# First, set your TFCI variable to choose the environment settings.
#   TFCI is a comma-separated list of filenames from the envs directory, which
#   are all settings for the scripts. TF's CI jobs are all made of a combination
#   of these env files.
#
#   If you've clicked on a test result from our CI (via a dashboard or GitHub link),
#   click to "Invocation Details" and find BUILD_CONFIG, which will contain a TFCI

  AbstractOperationKind getKind() const { return kind_; }

  // Release any underlying resources, including the interface object.
  //
  // WARNING: The destructor of this class is marked as protected to disallow
  // clients from directly destroying this object since it may manage it's own
  // lifetime through ref counting. Thus this must be allocated on the heap and
  // clients MUST call Release() in order to destroy an instance of this class.

It is possible to run multiple TensorFlow models in parallel. For example,
`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are
tenant isolation, resource allocation, model sharing and hardware attacks.

         * All you need is a good internet connection and you are all set.
      * Try to build TF from sources by changing CPU optimization flags.
   
   *Please let us know if this helps.*
   
windows_comment: >
   From the stack trace it looks like you are hitting windows path length limit.
      * Try to disable path length limit on Windows 10.

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
set -euxo pipefail

# Run this from inside the tensorflow github directory.
# Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file"
# Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl"
# 

// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,

labels: 'TFLiteConverter'

---

### 1. System information

- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installation (pip package or built from source):
- TensorFlow library (version, if pip package or github SHA, if built from source):

### 2. Code

Provide code to help us reproduce your issues using one of the following options:

#### Option A: Reference colab notebooks

==============================================================================*/

#include "tensorflow/c/eager/dlpack.h"

#include <vector>

#include "absl/strings/str_join.h"
#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

void TestHandleFromDLPack(TF_Status* status, TFE_Context* ctx,

#
# setup.packages.sh: Given a list of Ubuntu packages, install them and clean up.
# Usage: setup.packages.sh <package_list.txt>
set -e

# Prevent apt install tzinfo from asking our location (assumes UTC)
export DEBIAN_FRONTEND=noninteractive

apt-get update
# Remove commented lines and blank lines
apt-get install -y --no-install-recommends $(sed -e '/^\s*#.*$/d' -e '/^\s*$/d' "$1" | sort -u)

# limitations under the License.
# ==============================================================================

# Need a newer version of patchelf as the installed version is buggy in 20.04
# so get patchelf source from 22.04 ie 'jammy' and build it to avoid dependency
# problems that would occur with a binary package

mkdir -p /patchelf
cd /patchelf
echo deb-src http://ports.ubuntu.com/ubuntu-ports/ jammy universe>>/etc/apt/sources.list