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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. # # Pass --config=pip to run the same suite of tests. If you want to run just one # test for investigation, you'll need --config=pip_venv instead, and then you
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ci/official/README.md
******************************************************************************** ## TensorFlow's Official CI and Build/Test Scripts TensorFlow's official CI jobs run the scripts in this folder. Our internal CI system, Kokoro, schedules our CI jobs by combining a build script with a file from the `envs` directory that is filled with configuration options: - Nightly jobs (Run nightly on the `nightly` branch)
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import # the folder instead of the venv package. # # Pass --config=pip to run the same suite of tests. If you want to run just one # test for investigation, you'll need --config=pip_venv instead, and then you
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
"//tensorflow/tools/lib_package:jnilicenses_generate" } # This test ensures that all the targets built into the Python package include # their dependencies. It's a rewritten version of the "smoke test", an older # Python script that was very difficult to understand. See # https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/pip_smoke_test.py @test "Pip package includes all required //tensorflow dependencies" {
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LICENSE
this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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RELEASE.md
semantics to match NumPy. * `tf.split` now takes arguments in a reversed order and with different keywords. In particular, we now match NumPy order as `tf.split(value, num_or_size_splits, axis)`. * `tf.sparse_split` now takes arguments in reversed order and with different keywords. In particular we now match NumPy order as `tf.sparse_split(sp_input, num_split, axis)`. NOTE: we have
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ci/devinfra/README.md
# DevInfra CI Directory > **Warning** This folder is still under construction. It is part of an ongoing > effort to improve the structure of CI and build related files within the > TensorFlow repo. This warning will be removed when the contents of this > directory are stable and appropriate documentation around its usage is in > place. Maintainer: TensorFlow DevInfra Issue Reporting: File an issue against this repo and tag
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ci/devinfra/docker_windows/Dockerfile
| Select ifIndex).ifIndex; \ New-NetRoute -DestinationPrefix 169.254.169.254/32 -InterfaceIndex $ifIndex -NextHop $gateway # Enable Long Paths for Win32 File/Folder APIs. RUN New-ItemProperty -Path HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem \ -Name LongPathsEnabled -Value 1 -PropertyType DWORD -Force # Install Visual C++ Redistributable for Visual Studio 2015-2022.
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ci/official/utilities/code_check_full.bats
"//tensorflow/tools/lib_package:jnilicenses_generate" } # This test ensures that all the targets built into the Python package include # their dependencies. It's a rewritten version of the "smoke test", an older # Python script that was very difficult to understand. See # https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/pip_smoke_test.py @test "Pip package includes all required //tensorflow dependencies" {
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ci/README.md
The CI folder contains the configuration files and scripts used to build, test, and deploy TensorFlow. This folder is typically used by continuous integration (CI) tools to build and test TensorFlow whenever there is a change to the code. This folder is broken into subfolders that represent the level of support
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