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`

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

      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 }}

)

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",

# 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"

// Wraps a pointer to a context implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this
// interface cannot destruct the underlying context object. Instead, call
// TFE_DeleteContext who calls Release() on the context pointer and deletes
// the TFE_Context structure.
typedef struct TFE_Context TFE_Context;

namespace tensorflow {

DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionContext, TFE_Context);

      parent_op_(parent_op),
      tape_(tape),
      registry_(registry) {
  // TODO(b/172003047): Consider making AbstractOperation RefCounted.
  // parent_op_->Ref();
}
void TapeOperation::Release() {
  // TODO(srbs): Change to Unref().
  delete this;
}
TapeOperation::~TapeOperation() {
  // TODO(b/172003047): Consider making AbstractOperation RefCounted.
  // parent_op->Unref();
}

                                 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);

    TFE_DeleteTensorHandle(var_handle);
  }

  TFE_DeleteTensorHandle(handle_0);

  TFE_DeleteContext(ctx_0);
  TFE_DeleteContext(ctx_1);

  worker_server1.release();
  worker_server2.release();
}

TEST(CAPI, ShareVariableAcrossContextsAfterUpdateContextWorks) {
  tensorflow::ServerDef server_def_0 = GetServerDef(3);

    switch (block->state) {
      case FetchState::ERROR:
        // TF_FALLTHROUGH_INTENDED
      case FetchState::CREATED:
        block->state = FetchState::FETCHING;
        block->mu.Unlock();  // Release the lock while making the API call.
        block->data.clear();
        block->data.resize(block_size_, 0);
        int64_t bytes_transferred;
        bytes_transferred = block_fetcher_(key.first, key.second, block_size_,