CI_DOCKER_BUILD_EXTRA_PARAMS="--build-arg py_major_minor_version=${{ matrix.pyver }} --build-arg is_nightly=${is_nightly} --build-arg tf_project_name=${tf_project_name}" \

          echo "PyPI project name:" $tf_project_name
          CI_DOCKER_BUILD_EXTRA_PARAMS="--build-arg py_major_minor_version=${{ matrix.pyver }} --build-arg is_nightly=${is_nightly} --build-arg tf_project_name=${tf_project_name}" \
          ./tensorflow/tools/ci_build/ci_build.sh cpu.arm64 bash tensorflow/tools/ci_build/rel/ubuntu/cpu_arm64_test_build.sh

            .NewSubScope(child_scope_name);

    if (dx != nullptr) {
      std::vector<tensorflow::Output> dx_arg = OutputsFromTFOutputs(dx, ny);
      status->status =
          AddSymbolicGradients(scope, y_arg, x_arg, dx_arg, &dy_arg);
    } else {
      status->status = AddSymbolicGradients(scope, y_arg, x_arg, &dy_arg);
    }

    // Update g->name_map with the name_map from the scope, which will contain

RUN dpkg -i /patchelf/patchelf_0.14.3-1_arm64.deb

# All lines past this point are reset when $CACHEBUSTER is set. We need this
# for Python specifically because we install some nightly packages which are
# likely to change daily.
ARG CACHEBUSTER=0
RUN echo $CACHEBUSTER

# Setup build and environment
COPY devel.usertools /usertools
COPY devel.bashrc /root/.bashrc
COPY ld.so.conf /dt10/etc/

# Setup JAX Python environment.
FROM devel as jax

# JAX requirements, passed into container by defining the ARG 
# REQUIREMENTS_FILE=jax.requirements.txt


setuptools
wheel
cloudpickle
colorama>=0.4.4
matplotlib
pillow>=9.1.0
rich
absl-py
portpicker
six
opt-einsum
auditwheel
typing_extensions
importlib_metadata>=4.6
numpy==1.26.0;python_version=="3.12"
numpy==1.23.4;python_version=="3.11"
numpy==1.22.4;python_version<"3.11"
scipy==1.11.2;python_version=="3.12"

TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_cpu"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=tensorflow/build:2.16-python${TFCI_PYTHON_VERSION}
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--build-arg PYTHON_VERSION=python$TFCI_PYTHON_VERSION --target=devel tensorflow/tools/tf_sig_build_dockerfiles"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-x86_64"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_AUDIT_ENABLE=1

                                                  TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<tensorflow::OpKernelContext*>(ctx);
  const tensorflow::Tensor& arg_tensor = cc_ctx->input(index);
  absl::Status cc_status;
  if (arg_tensor.dtype() != tensorflow::DT_RESOURCE) {
    cc_status = absl::InvalidArgumentError(
        absl::StrCat("Trying to obtain resource handle from Input[", index,

  # Due to some flakiness of resources pulled in the build, allow the docker
  # command to reattempt build a few times in the case of failure (b/302558736)
  set +e
  for i in $(seq 1 5)
  do
    docker build \
    --build-arg REQUIREMENTS_FILE=jax.requirements.txt \
    --target=$target \
    --cache-from "$IMAGE" \
    -t "$IMAGE"  . && break
  done
  final=$?
  if [ $final -ne 0 ]; then
    exit $final
  fi
  set -e

  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      "    signature {"
      "      name: 'AddVariablesFunction'"
      "      input_arg {"
      "        name: 'var'"
      "        type: DT_RESOURCE"
      "      }"
      "      output_arg {"
      "        name: 'sum'"
      "        type: DT_FLOAT"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read0'"

# variable that doesn't exist. Please keep this list in alphabetical order.
#
# Find usage in scripts with e.g.:
#   cd ci/official
#   ls *.sh utilities/*.sh | xargs grep -H --color=always TFCI_ARG_HERE
# You may also get an overview, e.g.:
#   cd ci/official
#   grep -o '^TFCI\w*' envs/ci_default | xargs -n 1 -I{} bash -c "echo; echo {}; grep -R -H --exclude-dir=envs --color=always '{}'"
TFCI_ARTIFACT_FINAL_GCS_ENABLE=