#ifndef TENSORFLOW_C_C_API_MACROS_INTERNAL_H_
#define TENSORFLOW_C_C_API_MACROS_INTERNAL_H_

#ifdef __cplusplus
#include "tensorflow/core/platform/status.h"

// Macro to verify that the field `struct_size` of STRUCT_OBJ is initialized.
// `struct_size` is used for struct member compatibility check between core TF
// and plug-ins with the same C API minor version. More info here:

                                      int64_t init_timeout_in_ms, int retries,
                                      bool clear_existing_contexts = false) = 0;

  // Initializes context for the local worker and no contexts will be created
  // for remote workers. Currently this only works for resetting context.
  // TODO(b/289445025): Consider removing this when we find a proper fix.

    calls++;
    memset(buffer, 'x', n);
    TF_SetStatus(status, TF_OK, "");
    return n;
  };
  std::vector<char> out;
  // Our fake environment is initialized with the current timestamp.
  std::unique_ptr<NowSecondsEnv> env(new NowSecondsEnv);
  uint64 now = Env::Default()->NowSeconds();
  env->SetNowSeconds(now);
  tf_gcs_filesystem::RamFileBlockCache cache(

_optimizers = _KerasLazyLoader(
    globals(), submodule="optimizers", name="optimizers")
_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)
setattr(_current_module, "metrics", _metrics)
setattr(_current_module, "optimizers", _optimizers)
setattr(_current_module, "initializers", _initializers)

  }
  if (!result.ok()) {
    status->status = result;
    return;
  }

  // Store results in c_outputs[]
  for (int i = 0; i < noutputs; ++i) {
    const Tensor& src = outputs[i];
    if (!src.IsInitialized() || src.NumElements() == 0) {
      c_outputs[i] =
          EmptyTensor(static_cast<TF_DataType>(src.dtype()), src.shape());
      continue;
    }
    c_outputs[i] = TF_TensorFromTensor(src, &status->status);

  //
  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var");

  // 2. Wait for `var` to be created and initialized on the worker.
  TF_Status* status = TF_NewStatus();
  TFE_ContextAsyncWait(ctx_0, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);

  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var2");

  // 2. Wait for `var2` to be created and initialized on the worker.
  TF_Status* status = TF_NewStatus();
  TFE_ContextAsyncWait(ctx_0, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);

  TFE_TensorHandle* h1 = TestVariable(ctx, 2.0, task2_name);
  TFE_TensorHandle* h2 = TestVariable(ctx, 3.0, task0_name);

  // Add a sync point to make sure that variables have been initialized
  // before the function execution starts.
  TFE_ContextAsyncWait(ctx, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Pack 3 variable handles into one TFE_TensorHandle.

    : reader_(nullptr),
      v2_reader_(nullptr),
      var_to_shape_map_(nullptr),
      var_to_data_type_map_(nullptr) {
  // Depending on whether this is a V2 ckpt, initializes "reader_" or
  // "v2_reader_".
  std::vector<string> v2_path;
  if (Env::Default()->GetMatchingPaths(MetaFilename(filename), &v2_path).ok() &&
      !v2_path.empty()) {
    v2_reader_.reset(

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

# Currently pybind extension shared objects must use only C API headers since
# the C API has static initializers duplicated in the Python bindings. So we
# need a second rule that omits .cc files, in
# tensorflow/python:_pywrap_parallel_device.
filegroup(
    name = "lib_headers",
    srcs = ["parallel_device_lib.h"],
)