:::{note} For build-time environment variables, see Install from source code. :::
:::{envvar} DP_INTER_OP_PARALLELISM_THREADS
Alias: TF_INTER_OP_PARALLELISM_THREADS
Default: 0
Control parallelism within TensorFlow (when TensorFlow is built against Eigen) and PyTorch native OPs for CPU devices. See How to control the parallelism of a job for details. :::
:::{envvar} DP_INTRA_OP_PARALLELISM_THREADS
Alias: TF_INTRA_OP_PARALLELISM_THREADS**
Default: 0
Control parallelism within TensorFlow (when TensorFlow is built against Eigen) and PyTorch native OPs. See How to control the parallelism of a job for details. :::
- If OpenMP is used, OpenMP environment variables can be used to control OpenMP threads, such as
OMP_NUM_THREADS. - If CUDA is used, CUDA environment variables can be used to control CUDA devices, such as
CUDA_VISIBLE_DEVICES. - If ROCm is used, ROCm environment variables can be used to control ROCm devices.
- {{ tensorflow_icon }} If TensorFlow is used, TensorFlow environment variables can be used.
- {{ pytorch_icon }} If PyTorch is used, PyTorch environment variables can be used.
- {{ jax_icon }}
JAX_PLATFORMSandXLA_FLAGSare commonly used.
:::{envvar} DP_INTERFACE_PREC
Choices: high, low; Default: high
Control high (double) or low (float) precision of training. :::
:::{envvar} DP_AUTO_PARALLELIZATION
Choices: 0, 1; Default: 0
{{ tensorflow_icon }} Enable auto parallelization for CPU operators. :::
:::{envvar} DP_JIT
Choices: 0, 1; Default: 0
{{ tensorflow_icon }} Enable JIT. Note that this option may either improve or decrease the performance. Requires TensorFlow to support JIT. :::
:::{envvar} DP_INFER_BATCH_SIZE
Default: 1024 on CPUs and as maximum as possible until out-of-memory on GPUs
Inference batch size, calculated by multiplying the number of frames with the number of atoms. :::
:::{envvar} DP_BACKEND
Default: tensorflow
Default backend. :::
:::{envvar} NUM_WORKERS
Default: 8 or the number of cores (whichever is smaller)
{{ pytorch_icon }} Number of subprocesses to use for data loading in the PyTorch backend. See PyTorch documentation for details.
:::
These environment variables also apply to third-party programs using the C++ interface, such as LAMMPS.
:::{envvar} DP_PLUGIN_PATH
Type: List of paths, split by : on Unix and ; on Windows
List of customized OP plugin libraries to load, such as /path/to/plugin1.so:/path/to/plugin2.so on Linux and /path/to/plugin1.dll;/path/to/plugin2.dll on Windows.
:::