"//tensorflow/core/common_runtime/next_pluggable_device/c:tf_rendezvous_c_api",
        "//tensorflow/core/common_runtime/next_pluggable_device/c:tf_rendezvous_c_api_internal",
        "//tensorflow/core/platform:notification",
        "@com_google_absl//absl/status",
        "@com_google_absl//absl/strings",
        "@local_xla//xla/tsl/c:tsl_status_internal",
    ] + select({
        "//tensorflow:android": [

          as modifying the License.

      You may add Your own copyright statement to Your modifications and
      may provide additional or different license terms and conditions
      for use, reproduction, or distribution of Your modifications, or
      for any such Derivative Works as a whole, provided Your use,
      reproduction, and distribution of the Work otherwise complies with

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
have different security properties and provide different levels of confidence
when dealing with untrusted data. Based on the security history of these

    forward compatible code: by explicitly importing either
    `tensorflow.compat.v1` or `tensorflow.compat.v2`, you can ensure that your
    code works without modifications against an installation of 1.15 or 2.0.
*   EagerTensor now supports numpy buffer interface for tensors.
*   Add toggles `tf.enable_control_flow_v2()` and `tf.disable_control_flow_v2()`