# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
# Sourcing this enables Bazel remote cache (read and write)
# Note that "_push" cache configs write to GCS buckets and require
# authentication. If you are not a Googler, source "public_cache" to enable the
# public read-only cache.

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
#
# Changes the behavior in pycpp.sh from "run all tests" to "verify that all
# tests can compile." Used in some CI jobs (macOS and Linux Arm64) where test
# execution is too expensive.
TFCI_PYCPP_SWAP_TO_BUILD_ENABLE=1

# TF_LoadLibrary/tf.load_op_library) register their ops and kernels with this
# shared object directly.
#
# For example, from Python tf.load_op_library loads a custom op library (via
# dlopen() on Linux), the library finds libtensorflow_framework.so (no
# filesystem search takes place, since libtensorflow_framework.so has already
# been loaded by pywrap_tensorflow) and registers its ops and kernels via

# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
# Disable Docker

lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0

# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch

            "//tensorflow/core/common_runtime/eager:eager_operation",
            "//tensorflow/core/common_runtime/eager:execute",
            "//tensorflow/core/common_runtime/eager:kernel_and_device",
            "//tensorflow/core/common_runtime/eager:tensor_handle",
            "//tensorflow/core/lib/llvm_rtti",
            "@com_google_absl//absl/types:variant",
        ],
    }) + select({

abstract: TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives...

> effort to improve the structure of CI and build related files within the
> TensorFlow repo. This warning will be removed when the contents of this
> directory are stable and appropriate documentation around its usage is in
> place.

Maintainer: TensorFlow DevInfra

Issue Reporting: File an issue against this repo and tag
[@devinfra](https://github.com/orgs/tensorflow/teams/devinfra)

# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those
# targets.
license_query() {
 bazel cquery --experimental_cc_shared_library "$1" --keep_going \
  | grep -e "^//" -e "^@" \
  | grep -E -v "^//tensorflow" \
  | sed -e 's|:.*||' \
  | sort -u
}

# Verify that, given a build target and a license-list generator target, all of

#     release_cpu_linux:               Toolchain and CUDA options for Linux CPU builds.
#     release_gpu_linux:               Toolchain and CUDA options for Linux GPU builds.
#     release_cpu_macos:               Toolchain and CUDA options for MacOS CPU builds.
#     release_cpu_windows:             Toolchain and CUDA options for Windows CPU builds.

# Default build options. These are applied first and unconditionally.