@@ -26,7 +26,7 @@ step-by-step instructions.
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for more information about this collaboration.
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``` bash
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- conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0
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+ conda install -c conda-forge cudatoolkit=11.2.2 cudnn=8.1.0
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH :$CONDA_PREFIX /lib/
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python3 -m pip install tensorflow
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# Verify install:
@@ -236,7 +236,7 @@ The following NVIDIA® software are only required for GPU support.
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Then install CUDA and cuDNN with conda.
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` ` ` bash
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- conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0
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+ conda install -c conda-forge cudatoolkit=11.2.2 cudnn=8.1.0
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` ` `
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Configure the system paths. You can do it with the following command every time
@@ -271,7 +271,7 @@ The following NVIDIA® software are only required for GPU support.
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PyPI.
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```bash
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- pip install tensorflow
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+ pip install tensorflow==2.11.*
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```
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### 6. Verify install
@@ -293,6 +293,31 @@ The following NVIDIA® software are only required for GPU support.
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If a list of GPU devices is returned, you' ve installed TensorFlow
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successfully.
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+ ### Ubuntu 22.04
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+ In Ubuntu 22.04, you may encounter the following error:
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+
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+ ```
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+ Can' t find libdevice directory ${CUDA_DIR} /nvvm/libdevice.
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+ ...
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+ Couldn' t invoke ptxas --version
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+ ...
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+ InternalError: libdevice not found at ./libdevice.10.bc [Op:__some_op]
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+ ```
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+
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+ To fix this error, you will need to run the following commands.
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+
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+ ```bash
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+ # Install NVCC
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+ conda install -c nvidia cuda-nvcc=11.3.58
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+ # Configure the XLA cuda directory
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+ mkdir -p $CONDA_PREFIX/etc/conda/activate.d
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+ printf ' export LD_LIBRARY_PATH=$LD_LIBRARY_PATH :$CONDA_PREFIX /lib/\n export XLA_FLAGS=--xla_gpu_cuda_data_dir=$CONDA_PREFIX /lib/\n ' > $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
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+ source $CONDA_PREFIX/etc/conda/activate.d/env_vars.sh
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+ # Copy libdevice file to the required path
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+ mkdir -p $CONDA_PREFIX/lib/nvvm/libdevice
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+ cp $CONDA_PREFIX/lib/libdevice.10.bc $CONDA_PREFIX/lib/nvvm/libdevice/
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+ ```
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* {MacOS}
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