running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized
in taking those formats, modifying them, and/or converting them to intermediate
formats that can be processed by TensorFlow.

These modifications and conversions are handled by a variety of libraries that

}

# Note: this is excluded on the full code base, since any submitted code must
# have passed Google's internal style guidelines.
@test "Check formatting for C++ files" {
    skip "clang-format doesn't match internal clang-format checker"
    echo "clang-format is recommended. Here are the suggested changes:"
    echo "============================="
    grep -e '\.h$' -e '\.cc$' $BATS_FILE_TMPDIR/changed_files > $BATS_TEST_TMPDIR/files || true

# Run manually to reformat a file:
# clang-format -i --style=file <file>
BasedOnStyle: Google

`tf.keras`:

Use `clang-tidy` to check your C/C++ changes. To install `clang-tidy` on ubuntu:16.04, do:

```bash
apt-get install -y clang-tidy
```

You can check a C/C++ file by doing:


```bash
clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc
diff <my_cc_file> /tmp/my_cc_file.cc
```

#### Python coding style

Changes to TensorFlow Python code should conform to

        "//tensorflow/core:test_main",
        "//tensorflow/core/kernels:ops_testutil",
        "@com_google_absl//absl/container:inlined_vector",
        "@com_google_absl//absl/strings:str_format",
        "@eigen_archive//:eigen3",
    ],
)

tf_cc_test(
    name = "ops_test",
    size = "medium",
    srcs = ["ops_test.cc"],
    linkopts = select({

      replaced with your own identifying information. (Don't include
      the brackets!)  The text should be enclosed in the appropriate
      comment syntax for the file format. We also recommend that a
      file or class name and description of purpose be included on the
      same "printed page" as the copyright notice for easier
      identification within third-party archives.

        "//perftools/accelerators/xprof/convert/...",
        "//perftools/accelerators/xprof/integration_tests/...",
        "//smartass/brain/configure/...",
        "//tensorflow/...",
        "//tensorflow_decision_forests/...",
        "//tensorflow_federated/...",
        "//tensorflow_models/google/recml/...",
        "//third_party/cloud_tpu/convergence_tools/sdc_monitoring/...",

        "//tensorflow/core/distributed_runtime/rpc:rpc_rendezvous_mgr",
        "//tensorflow/core/distributed_runtime/rpc/eager:grpc_eager_client",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings:str_format",
        "@local_xla//xla/tsl/c:tsl_status_internal",
    ],
    alwayslink = 1,
)

filegroup(
    name = "pywrap_required_hdrs",
    srcs = [
        "abstract_context.h",

# checks for cross-file issues like bad includes or missing BUILD definitions.
#
# We can't test on the windows toolchains because they're using a legacy
# toolchain format (or something) that specifies the toolchain directly instead
# of as a "repository". They can't be valid on Linux because Linux can't do
# anything with a Windows-only toolchain, and bazel errors if trying to build