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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
# only on affected targets, usually. There are targets in //tensorflow/lite that # don't pass --nobuild, so they're on their own. # # Although buildifier checks for formatting as well, "bazel build nobuild" # checks for cross-file issues like bad includes or missing BUILD definitions. # # We can't test on the windows toolchains because they're using a legacy
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ci/official/envs/linux_arm64
# despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python TFCI_DOCKER_PULL_ENABLE=1 TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-linux-arm64" TFCI_OUTPUT_DIR=build_output TFCI_WHL_AUDIT_ENABLE=1
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tensorflow/c/eager/BUILD
"tf_cc_test", "tf_copts", "tf_cuda_cc_test", "tf_cuda_library", ) load("//tensorflow:tensorflow.default.bzl", "cc_header_only_library", "filegroup") load( "//tensorflow/core/platform:build_config_root.bzl", "tf_cuda_tests_tags", ) load("//tensorflow/core/platform:rules_cc.bzl", "cc_library") package( # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
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ci/official/README.md
# # Bazel will cache your builds in tensorflow/build_output/cache, # and will also try using public build cache results to speed up # your builds. This usually saves a lot of time, especially when # re-running tests. However, note that: # # - New environments like new CUDA versions, changes to manylinux, # compilers, etc. can cause undefined behavior such as build failures # or tests passing incorrectly.
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CONTRIBUTING.md
* [JavaScript/TypeScript license example](https://github.com/tensorflow/tensorboard/blob/master/tensorboard/components/tf_backend/backend.ts#L1) Bazel BUILD files also need to include a license section, e.g., [BUILD example](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/BUILD#L61). #### C++ coding style
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ci/official/utilities/cleanup_summary.sh
can view more detailed results that are probably easier to read than this log. Try the links below: EOF # Find any "Streaming build results to" line, then print the last word in it, # and don't print duplicates awk '/Streaming build results to/ {print $NF}' "$TFCI_OUTPUT_DIR/script.log" | uniq } # Print out any ResultStore URLs for Bazel invocations' results.
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
labels: 'comp:lite-in-play-services' --- **System information** - Android Device information (use `adb shell getprop ro.build.fingerprint` if possible): - TensorFlow Lite in Play Services SDK version (found in `build.gradle`): - Google Play Services version (`Settings` > `Apps` > `Google Play Services` > `App details`): **Standalone code to reproduce the issue**
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.pylintrc
tensorflow/tools/ci_build/pylintrc...
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WORKSPACE
# buildifier: disable=load-on-top workspace(name = "org_tensorflow") # buildifier: disable=load-on-top # We must initialize hermetic python first. load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") http_archive( name = "bazel_skylib", sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506", urls = [
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.github/ISSUE_TEMPLATE/tflite-converter-issue.md
#### Option A: Reference colab notebooks 1) Reference [TensorFlow Model Colab](https://colab.research.google.com/gist/ymodak/e96a4270b953201d5362c61c1e8b78aa/tensorflow-datasets.ipynb?authuser=1): Demonstrate how to build your TF model.
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