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.github/ISSUE_TEMPLATE/tflite-op-request.md
``` # Copy and paste here ``` **Standalone code to reproduce the issue** Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to Colab/Jupyter/any notebook. Also, please include a link to a GraphDef or the model if possible. **Any other info / logs** Include any logs or source code that would be helpful to diagnose the problem.
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.github/ISSUE_TEMPLATE/tensorflow_issue_template.yaml
id: code-to-reproduce attributes: label: Standalone code to reproduce the issue description: Provide a reproducible test case that is the bare minimum necessary to generate the problem. Please share a link to Colab, Jupyter, or any notebook. placeholder: Tell us what you see! value: render: shell validations: required: true - type: textarea id: logs attributes:
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ci/official/containers/linux_arm64/build.sh
TAG=$(head -n 1 "$KOKORO_PIPER_DIR/presubmit_request.txt" | cut -d" " -f2) else TAG="pr-${KOKORO_GITHUB_PULL_REQUEST_NUMBER}" fi fi # Build for both JAX and TF usage. We do these in one place because they share # almost all of the same cache layers export DOCKER_BUILDKIT=1 for target in jax tf; do IMAGE="gcr.io/tensorflow-sigs/build-arm64:$target-$TAG" docker pull "$IMAGE" || true
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ci/official/containers/linux_arm64/devel.usertools/squash_testlogs.py
r._elem.remove(testsuite._elem) if len(r) > 0: # pylint: disable=g-explicit-length-test result += r # Insert the number of failures for each test to help identify flakes # need to clarify for shard for p in result._elem.xpath(".//error | .//failure"): key = re.sub(r"0x\w+", "", p.getparent().get("name", "")) + p.text p.text = runfiles_matcher.sub("[testroot]/", p.text)
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ci/official/envs/rbe
That setting must exist for this script to function correctly. EOF exit 1 fi TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX" # These flags share the user's gcloud credentials with the container, so that bazel # inside the container can authenticate. Note: TF's CI does not have any credential # stored here.
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.github/ISSUE_TEMPLATE/tflite-other.md
reproduce the issue description: Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to Colab/Jupyter/any notebook. placeholder: Tell us what you see! value: render: shell validations: required: true - type: textarea id: logs attributes: label: Relevant log output description:
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.bazelrc
build:rbe_linux --linkopt=-lrt build:rbe_linux --host_linkopt=-lrt build:rbe_linux --linkopt=-lm build:rbe_linux --host_linkopt=-lm build:rbe_linux_cpu --config=rbe_linux # Linux cpu and cuda builds share the same toolchain now. build:rbe_linux_cpu --host_crosstool_top="@sigbuild-r2.17-clang_config_cuda//crosstool:toolchain" build:rbe_linux_cpu --crosstool_top="@sigbuild-r2.17-clang_config_cuda//crosstool:toolchain"
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
(`Settings` > `Apps` > `Google Play Services` > `App details`): **Standalone code to reproduce the issue** Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to or attach code demonstrating the problem. **Any other info / logs** Include any logs or source code that would be helpful to diagnose the problem.
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ci/official/README.md
# export TFCI=py311,linux_x86,no_docker # Advanced: Use Remote Build Execution (RBE) (internal developers only) # # RBE dramatically speeds up builds and testing. It also gives you a # public URL to share your build results with collaborators. However, # it is only available to a limited set of internal TensorFlow developers. # # RBE is incompatible with local caching, so you must remove
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RELEASE.md
shards to disk. `tf.train.experimental.ShardByTaskPolicy` is the default sharding behavior, but `tf.train.experimental.MaxShardSizePolicy` can be used to shard the checkpoint with a maximum shard file size. Users with advanced use cases can also write their own custom `tf.train.experimental.ShardingCallback`s. * `tf.train.CheckpointOptions`
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