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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
test:nonpip_filters --test_lang_filters=py --flaky_test_attempts=3 --test_size_filters=small,medium test:nonpip --config=nonpip_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... # "pip tests" run a similar suite of tests the "nonpip" tests, but do something
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
test:nonpip_filters --test_lang_filters=py --flaky_test_attempts=3 --test_size_filters=small,medium test:nonpip --config=nonpip_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... # "pip tests" run a similar suite of tests the "nonpip" tests, but do something
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.bazelrc
# TODO(kanglan): Update windows configs after b/289091160 is fixed build:release_cpu_windows --config=avx_win build:release_cpu_windows --define=no_tensorflow_py_deps=true # Exclude TFRT integration for anything but Linux. build:android --config=no_tfrt build:macos --config=no_tfrt build:windows --config=no_tfrt build:rocm --config=no_tfrt
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ci/README.md
# TensorFlow continuous integration > **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
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ci/official/containers/linux_arm64/build.sh
# - gcr.io/tensorflow-sigs/build-arm64:tf-latest-multi-python set -exo pipefail function is_continuous_or_release() { [[ "$KOKORO_JOB_TYPE" == "CONTINUOUS_INTEGRATION" ]] || [[ "$KOKORO_JOB_TYPE" == "RELEASE" ]] } # Move into the directory of the script cd "$(dirname "$0")" if is_continuous_or_release || [[ -z "$KOKORO_BUILD_ID" ]]; then
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CONTRIBUTING.md
just getting started, GitHub has a [how-to](https://help.github.com/articles/using-pull-requests/). TensorFlow team members will be assigned to review your pull requests. Once the pull requests are approved and pass continuous integration checks, a TensorFlow team member will apply `ready to pull` label to your change. This means we are working on getting your pull request submitted to our internal repository. After
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tensorflow/c/eager/parallel_device/parallel_device_testlib.cc
#include "tensorflow/c/eager/c_api.h" #include "tensorflow/c/eager/c_api_experimental.h" #include "tensorflow/core/platform/test.h" // NOTE(allenl): These tests currently go through TFE_Execute and so are // integration testing rather than purely testing the parallel device. They // correspond fairly well to the implementation, but testing the C++ directly is // another option. namespace tensorflow { namespace parallel_device {
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tensorflow/c/eager/parallel_device/parallel_device_test.cc
#include "tensorflow/c/tf_status_internal.h" #include "tensorflow/core/lib/core/status_test_util.h" #include "tensorflow/core/platform/test.h" // NOTE(allenl): These tests currently go through TFE_Execute and so are // integration testing rather than purely testing the parallel device. They // correspond fairly well to the implementation, but testing the C++ directly is // another option. namespace tensorflow { namespace parallel_device {
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tensorflow/BUILD
"//learning/serving/contrib/tfrt/mlir/canonical_ops/...", "//learning/serving/experimental/remote_predict/...", "//perftools/accelerators/xprof/convert/...", "//perftools/accelerators/xprof/integration_tests/...", "//smartass/brain/configure/...", "//tensorflow/...", "//tensorflow_decision_forests/...", "//tensorflow_federated/...", "//tensorflow_models/google/recml/...",
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RELEASE.md
large-scale modeling with minimal changes to user code. You are welcome to try it out, though be aware that the DTensor API is experimental and up-to backward-incompatible changes. DTensor and Keras integration is published under `tf.keras.dtensor` in this release (refer to the `tf.keras` entry). The tutoral and guide for DTensor will be published on https://www.tensorflow.org/. Please stay tuned.
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