Releases: NVIDIA/tensorflow
Releases · NVIDIA/tensorflow
22.04
NVIDIA TensorFlow Release 22.04
NVIDIA TensorFlow release 22.04 is based on TensorFlow 1.15.5.
Binary builds
PIP - built for Python 3.8 on Ubuntu 20.04:
pip install --user nvidia-pyindex
pip install --user nvidia-tensorflow[horovod]
docker pull nvcr.io/nvidia/tensorflow:22.04-tf1-py3
22.03
NVIDIA TensorFlow Release 22.03
NVIDIA TensorFlow release 22.03 is based on TensorFlow 1.15.5.
Binary builds
PIP - built for Python 3.8 on Ubuntu 20.04:
pip install --user nvidia-pyindex
pip install --user nvidia-tensorflow[horovod]
docker pull nvcr.io/nvidia/tensorflow:22.03-tf1-py3
22.02
NVIDIA TensorFlow Release 22.02
Key Features and Enhancements
NVIDIA TensorFlow release 22.02 is based on TensorFlow 1.15.5.
Known Issues
- A CUDNN performance regression can cause slowdowns of up to 15% in certain ResNet models. This will be fixed in a future release.
- TensorFlow Wheel release 21.12 has a known corruption issue in its NVTX profiling markers when using the CUPTI library from CUDA Toolkit version 11.5. An updated CUPTI build, numbered 11.5.57 or higher, in CUDA 11.5 Update 1 will address this issue.
Binary builds
PIP - built for Python 3.8 on Ubuntu 20.04:
pip install --user nvidia-pyindex
pip install --user nvidia-tensorflow[horovod]
docker pull nvcr.io/nvidia/tensorflow:22.02-tf1-py3
22.01
NVIDIA TensorFlow Release 22.01
Key Features and Enhancements
NVIDIA TensorFlow release 22.01 is based on TensorFlow 1.15.5.
Release 22.01 includes the following key features and enhancements:
- Fixed circular dependency in monolithic builds to address github issue 21.
Known Issues
- A CUDNN performance regression can cause slowdowns of up to 15% in certain ResNet models. This will be fixed in a future release.
- TensorFlow Wheel release 21.12 has a known corruption issue in its NVTX profiling markers when using the CUPTI library from CUDA Toolkit version 11.5. An updated CUPTI build, numbered 11.5.57 or higher, in CUDA 11.5 Update 1 will address this issue.
- Debugging with TF_CPP_MIN_VLOG_LEVEL=3 can result in a segmentation while auto-tuning convolution algorithms. This will be fixed in the 22.02 release.
Binary builds
PIP - built for Python 3.8 on Ubuntu 20.04:
pip install --user nvidia-pyindex
pip install --user nvidia-tensorflow[horovod]
docker pull nvcr.io/nvidia/tensorflow:22.01-tf1-py3
21.12
NVIDIA TensorFlow Release 21.12
Key Features and Enhancements
NVIDIA TensorFlow release 20.06 is based on TensorFlow 1.15.5.
Release 21.12 includes the following key features and enhancements:
- The environment variable TF_DISABLE_REDUCED_PRECISION_REDUCTION=1 can now be set to disable intermediate reductions in lower precision than the requested math type.
- Patched the following CVEs in TensorFlow 1.15.5: CVE-2021-29571, CVE-2021-29592, CVE-2021-29601, CVE-2021-29608, CVE-2021-29609, CVE-2021-29613, CVE-2021-22876, CVE-2021-22897, CVE-2021-22898, CVE-2021-22901, CVE-2021-37636, CVE-2021-37640, CVE-2021-37642, CVE-2021-37644, CVE-2021-37646, CVE-2021-37653, CVE-2021-37660, CVE-2021-37661, CVE-2021-37668, CVE-2021-37669, CVE-2021-37670, CVE-2021-37672, CVE-2021-37673, CVE-2021-37674, CVE-2021-37675, CVE-2021-37684, CVE-2021-37686, CVE-2021-37690, CVE-2021-37691, CVE-2021-41195, CVE-2021-41196, CVE-2021-41197, CVE-2021-41198, CVE-2021-41199, CVE-2021-41200, CVE-2021-41201, CVE-2021-41202, CVE-2021-41203, CVE-2021-41204, CVE-2021-41206, CVE-2021-41207, CVE-2021-41208, CVE-2021-41213, CVE-2021-41215, CVE-2021-41216, CVE-2021-41217, CVE-2021-41218, CVE-2021-41219, CVE-2021-41221, CVE-2021-41222, CVE-2021-41223, CVE-2021-41224, CVE-2021-41225, CVE-2021-41228, CVE-2021-22922, CVE-2021-22923, CVE-2021-22924, CVE-2021-22925, CVE-2021-22926
Known Issues
- A CUDNN performance regression can cause slowdowns of up to 15% in certain ResNet models. This will be fixed in a future release.
- TensorFlow Wheel release 21.12 has a known corruption issue in its NVTX profiling markers when using the CUPTI library from CUDA Toolkit version 11.5. An updated CUPTI build, numbered 11.5.57 or higher, in CUDA 11.5 Update 1 will address this issue.
Binary builds
PIP - built for Python 3.8 on Ubuntu 20.04:
pip install --user nvidia-pyindex
pip install --user nvidia-tensorflow[horovod]
docker pull nvcr.io/nvidia/tensorflow:21.12-tf1-py3
20.06
NVIDIA TensorFlow Release 20.06
Initial GitHub Release
Key Features and Enhancements
NVIDIA TensorFlow release 20.06 is based on TensorFlow 1.15.2.
Release 20.06 includes the following key features and enhancements:
- Integrated latest NVIDIA Deep Learning SDK to support NVIDIA A100 when built with CUDA 11 and cuDNN 8
- Improved NVTX annotations for XLA clusters for use with NVIDIA DLProf
- Improved XLA to avoid excessive recompilations
- Enhancements for Automatic Mixed Precision with einsum, 3D Convolutions, and list operations
- Improved 3D Convolutions to support NDHWC format
- Default TF32 support on NVIDIA A100
Known Issues
- TF-TRT inference throughput may regress for certain models by up to 37% compared to the 21.06-tf1 release. This will be fixed in a future release.
- A CUDNN performance regression can cause slowdowns of up to 15% in certain ResNet models. This will be fixed in a future release.
- TensorFlow Wheel release 21.12 has a known corruption issue in its NVTX profiling markers when using the CUPTI library from CUDA Toolkit version 11.5. An updated CUPTI build, numbered 11.5.57 or higher, in CUDA 11.5 Update 1 will address this issue.
Binary builds
PIP - built for Python 3.8 on Ubuntu 20.04:
pip install --user nvidia-pyindex
pip install --user nvidia-tensorflow[horovod]
docker pull nvcr.io/nvidia/tensorflow:21.12-tf1-py3