly tests ubuntu conda cpu
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name: Nightly tests ubuntu conda cpu
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- nightly-test-2
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schedule:
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schedule:
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# minute (0-59)
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# minute (0-59)
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# hour (0-23)
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# hour (0-23)
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name: Nightly tests ubuntu conda cuda
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name: Nightly tests ubuntu conda cuda
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on:
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on:
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push:
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branches:
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- nightly-test-2
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schedule:
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schedule:
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# minute (0-59)
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# minute (0-59)
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# hour (0-23)
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# hour (0-23)
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needs: generate_build_matrix
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needs: generate_build_matrix
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runs-on: ubuntu-18.04
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runs-on: ubuntu-18.04
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strategy:
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strategy:
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fail-fast: true
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fail-fast: false
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matrix:
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matrix:
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${{ fromJson(needs.generate_build_matrix.outputs.matrix) }}
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${{ fromJson(needs.generate_build_matrix.outputs.matrix) }}
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name: Nightly tests windows pip cuda
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name: Nightly tests windows pip cuda
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on:
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branches:
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- nightly-test
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schedule:
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schedule:
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# minute (0-59)
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# minute (0-59)
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# hour (0-23)
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# hour (0-23)
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4
.github/workflows/run-tests-ubuntu-cuda.yml
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4
.github/workflows/run-tests-ubuntu-cuda.yml
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id: set-matrix
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id: set-matrix
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run: |
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# outputting for debugging purposes
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# outputting for debugging purposes
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python scripts/github_actions/generate_build_matrix.py --enable-cuda
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python scripts/github_actions/generate_build_matrix.py --enable-cuda --test-only-latest-torch
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MATRIX=$(python scripts/github_actions/generate_build_matrix.py --enable-cuda)
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MATRIX=$(python scripts/github_actions/generate_build_matrix.py --enable-cuda --test-only-latest-torch)
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echo "::set-output name=matrix::${MATRIX}"
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echo "::set-output name=matrix::${MATRIX}"
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run_tests_ubuntu_cuda:
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run_tests_ubuntu_cuda:
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.github/workflows/run-tests-windows-cuda.yml
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.github/workflows/run-tests-windows-cuda.yml
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on:
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on:
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push:
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push:
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branches:
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branches:
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- nightly-test
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- master
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- master
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pull_request:
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pull_request:
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id: set-matrix
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id: set-matrix
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run: |
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run: |
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# outputting for debugging purposes
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# outputting for debugging purposes
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python scripts/github_actions/generate_build_matrix.py --enable-cuda --for-windows
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python scripts/github_actions/generate_build_matrix.py --enable-cuda --for-windows --test-only-latest-torch
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MATRIX=$(python scripts/github_actions/generate_build_matrix.py --enable-cuda --for-windows)
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MATRIX=$(python scripts/github_actions/generate_build_matrix.py --enable-cuda --for-windows --test-only-latest-torch)
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echo "::set-output name=matrix::${MATRIX}"
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echo "::set-output name=matrix::${MATRIX}"
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run_tests_windows_cuda:
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run_tests_windows_cuda:
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70
README.md
70
README.md
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# kaldifeat
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# kaldifeat
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<div align="center">
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<div align="center">
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<img src="/doc/source/images/os.svg">
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<img src="/doc/source/images/os-green.svg">
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<img src="/doc/source/images/python_ge_3.6-blue.svg">
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<img src="/doc/source/images/python_ge_3.6-blue.svg">
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<img src="/doc/source/images/pytorch_ge_1.5.0-green.svg">
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<img src="/doc/source/images/pytorch_ge_1.5.0-green.svg">
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<img src="/doc/source/images/cuda_ge_10.1-orange.svg">
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<img src="/doc/source/images/cuda_ge_10.1-orange.svg">
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@ -268,15 +268,22 @@ See <https://github.com/k2-fsa/k2/blob/v2.0-pre/k2/torch/csrc/features.cu>.
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See <https://github.com/lhotse-speech/lhotse/blob/master/lhotse/features/kaldifeat.py>.
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See <https://github.com/lhotse-speech/lhotse/blob/master/lhotse/features/kaldifeat.py>.
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## sherpa
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[sherpa](https://github.com/k2-fsa/sherpa) uses kaldifeat for streaming feature
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extraction.
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See <https://github.com/k2-fsa/sherpa/blob/master/sherpa/bin/pruned_stateless_emformer_rnnt2/decode.py>
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# Installation
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# Installation
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## From conda (Only for Linux + CUDA)
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## From conda (Only for Linux)
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Supported versions of Python, PyTorch, and CUDA toolkit are listed below:
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Supported versions of Python, PyTorch, and CUDA toolkit are listed below:
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[](/doc/source/images/python-3.6_3.7_3.8-blue.svg)
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[](/doc/source/images/python_ge_3.6-blue.svg)
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[](/doc/source/images/pytorch-1.6.0_1.7.0_1.7.1_1.8.0_1.8.1_1.9.0-green.svg)
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[](/doc/source/images/pytorch_ge_1.5.0-green.svg)
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[](/doc/source/images/cuda-10.1_10.2_11.0_11.1-orange.svg)
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[](/doc/source/images/cuda_ge_10.1-orange.svg)
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```bash
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```bash
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conda install -c kaldifeat -c pytorch -c conda-forge kaldifeat python=3.8 cudatoolkit=11.1 pytorch=1.8.1
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conda install -c kaldifeat -c pytorch -c conda-forge kaldifeat python=3.8 cudatoolkit=11.1 pytorch=1.8.1
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You can select the supported Python version, CUDA toolkit version and PyTorch version as you wish.
