debugging information with `--config=dbg`, as issues occur on Linux if
there is too much debug info (see [this GitHub
issue](https://github.com/tensorflow/tensorflow/issues/48919) for context). If
you want to debug a kernel, you can compile specific files with `-g` using the
`--per_file_copt` bazel option. For example, if you want to debug the Identity
op, which are in files starting with `identity_op`, you can run

```bash

      /*device_mgr_owned*/ true, std::move(r),
      /*cluster_flr=*/nullptr,
      /*collective_executor_mgr=*/nullptr,
      /*run_eager_op_as_function=*/opts->run_eager_op_as_function,
      /*jit_compile_rewrite=*/opts->jit_compile_rewrite);
#if !defined(IS_MOBILE_PLATFORM)
  eager_context->SetDistributedManager(
      std::make_unique<tensorflow::EagerContextDistributedManager>(
          eager_context));

                                                       unsigned char enable,
                                                       TF_Status* status);

// Enables rewrite jit_compile functions.
TF_CAPI_EXPORT void TFE_ContextSetJitCompileRewrite(TFE_Context* ctx,
                                                    unsigned char enable,
                                                    TF_Status* status);

        "@local_xla//xla/tsl/c:tsl_status",
    ] + select({
        "//tensorflow:with_xla_support": [
            "//tensorflow/compiler/jit",
            "//tensorflow/compiler/tf2xla:xla_compiler",
        ],
        "//conditions:default": [],
    }) + if_tensorrt([
        "//tensorflow/compiler/tf2tensorrt:trt_convert_api",
    ]),
)

# Check that c_api_no_xla does not depend on xla.
check_deps(

        case 128:
          *tf_dtype = TF_DataType::TF_COMPLEX128;
          return absl::OkStatus();
        default:
          return tensorflow::errors::InvalidArgument(
              "Unsupported Complex bits: ", dtype.bits);
      }
      break;
    default:
      return tensorflow::errors::InvalidArgument("Unsupported Type Codes: ",
                                                 dtype.code);
  }
}

            "@com_google_absl//absl/types:variant",
        ],
    }) + select({
        "//tensorflow:with_xla_support": [
            "//tensorflow/compiler/jit",
            "//tensorflow/compiler/jit:xla_device",
            "//tensorflow/compiler/tf2xla:xla_compiler",
        ],
        "//conditions:default": [],
    }) + [
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/core:gpu_runtime",

  # grep patterns for packages whose dependencies can be ignored
  cat > $BATS_TEST_TMPDIR/ignore_deps_for_these_packages <<EOF
//tensorflow/lite
//tensorflow/compiler/mlir/lite
//tensorflow/compiler/mlir/tfrt
//tensorflow/core/runtime_fallback
//tensorflow/core/tfrt
//tensorflow/python/kernel_tests/signal
//tensorflow/examples
//tensorflow/tools/android
//tensorflow/python/eager/benchmarks

#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/c/eager/tfe_op_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/compiler/jit/flags.h"
#include "tensorflow/core/common_runtime/eager/attr_builder.h"
#include "tensorflow/core/common_runtime/eager/context.h"
#include "tensorflow/core/common_runtime/eager/eager_operation.h"