commit | f7859be0008d00598965a554feac23132d0cc8c3 | [log] [tgz] |
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author | Nick Felt <nickfelt@google.com> | Wed Apr 07 19:58:57 2021 -0700 |
committer | TensorFlower Gardener <gardener@tensorflow.org> | Wed Apr 07 20:04:15 2021 -0700 |
tree | 929625478ce7a2c645ba077536b2cd04c5522a7e | |
parent | 5f7c36be8e5138657a23eb1ff04526a46c5a1605 [diff] |
Enable experimental SavedModel support for SummaryWriter using TrackableResource This introduces a new `experimental_trackable` boolean argument to `tf.summary.create_file_writer()`. If True (default is False), the created `SummaryWriter` will be a `tf.saved_model.experimental.TrackableResource`, allowing the writer to be saved in a SavedModel as a property on a `tf.Module`, and then used within @tf.function methods on the module. There are a couple significant limitations to this support: 1) The logdir passed to `create_file_writer()` will be baked into the resulting SavedModel and cannot be changed later. One workaround is to specify a relative path, and then ensure that any code loading the SavedModel is using a working directory into which logs can be written. 2) Initializing the SavedModel resources (e.g. when loading it back into Python) will recreate the writer and open a new file, which may be a surprising side effect. Possible future solutions would be deferring either the writer creation or the opening of the file. PiperOrigin-RevId: 367347580 Change-Id: Ib6b614aaf5edb248e7b6de690d9f3d367a4c97cd
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.
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$ 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.
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$ python
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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 | Status Temporarily Unavailable | Nightly Binary Official GCS |
Libtensorflow Linux CPU | Status Temporarily Unavailable | Nightly Binary Official GCS |
Libtensorflow Linux GPU | Status Temporarily Unavailable | Nightly Binary Official GCS |
Libtensorflow Windows CPU | Status Temporarily Unavailable | Nightly Binary Official GCS |
Libtensorflow Windows GPU | Status Temporarily Unavailable | Nightly Binary 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) | 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 |
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