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You can select the supported Python version, CUDA toolkit version and PyTorch version as you wish.
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**Note:** If you want a CPU only version or want to install `kaldifeat` on other operating systems,
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To install a CPU version, use
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e.g., macOS, please use `pip install` or compile `kaldifeat` from source.
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```bash
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conda install -c kaldifeat -c pytorch cpuonly kaldifeat python=3.8 pytorch=1.8.1
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```
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## From PyPi with pip
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**Note:** If you want to install `kaldifeat` on macOS or Windows, please
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use either `pip install -v kaldifeat` or compile `kaldifeat` from source.
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## From PyPi with pip (Support Linux/macOS/Windows)
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You need to install PyTorch and CMake first.
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You need to install PyTorch and CMake first.
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CMake 3.11 is known to work. Other CMake versions may also work.
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CMake 3.11 is known to work. Other CMake versions may also work.
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pip install -v kaldifeat
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pip install -v kaldifeat
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```
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```
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## From source
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## From source (Support Linux/macOS/Windows)
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The following are the commands to compile `kaldifeat` from source.
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The following are the commands to compile `kaldifeat` from source.
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We assume that you have installed `CMake` and PyTorch.
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We assume that you have installed `CMake` and PyTorch.
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### How to install a CUDA version
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### How to install a CUDA version
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There are two approaches:
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You need to first install a CUDA version of PyTorch and then install `kaldifeat`.
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- (1) Install using `conda`. It always installs a CUDA version of kaldifeat.
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**Note**: You can use a CUDA version of kaldifeat on machines with no GPUs.
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- (2) Install a CUDA version of PyTorch and then install kaldifeat from source
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or use `pip install kaldifeat`.
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### How to install a CPU-only version
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### How to install a CPU-only version
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You have to first install a CPU-only version of PyTorch and then install kaldifeat
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You need to first install a CPU version of PyTorch and then install `kaldifeat`.
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from source or use `pip install kaldifeat`.
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### How to fix `Caffe2: Cannot find cuDNN library`
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```
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Your installed Caffe2 version uses cuDNN but I cannot find the cuDNN
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libraries. Please set the proper cuDNN prefixes and / or install cuDNN.
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```
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This error happens when you want to install a CUDA version of kaldifeat
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by `pip install kaldifeat` or from source.
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You need to first install cuDNN. Assume you have installed cuDNN to the
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path `/path/to/cudnn`. You can fix the error by the following commands.
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(1) Fix for installation using `pip install`
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```bash
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export KALDIFEAT_CMAKE_ARGS="-DCMAKE_BUILD_TYPE=Release -DCUDNN_LIBRARY_PATH=/path/to/cudnn/lib/libcudnn.so -DCUDNN_INCLUDE_PATH=/path/to/cudnn/include"
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pip install --verbose kaldifeat
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```
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(2) Fix for installation from source
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```bash
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mkdir /some/path
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git clone https://github.com/csukuangfj/kaldifeat.git
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cd kaldifeat
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export KALDIFEAT_CMAKE_ARGS="-DCMAKE_BUILD_TYPE=Release -DCUDNN_LIBRARY_PATH=/path/to/cudnn/lib/libcudnn.so -DCUDNN_INCLUDE_PATH=/path/to/cudnn/include"
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python setup.py install
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```
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8
doc/source/images/README.md
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doc/source/images/README.md
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## File description
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<https://shields.io/> is used to create the following files:
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- ./os.svg
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- ./python_ge_3.6-blue.svg
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- ./cuda_ge_10.1-orange.svg
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- ./pytorch_ge_1.5.0-green.svg
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1
doc/source/images/os-green.svg
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1
doc/source/images/os-green.svg
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<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="176" height="20" role="img" aria-label="os: Linux | macOS | Windows"><title>os: Linux | macOS | Windows</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="176" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="23" height="20" fill="#555"/><rect x="23" width="153" height="20" fill="#97ca00"/><rect width="176" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="125" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="130">os</text><text x="125" y="140" transform="scale(.1)" fill="#fff" textLength="130">os</text><text aria-hidden="true" x="985" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="1430">Linux | macOS | Windows</text><text x="985" y="140" transform="scale(.1)" fill="#fff" textLength="1430">Linux | macOS | Windows</text></g></svg>
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After Width: | Height: | Size: 1.2 KiB |
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<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="118" height="20" role="img" aria-label="OS: Linux | macOS"><title>OS: Linux | macOS</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="118" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="27" height="20" fill="#555"/><rect x="27" width="91" height="20" fill="#4c1"/><rect width="118" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="145" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="170">OS</text><text x="145" y="140" transform="scale(.1)" fill="#fff" textLength="170">OS</text><text aria-hidden="true" x="715" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="810">Linux | macOS</text><text x="715" y="140" transform="scale(.1)" fill="#fff" textLength="810">Linux | macOS</text></g></svg>
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Before Width: | Height: | Size: 1.1 KiB |
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