commit | d2504636c4bda94de5ac298774b9585002708248 | [log] [tgz] |
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author | Robert David <lrdx@google.com> | Thu Nov 19 10:35:21 2020 -0800 |
committer | TensorFlower Gardener <gardener@tensorflow.org> | Thu Nov 19 10:47:07 2020 -0800 |
tree | ddbec4e57335e558acd18bd94278177b24621e0c | |
parent | 649966f38f533a7e74913d8edf2989325a186a38 [diff] |
Bump FULLY_CONNECTED's supported version to v9. New options and features introduced between v4 and v9: v5: keep_num_dims: Not supported. Added check to FullyConnectedOperationParser to explicitly fail when flag is set. v6: No bias provided: Was already supported in GPU, but the versioning not allowed to run these models. v7: INT16 input/output. Integer input/output tensors are not supported. v8: sparse_weight: Sparsity is not supported. Added check to ObjectReader::ReadTensor to reject sparse tensors. v9: asymmetric_quantize_inputs: Controls on-the-fly quantization behavior with hybrid quant. Not relevant for GPU, as all operations are in floating-point. PiperOrigin-RevId: 343320830 Change-Id: I4198173a83f1063099df18f531c478208f3594a6
Documentation |
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TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.
TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.
Keep up-to-date with release announcements and security updates by subscribing to announce@tensorflow.org. See all the mailing lists.
See the TensorFlow install guide for the pip package, to enable GPU support, use a Docker container, and build from source.
To install the current release, which includes support for CUDA-enabled GPU cards (Ubuntu and Windows):
$ pip install tensorflow
A smaller CPU-only package is also available:
$ pip install tensorflow-cpu
To update TensorFlow to the latest version, add --upgrade
flag to the above commands.
Nightly binaries are available for testing using the tf-nightly and tf-nightly-cpu packages on PyPi.
$ python
>>> import tensorflow as tf >>> tf.add(1, 2).numpy() 3 >>> hello = tf.constant('Hello, TensorFlow!') >>> hello.numpy() b'Hello, TensorFlow!'
For more examples, see the TensorFlow tutorials.
If you want to contribute to TensorFlow, be sure to review the contribution guidelines. This project adheres to TensorFlow's code of conduct. By participating, you are expected to uphold this code.
We use GitHub issues for tracking requests and bugs, please see TensorFlow Discuss for general questions and discussion, and please direct specific questions to Stack Overflow.
The TensorFlow project strives to abide by generally accepted best practices in open-source software development:
Build Type | Status | Artifacts |
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Linux CPU | PyPI | |
Linux GPU | PyPI | |
Linux XLA | TBA | |
macOS | PyPI | |
Windows CPU | PyPI | |
Windows GPU | PyPI | |
Android | ||
Raspberry Pi 0 and 1 | Py3 | |
Raspberry Pi 2 and 3 | Py3 | |
Libtensorflow MacOS CPU | Nightly GCS Official GCS | |
Libtensorflow Linux CPU | Nightly GCS Official GCS | |
Libtensorflow Linux GPU | Nightly GCS Official GCS | |
Libtensorflow Windows CPU | Nightly GCS Official GCS | |
Libtensorflow Windows GPU | Nightly GCS Official GCS |
Build Type | Status | Artifacts |
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Linux AMD ROCm GPU Nightly | Nightly | |
Linux AMD ROCm GPU Stable Release | Release 1.15 / 2.x | |
Linux s390x Nightly | Nightly | |
Linux s390x CPU Stable Release | Release | |
Linux ppc64le CPU Nightly | Nightly | |
Linux ppc64le CPU Stable Release | Release 1.15 / 2.x | |
Linux ppc64le GPU Nightly | Nightly | |
Linux ppc64le GPU Stable Release | Release 1.15 / 2.x | |
Linux aarch64 CPU Nightly (Linaro) Python 3.8 | Nightly | |
Linux aarch64 CPU Stable Release (Linaro) | Release 1.x & 2.x | |
Linux aarch64 CPU Nightly (OpenLab) Python 3.6 | Nightly | |
Linux aarch64 CPU Stable Release (OpenLab) | Release 1.15 / 2.x | |
Linux CPU with Intel oneAPI Deep Neural Network Library (oneDNN) Nightly | Nightly | |
Linux CPU with Intel oneAPI Deep Neural Network Library (oneDNN) Stable Release | Release 1.15 / 2.x | |
Red Hat® Enterprise Linux® 7.6 CPU & GPU Python 2.7, 3.6 | 1.13.1 PyPI |
Container Type | Status | Artifacts |
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TensorFlow aarch64 Neoverse-N1 CPU Stable (Linaro) Debian | Static | Release 2.3 |
Learn more about the TensorFlow community and how to contribute.