[pull] master from tensorflow:master #389
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…n to the Keras classification tutorial. PiperOrigin-RevId: 566758660
Updated the file as mentioned by MarkDaoust.
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Final copy of change
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1. First the simple version. 2. Then a more complex version. No trying to convert from LookupTable to TextVectorization layer. PiperOrigin-RevId: 569214556
… conda TF 2.14 supports `pip install tensorflow[and-cuda]`, which should totally remove the need for miniconda in the installation process. The Miniconda instructions provided: 1. The CUDA libraries 2. A virtual Python environment These new instructions _only_ provide the CUDA libraries, not a virtual environment. This is consistent with the CPU installation methods. PiperOrigin-RevId: 569336143
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…-built Clang+LLVM-16 binaries during the building TensorFlow from source. PiperOrigin-RevId: 570107458
…on first usage, rather than second; add transition sentence to mixed data types section. PiperOrigin-RevId: 572711158
Added 2 lines of code `import keras`, `@keras.saving.register_keras_serializable()` on top of the Keras Custom model definition because it shows typeerror - "Make sure custom classes are decorated with `@keras.saving.register_keras_serializable()`" after reloading the model when saving as `.keras`. As mentioned in this Saving [Custom objects](https://www.tensorflow.org/guide/keras/serialization_and_saving#custom_objects) definition. Please refer to this replicated working code [gist](https://colab.research.google.com/gist/RenuPatelGoogle/f124503c52144c5ed6e9c79cffcb593d/intro_to_modules.ipynb#scrollTo=hpW-4Dj3Q1Rb) for your reference. Thank you.
Added keras import on top of the code.
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Found one broken link in this tutorial and I have replaced it with right one.
Found one broken link in this tutorial and I have replaced with new one.
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…er it is re-directing to archived repo. PiperOrigin-RevId: 726073729
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…aintain reproducible wheel content and filename results.
It enables ability to pass defines values to `//tensorflow/core/public:release_version`.
Instead of having TF version in three places (`setup.py`, `version.h` and `tensorflow.bzl`), it should be located in one place only. Declaration of TF version in a new `tf_version.bzl` file will allow passing this value to build rules wrapping `setup.py` and `release_version.h`.
Dependency on `//tensorflow/core/public:release_version` should be added if `TF_MAJOR_VERSION, TF_MINOR_VERSION, TF_PATCH_VERSION, TF_VERSION_SUFFIX` values are used in the code.
Dependency on `//tensorflow/core/public:version` should be added if graphDef compatibility versions or checkpoint compatibility versions are used in the code.
The next step would be to change cc_library release_version in the following way:
```
cc_library(
name = "release_version",
hdrs = ["release_version.h"],
defines = [
"TF_MAJOR_VERSION={}".format(MAJOR_VERSION),
"TF_MINOR_VERSION={}".format(MINOR_VERSION),
"TF_PATCH_VERSION={}".format(PATCH_VERSION),
"TF_VERSION_SUFFIX={}".format(TF_SEMANTIC_VERSION_SUFFIX),
],
visibility = ["//visibility:public"],
)
```
The version chunks will be created from the value in `tf_version.bzl`. The version suffix will be created by a new repository rule, and it will be controlled by environment variables.
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This change introduces a uniform way of building the TF wheel and controlling the filename version suffixes. A new repository rule `python_wheel_version_suffix_repository` provides information about project and wheel version suffixes. The final value depends on environment variables passed to Bazel command: `_ML_WHEEL_WHEEL_TYPE, _ML_WHEEL_BUILD_DATE, _ML_WHEEL_GIT_HASH, _ML_WHEEL_VERSION_SUFFIX` `tf_version.bzl` defines the TF project version and loads the version suffix information calculated by `python_wheel_version_suffix_repository`. The targets `//tensorflow/core/public:release_version, //tensorflow:tensorflow_bzl //tensorflow/tools/pip_package:setup_py` use the version chunks defined above. The version of the wheel in the build rule output depends on the environment variables. Environment variables combinations for creating wheels with different versions: * snapshot (default build rule behavior): `--repo_env=ML_WHEEL_TYPE=snapshot` * release: `--repo_env=ML_WHEEL_TYPE=release` * release candidate: `--repo_env=ML_WHEEL_TYPE=release --repo_env=ML_WHEEL_VERSION_SUFFIX=-rc1` * nightly build with date as version suffix: `--repo_env=ML_WHEEL_TYPE=nightly --repo_env=ML_WHEEL_BUILD_DATE=<YYYYmmdd>` * build with git data as version suffix: `--repo_env=ML_WHEEL_TYPE=custom --repo_env=ML_WHEEL_BUILD_DATE=$(git show -s --format=%as HEAD) --repo_env=ML_WHEEL_GIT_HASH=$(git rev-parse HEAD)` PiperOrigin-RevId: 733444080
PiperOrigin-RevId: 733943464
The tag `latest` has been deprecated by NVIDIA: NVIDIA/nvidia-container-toolkit#302 (comment) Therefore, the provided command is deprecated: `docker run --gpus all --rm nvidia/cuda nvidia-smi` Unable to find image 'nvidia/cuda:latest' locally docker: Error response from daemon: manifest for nvidia/cuda:latest not found: manifest unknown: manifest unknown. See 'docker run --help'. sudo docker run --gpus all --rm nvidia/cuda nvidia-smi Unable to find image 'nvidia/cuda:latest' locally docker: Error response from daemon: manifest for nvidia/cuda:latest not found: manifest unknown: manifest unknown. See 'docker run --help'. Updated command found here: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/sample-workload.html#running-a-sample-workload-with-docker
Remove sudo Co-authored-by: Mihai Maruseac <[email protected]>
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…-matches PiperOrigin-RevId: 752645444
…ectory. PiperOrigin-RevId: 760248423
…cation PiperOrigin-RevId: 770888890
Fix broken Microsoft VC++ link
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PiperOrigin-RevId: 789619765
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