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March 12, 2025
M128 release
- Except for TensorFlow container images, new container images don't include conda. This change was made to improve size, performance, and vulnerability management. The existing container image names now point to container images that don't include conda (for example:
gcr.io/deeplearning-platform-release/base-cpu.py310). - Container images that include conda will be available until at least September 30, 2025. These container images now have
-condaappended to the name (for example:gcr.io/deeplearning-platform-release/base-cpu-conda.py310). - All TensorFlow container images still include conda, but M128 container image names have
-condaappended. Specifying container images without-condaappended references older container images, which also include conda.
July 16, 2024
M123 release
- Hugging Face Text Generation Inference 2.1 GPU container images are now available.
March 29, 2024
M119 release
- Fixed an issue wherein Dataproc extensions caused JupyterLab to crash when remote kernels weren't available.
M119 release
- Fixed an issue wherein Dataproc extensions caused JupyterLab to crash when remote kernels weren't available.
December 14, 2023
M114 release
- Starting with this release, Python 3.7 is no longer available.
- Upgraded R to 4.3 on Python 3.10 containers.
- Fixed an issue where the PySpark-BigQuery connector didn't work properly on Python 3.10 PySpark container.
October 10, 2023
M112 release
- Miscellaneous bug fixes and improvements.
August 10, 2023
M110 release
- Added support for TensorFlow 2.13 with Python 3.10 on Debian 11.
- Added support for TensorFlow 2.8 with Python 3.10 on Debian 11.
- Miscellaneous software updates.
April 06, 2023
M106 release
- Miscellaneous software updates.
March 31, 2023
M105 release
The following Deep Learning Containers images are now available with Python 3.10 on Debian 11:
- TensorFlow 2.11 CPU (
us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf-cpu.2-11.py310:latest) - TensorFlow 2.11 GPU with Cuda 11.3 (
us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf-gpu.2-11.py310:latest) - PyTorch 1.13 with Cuda 11.3 (
us-docker.pkg.dev/deeplearning-platform-release/gcr.io/pytorch-gpu.1-13.py310:latest) - Base CPU (
us-docker.pkg.dev/deeplearning-platform-release/gcr.io/base-cpu.py310:latest) - Base GPU with Cuda 11.3 (
us-docker.pkg.dev/deeplearning-platform-release/gcr.io/base-cu113.py310:latest)
- TensorFlow 2.11 CPU (
The following Deep Learning Containers images are now available with Python 3.9 on Debian 11:
- TensorFlow 2.6 CPU (
us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf-cpu.2-6.py39:latest) - TensorFlow 2.6 GPU with Cuda 11.3 (
us-docker.pkg.dev/deeplearning-platform-release/gcr.io/tf-gpu.2-6.py39:latest)
- TensorFlow 2.6 CPU (
Miscellaneous bug fixes and improvements.
December 09, 2022
M101 release
- TensorFlow patch version upgrades:
- From 2.8.3 to 2.8.4.
- From 2.9.2 to 2.9.3.
- From 2.10.0 to 2.10.1.
- TensorFlow 1.15 Deep Learning Containers images are now deprecated.
- Regular security patches and package upgrades.
November 08, 2022
M100 release
- Regular package updates.
March 21, 2022
- Fixed an R package installation issue for R Deep Learning Containers and Vertex AI Workbench.
December 20, 2021
- Starting with this release, the Python packages that are installed on each container image are listed in files that are available on Cloud Storage.
September 09, 2021
M79 release
- Updated Pytorch 1.9 containers (they were not refreshed in the last release).
- Updated Theia IDE (experimental) containers.
- Node.js is pinned to
>=12.14.1,<13.
- Fixed a bug in which the home folder in custom container VMs was owned by the root instead of Jupyter.
- Fixed a bug in which the home folder in custom container VMs was owned by the root instead of Jupyter.
August 18, 2021
TensorFlow Enterprise 2.5
- TensorFlow Enterprise 2.5 Deep Learning Containers are now deprecated.
TensorFlow Enterprise 2.5
- TensorFlow Enterprise 2.5 Deep Learning Containers are now deprecated.
June 22, 2021
M73 release
- Upgraded TensorFlow Enterprise 2.1.3 to 2.1.4.
- Upgraded TensorFlow Enterprise 2.3.2 to 2.3.3.
- Miscellaneous bug fixes and updates.
February 08, 2021
M63 release
- SWIFT 0.12 (experimental) containers are available.
January 25, 2021
General Availability
AI Platform Deep Learning Containers is now generally available.
Python 2
Python 2 is no longer supported in Deep Learning Containers. Read more about Python 2 support on Google Cloud.
October 28, 2020
- Added PyTorch 1.6 CUDA 11 environments that support A100 GPU accelerators. This special PyTorch build provides another option to add to our A100-compatible TensorFlow Enterprise builds.
August 17, 2020
TensorFlow Enterprise 2.3 environments are now available. These environments include support for A100 GPU accelerators, CUDA 11, and TensorFloat-32 (TF32).
January 08, 2020
TensorFlow Enterprise environments are now available. Use TensorFlow Enterprise with Deep Learning Containers.
June 24, 2019
AI Platform Deep Learning Containers is now available in beta. AI Platform Deep Learning Containers lets you quickly prototype with a portable and consistent environment for developing, testing, and deploying your AI applications.
Visit the AI Platform Deep Learning Containers overview and the guide to getting started with a local deep learning container.