"//tensorflow/core:framework",
            "//tensorflow/core:framework_lite",
            "//tensorflow/core:protos_all_cc",
            "@local_tsl//tsl/framework:device_id_utils",
            "@local_tsl//tsl/platform:statusor",
            "@local_xla//xla/stream_executor",
        ],
    }),
)

cc_library(
    name = "kernels_experimental_hdrs",

  if (TF_GetCode(status) != TF_OK) return;

  // unwrap op_ and set step_id only if valid step id value was set.
  // Currently only required for non-TFRT use cases, e.g., EagerOp.
  if (step_id_.has_value()) {
    tensorflow::unwrap(op_.get())->SetStepId(step_id_.value());
  }

  TFE_Execute(op_.get(), unwrapped_results.data(), &real_num_outputs, status);

  TFE_OpSetAttrInt(op, "group_size", group_size);
  TFE_OpSetAttrInt(op, "group_key", 123);
  TFE_OpSetAttrInt(op, "instance_key", 456);
  TFE_OpSetAttrString(op, "merge_op", "Add", 3);
  TFE_OpSetAttrString(op, "final_op", "Id", 2);
  std::vector<int64_t> subdiv_offsets;
  TFE_OpSetAttrIntList(op, "subdiv_offsets", subdiv_offsets.data(),
                       subdiv_offsets.size());

  return op;
}

  testsuite = ElemTree.SubElement(testsuites, 'testsuite')
  for url, invocation_results in result_store_dict.items():
    invocation_id = url.rsplit('/')[-1]
    if verbose:
      print(f'Creating testcase for invocation {invocation_id}')
    status = invocation_results['status']
    command = invocation_results.get('command')
    command_type = invocation_results.get('command_type')

          echo "DATE=$(date +'%Y-%m-%d')" >> "$GITHUB_OUTPUT"
          # Converts r2.9 to just 2.9
          echo "REF=$(echo $GITHUB_REF_NAME | sed 's/r//g')" >> "$GITHUB_OUTPUT"
        id: vars
      -
        name: Build and push
        id: docker_build
        uses: docker/build-push-action@c56af957549030174b10d6867f20e78cfd7debc5 # v3.2.0
        with:
          push: true

  [[ "$KOKORO_JOB_TYPE" == "CONTINUOUS_INTEGRATION" ]] || [[ "$KOKORO_JOB_TYPE" == "RELEASE" ]]
}

# Move into the directory of the script
cd "$(dirname "$0")"

if is_continuous_or_release || [[ -z "$KOKORO_BUILD_ID" ]]; then
  # A continuous job is the only one to publish to latest
  TAG="latest-multi-python"
else
  # If it is a change, grab a good tag for iterative builds
  if [[ -z "${KOKORO_GITHUB_PULL_REQUEST_NUMBER}" ]]; then

    return;
  } else if (context->GetContextId() ==
             tensorflow::EagerContext::kInvalidContextId) {
    status->status = tensorflow::errors::InvalidArgument(
        "Trying to update a context with invalid context id.");
  }
  status->status =
      tensorflow::unwrap(ctx)->GetDistributedManager()->SetOrUpdateServerDef(
          server_def, /*reset_context=*/false, keep_alive_secs,
          init_timeout_in_ms, /*retries=*/0);

  EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  Define(1, {add}, {feed1, feed2}, {add}, {}, true);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s_));
  EXPECT_EQ(string("The source of control edge [id=3 scalar:-1 -> add:-1] "
                   "is not in the body. Encountered while creating "
                   "function 'MyFunc'"),
            string(TF_Message(s_)));
}

        for more details.
    *   Added `dataset_id` to `tf.data.experimental.service.register_dataset`.
        If provided, `tf.data` service will use the provided ID for the dataset.
        If the dataset ID already exists, no new dataset will be registered.
        This is useful if multiple training jobs need to use the same dataset

      # Sharded tests have target names like this:
      # WindowOpsTest.test_tflite_convert0 (<function hann_window at
      #     0x7fc61728dd40>, 10, False, tf.float32)
      # Where 0x... is a thread ID (or something) that is not important for
      # debugging, but breaks this "number of failures" counter because it's
      # different for repetitions of the same test. We use re.sub(r"0x\w+")
      # to remove it.