Steps needed to install K2 from scratch

install_k2.sh

#!/usr/bin/env bash

# Do not run the commented lines

# First git clone k2 and cd to inside it.

# Common steps
conda create -n k2 python=3.8
conda activate k2 

# Install PyTorch and Torchaudio
pip install torch==1.8.1+cu111 torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html

pip install cmake
# mkdir build
# pushd build 

# CONDA_ROOT="$(conda config --show root_prefix | cut -f2 -d' ')"
# CONDA_ENV_DIR="$CONDA_ROOT/envs/k2"

# Suppose you want to install it with CUDA 11.1 and CUDNN 8.0
# See /cm/shared/apps for other options

CUDNN_LIBRARY_PATH=/cm/shared/apps/cudnn/8.0.2_cuda11.0/lib64
CUDNN_INCLUDE_PATH=/cm/shared/apps/cudnn/8.0.2_cuda11.0/include
CUDA_TOOLKIT_DIR=/cm/shared/apps/cuda11.1

cmake \
  -DCMAKE_BUILD_TYPE=Release \
  -DCMAKE_CUDA_COMPILER=$(which nvcc) \
  -DPYTHON_EXECUTABLE=$(which python) \
  -DCUDNN_LIBRARY_PATH=$CUDNN_LIBRARY_PATH/libcudnn.so \
  -DCUDNN_INCLUDE_PATH=$CUDNN_INCLUDE_PATH \
  -DCUDA_TOOLKIT_ROOT_DIR=$CUDA_TOOLKIT_DIR \
  ..
  
# make -j24 _k2

# popd

# When updating and rebuilding K2, before executing these steps, run:
# rm -rf dist/
K2_CMAKE_ARGS="-DCUDNN_LIBRARY_PATH=$CUDNN_LIBRARY_PATH/libcudnn.so -DCUDNN_INCLUDE_PATH=$CUDNN_INCLUDE_PATH -DCUDA_TOOLKIT_ROOT_DIR=$CUDA_TOOLKIT_DIR"
scripts/build_pip.sh
pip install dist/*

# Other tools that may be required to install

# kaldifeat

export KALDIFEAT_CMAKE_ARGS="-DCUDNN_LIBRARY_PATH=$CUDNN_LIBRARY_PATH/libcudnn.so -DCUDNN_INCLUDE_PATH=$CUDNN_INCLUDE_PATH -DCUDA_TOOLKIT_ROOT_DIR=$CUDA_TOOLKIT_DIR"
pip install --verbose kaldifeat

# optimized_transducer

export OT_CMAKE_ARGS="-DCUDNN_LIBRARY_PATH=$CUDNN_LIBRARY_PATH/libcudnn.so -DCUDNN_INCLUDE_PATH=$CUDNN_INCLUDE_PATH -DCUDA_TOOLKIT_ROOT_DIR=$CUDA_TOOLKIT_DIR"
pip install --verbose optimized_transducer