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ci/official/envs/macos_x86
TFCI_MACOS_BAZEL_TEST_DIR_PATH="/System/Volumes/Data/bazel_output" TFCI_MACOS_INSTALL_BAZELISK_ENABLE=1 TFCI_MACOS_INSTALL_BAZELISK_URL="https://github.com/bazelbuild/bazelisk/releases/download/v1.11.0/bazelisk-darwin-amd64" TFCI_MACOS_TWINE_INSTALL_ENABLE=1 TFCI_OUTPUT_DIR=build_output TFCI_WHL_BAZEL_TEST_ENABLE=1 TFCI_WHL_SIZE_LIMIT=255M TFCI_WHL_SIZE_LIMIT_ENABLE=1 # 3.11 is the system python on our images case $TFCI_PYTHON_VERSION in 3.11)
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ci/official/upload.sh
DOWNLOADS="$(mktemp -d)" mkdir -p "$DOWNLOADS" gsutil -m rsync -r "$TFCI_ARTIFACT_STAGING_GCS_URI" "$DOWNLOADS" ls "$DOWNLOADS" # Upload all build artifacts to e.g. gs://tensorflow/versions/2.16.0-rc1 (releases) or # gs://tensorflow/nightly/2.16.0-dev20240105 (nightly), overwriting previous values. if [[ "$TFCI_ARTIFACT_FINAL_GCS_ENABLE" == 1 ]]; then gcloud auth activate-service-account --key-file="$TFCI_ARTIFACT_FINAL_GCS_SA_PATH"
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Jan 24 20:52:12 GMT 2024 - 2.8K bytes - Viewed (0) -
RELEASE.md
Modak, Yasuhiro Matsumoto, Yi Li, Yong Tang, zhaozheng09, Zhoulong Jiang, zzpmiracle # Release 2.6.2 Fixes an issue where `keras`, `tensorflow_estimator` and `tensorboard` were missing proper upper bounds and resulted in broken installs after TF 2.7 release # Release 2.6.1 This release introduces several vulnerability fixes: * Fixes a code injection issue in `saved_model_cli`
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Mon Apr 29 19:17:57 GMT 2024 - 727.7K bytes - Viewed (8) -
ci/official/requirements_updater/BUILD.bazel
) compile_pip_requirements_3_9( name = "requirements_3_9_release", extra_args = [ "--allow-unsafe", "-P keras-nightly", "-P tb-nightly", ], requirements_in = "requirements.in", requirements_txt = "requirements_lock_3_9.txt", ) compile_pip_requirements_3_10( name = "requirements_3_10_release", extra_args = [ "--allow-unsafe", "-P keras-nightly",
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tensorflow/c/eager/c_api_test.cc
if (forward_input) { // Since the input was forwarded, we released the input handle right away // and hence expect the input to be forwarded to the return tensor. EXPECT_EQ(orig_ptr, TF_TensorData(t)); } else { // In async mode we expect forwarding to work without releasing the input // handle since by the time the kernel is executed we have released the // handle in the client code.
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ci/official/envs/linux_x86_cuda
# limitations under the License. # ============================================================================== source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ARGS="--gpus all" TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
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tensorflow/c/eager/c_api_experimental_test.cc
status); EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status); TFE_DeleteContextOptions(opts); TFE_DeleteContext(ctx); TF_DeleteStatus(status); w0.release(); w1.release(); } TEST(CAPI, ShareVariableAcrossContextsAfterUpdateContextWorksWithTimeout) { tensorflow::ServerDef server_def_0 = GetServerDef(3);
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.github/workflows/release-branch-cherrypick.yml
with: title: '${{ github.event.inputs.release_branch }} cherry-pick: ${{ steps.cherrypick.outputs.SHORTSHA }} "${{ steps.cherrypick.outputs.TITLE }}"' committer: TensorFlow Release Automation <******@****.***> token: ${{ secrets.JENKINS_TOKEN }} base: ${{ github.event.inputs.release_branch }} branch: ${{ github.event.inputs.release_branch }}-${{ steps.cherrypick.outputs.SHORTSHA }}
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ci/official/requirements_updater/release_updater.sh
do cp ../../../requirements_lock_"$VERSION".txt "requirements_lock_"$VERSION".txt" bazel run \ --experimental_convenience_symlinks=ignore \ --enable_bzlmod=false \ //:requirements_"$VERSION"_release.update sed -i '/^#/d' requirements_lock_"$VERSION".txt mv "requirements_lock_"$VERSION".txt" ../../../requirements_lock_"$VERSION".txt done
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tensorflow/c/eager/tape.h
// Accumulate runs the gradient computation immediately. // // Keeps references to Tensors watched via Watch and computed in Accumulate // corresponding to output_tensors, and releases these references in its // destructor. However, waiting until the destructor runs loses the memory // efficiency of forward-mode autodiff. Instead, language bindings should call
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