TF_Function* function,
                                                  TF_Status* status);

// Removes a function from the context. Once removed, you can no longer
// TFE_Execute it or TFE_Execute any TFE_Op which has it as an attribute or any
// other function which calls it as an attribute.
TF_CAPI_EXPORT extern void TFE_ContextRemoveFunction(TFE_Context* ctx,

    unwrapped_outputs.push_back(handle);
  }
  for (int i = 0; i < *num_outputs; ++i) {
    auto logged_tensor = std::make_unique<LoggedTensor>(unwrapped_outputs[i]);
    outputs[i] = MakeLoggedTensorHandle(context, dev->device_name,
                                        std::move(logged_tensor), s);
  }
  *(dev->executed_flag) = true;
}

void DeleteLoggingDevice(void* device_info) {

// Builds the while loop specified by `params` and returns the output tensors of
// the while loop in `outputs`. `outputs` should be allocated to size
// `params.ninputs`.
//
// `params` is no longer valid once this returns.
//
// Either this or TF_AbortWhile() must be called after a successful
// TF_NewWhile() call.
TF_CAPI_EXPORT extern void TF_FinishWhile(const TF_WhileParams* params,

                           bool* executed_flag, TFE_CustomDevice** device,
                           void** device_info);
TFE_TensorHandle* UnpackTensorHandle(TFE_TensorHandle* logged_tensor_handle,
                                     TF_Status* status);

  env->SetNowSeconds(3);
  int value = 0;
  EXPECT_TRUE(cache.Lookup(key, &value));
  EXPECT_EQ(value, 42);
  // 2 seconds after the most recent insertion, the entry is no longer valid.
  env->SetNowSeconds(4);
  EXPECT_FALSE(cache.Lookup(key, &value));
  // Re-insert the entry.
  cache.Insert(key, 43);
  EXPECT_TRUE(cache.Lookup(key, &value));
  EXPECT_EQ(value, 43);

  status = env_->NewRandomAccessFile(filepath, &read_file);
  if (!status.ok())
    GTEST_SKIP() << "NewRandomAccessFile() not supported: " << status;

  char scratch[64 /* must be bigger than test_data */] = {0};
  StringPiece result;
  // read at least 1 byte more than test_data
  status = read_file->Read(0, test_data.size() + 1, &result, scratch);

    define_values = {"__TENSORFLOW_NO_LGPL_DEPS__": "1"},
    visibility = ["//visibility:public"],
)

# Config setting that disables the default logger, only logging
# to registered TFLogSinks
config_setting(
    name = "no_default_logger",
    define_values = {"no_default_logger": "true"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "force_rtti",
    define_values = {

# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --enable_platform_specific_config

# Enable XLA support by default.
build --define=with_xla_support=true

# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --config=short_logs

# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --config=v2

# Disable AWS/HDFS support by default

    # gcc on ppc64le does not support -march, use mcpu instead
    default_cc_opt_flags = '-mcpu=native'
  elif is_windows():
    default_cc_opt_flags = '/arch:AVX'
  else:
    # On all other platforms, no longer use `-march=native` as this can result
    # in instructions that are too modern being generated. Users that want
    # maximum performance should compile TF in their environment and can pass
    # `-march=native` there.

#   variables in between script executions. To forcibly remove the
#   container and start fresh, run "docker rm -f tf". Removing the container
#   destroys some temporary bazel data and causes longer builds.
#
#   You will need the NVIDIA Container Toolkit for GPU testing:
#   https://github.com/NVIDIA/nvidia-container-toolkit
#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you