#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/core/platform/test.h"

// NOTE(allenl): These tests currently go through TFE_Execute and so are
// integration testing rather than purely testing the parallel device. They
// correspond fairly well to the implementation, but testing the C++ directly is
// another option.

namespace tensorflow {

using MaybeParallelTensorUnowned =
    absl::variant<ParallelTensor*, TFE_TensorHandle*>;

// A ParallelDevice on its own is not registered with a TFE_Context, and so has
// no device name (e.g. for `tf.device`). `NamedParallelDevice` associates a
// name with it, which lets us pack its `ParallelTensor`s into TFE_TensorHandles
// placed on the parallel device.
class NamedParallelDevice {

  string lib_path =
      tensorflow::GetDataDependencyFilepath(tensorflow::io::JoinPath(
          "tensorflow", "c", "experimental", "stream_executor", "test",
          "test_pluggable_device.so"));
  TF_Library* lib = TF_LoadPluggableDeviceLibrary(lib_path.c_str(), status);
  TF_Code code = TF_GetCode(status);
  string status_msg(TF_Message(status));
  TF_DeleteStatus(status);

  if (use_function) {
    const char* fn_name = "test_fn";
    core::RefCountPtr<AbstractFunction> scoped_func;
    // Returning null tensors from a tf.function is not supported, so we keep
    // track of indices in the model's outputs are nullptr in this set.
    // The FunctionDef only outputs the non-null tensors. We later pad the
    // function op outputs to have nullptrs at the `null_indices`.

          info->plugin_memory_allocate, info->plugin_memory_free));
}

// Registers filesystem at `index`, if plugin is providing valid information.
//
// Extracted to a separate function so that pointers inside `info` are freed
// by the caller regardless of whether validation/registration failed or not.
//
// Must be called only with `index` a valid index in `info->ops`.

  tensorflow::unwrap(ctx)->SetThreadLocalDevicePlacementPolicy(
      static_cast<tensorflow::ContextDevicePlacementPolicy>(policy));
}

// Note: this function looks up a thread local policy. So it should be called in
// the appropriate client thread. In particular, in async mode, it may not be
// safe to call this function from the async EagerExecutor threads.

  } else if (!absl::SimpleAtoi(content_length->second, &read)) {
    TF_SetStatus(status, TF_UNKNOWN, "Could not get content-length header");
    return -1;
  }
  // `TF_OUT_OF_RANGE` isn't considered as an error. So we clear it here.
  TF_SetStatus(status, TF_OK, "");
  TF_VLog(1, "Successful read of %s @ %u of size: %u", path.c_str(), offset,
          read);
  stream.read(buffer, read);
  read = stream.gcount();

  // `gradient_checker` only works with model that returns only 1 tensor.
  // Although, `ops::SparseSoftmaxCrossEntropyWithLogits` returns 2 tensors, the
  // second tensor isn't needed for computing gradient so we could safely drop
  // it.
  outputs[0] = loss;
  backprop->Unref();
  return absl::OkStatus();
}

Status BiasAddModel(AbstractContext* ctx,
                    absl::Span<AbstractTensorHandle* const> inputs,

      ptr = new const char*[strs.size()];
      for (size_t i = 0; i < strs.size(); ++i) {
        ptr[i] = strs[i].c_str();
      }
    }
    return ptr;
  }

  // An explicit `num_opers` is needed so that we can distinguish between the
  // case of no operations specified (-1) and the case of an empty set of
  // operations specified (0).
  void DefineT(int num_opers, const std::vector<TF_Operation*>& opers,

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  std::string translated_name = TranslateName(dir);
  // Note that `children` is allocated by the plugin and freed by core
  // TensorFlow, so we need to use `plugin_memory_free_` here.
  char** children = nullptr;
  const int num_children =
      ops_->get_children(filesystem_.get(), translated_name.c_str(), &children,
                         plugin_status.get());