1.  The issue should be related to the repo it is created in.

**Here's why we have this policy:** We want to focus on the work that benefits
the whole community, e.g., fixing bugs and adding features. Individual support
should be sought on Stack Overflow or other non-GitHub channels. It helps us to

  Tensor input(tensorflow::DT_STRING, TensorShape({4}));
  for (int64_t i = 0; i < input.NumElements(); ++i) {
    tensorflow::Example example;
    auto* feature_map = example.mutable_features()->mutable_feature();
    (*feature_map)["x"].mutable_float_list()->add_value(i);
    input.flat<tstring>()(i) = example.SerializeAsString();
  }

  const tensorflow::string input_op_name(

make sure your changes are consistent with the guidelines and follow the
TensorFlow coding style.

#### General guidelines and philosophy for contribution

*   Include unit tests when you contribute new features, as they help to a)
    prove that your code works correctly, and b) guard against future breaking
    changes to lower the maintenance cost.
*   Bug fixes also generally require unit tests, because the presence of bugs

  virtual void ResetGlobalRendezvousForFunction() = 0;

  //===--------------------------------------------------------------------===//
  // Following are features in current TF Eager Runtime.
  // TODO(tfrt-devs): Figure out a way to deprecate following features after
  // migrated to TFRT.
  //===--------------------------------------------------------------------===//
  // Clear pending nodes in thread executors and kernel caches.

    *   `CategoryCrossing`: create new categorical features representing
        co-occurrences of previous categorical feature values
    *   `Hashing`: the hashing trick, for large-vocabulary categorical features
    *   `Discretization`: turn continuous numerical features into categorical
        features by binning their values
*   Improved **image preprocessing** layers: `CenterCrop`, `Rescaling`

        ":linux_aarch64",
        ":linux_armhf",
    ],
)

config_setting(
    name = "freebsd",
    values = {"cpu": "freebsd"},
    visibility = ["//visibility:public"],
)

# Features that are default ON are handled differently below.
#
config_setting(
    name = "no_gcp_support",
    define_values = {"no_gcp_support": "true"},
    visibility = ["//visibility:public"],
)

)

cc_library(
    name = "dlpack",
    srcs = ["dlpack.cc"],
    hdrs = ["dlpack.h"],
    copts = tf_copts() + [
        "-fexceptions",
        "-fno-strict-aliasing",
    ],
    features = ["-use_header_modules"],
    visibility = ["//tensorflow:__subpackages__"],
    deps = [
        ":c_api",
        ":c_api_experimental",
        ":tfe_tensorhandle_internal",

build:windows --host_copt=/D_USE_MATH_DEFINES

# Windows has a relatively short command line limit, which TF has begun to hit.
# See https://docs.bazel.build/versions/main/windows.html
build:windows --features=compiler_param_file
build:windows --features=archive_param_file

# Speed Windows compile times. Available in VS 16.4 (we are on 16.11). See
# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion

      '(Experimental) Build kernels into separate shared objects.')
  config_info_line('v1', 'Build with TensorFlow 1 API instead of TF 2 API.')

  print('Preconfigured Bazel build configs to DISABLE default on features:')
  config_info_line('nogcp', 'Disable GCP support.')
  config_info_line('nonccl', 'Disable NVIDIA NCCL support.')


if __name__ == '__main__':