return StatusFromTF_Status(plugin_status.get());
}

std::string ModularFileSystem::TranslateName(const std::string& name) const {
  if (ops_->translate_name == nullptr) return FileSystem::TranslateName(name);

  char* p = ops_->translate_name(filesystem_.get(), name.c_str());
  CHECK(p != nullptr) << "TranslateName(" << name << ") returned nullptr";

  std::string ret(p);
  // Since `p` is allocated by plugin, free it using plugin's method.

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());

  return op_->SetAttrInt(attr_name, value);
}
Status SetAttrFloat(AbstractOperation* op_, const char* attr_name, float value,
                    ForwardOperation* forward_op_) {
  forward_op_->attrs.Set(attr_name, value);
  return op_->SetAttrFloat(attr_name, value);
}
Status SetAttrBool(AbstractOperation* op_, const char* attr_name, bool value,

    ],
)

filegroup(
    name = "pywrap_tf_session_hdrs",
    srcs = [
        "python_api.h",
    ],
    visibility = [
        "//tensorflow/core:__pkg__",
        "//tensorflow/python:__pkg__",
    ],
)

cc_library(
    name = "tf_attrtype",
    hdrs = ["tf_attrtype.h"],
    visibility = ["//visibility:public"],
)

cc_library(
    name = "c_api_macros_hdrs",
    hdrs = [

extern "C" {
#endif

// Resets `op_to_reset` with `op_or_function_name` and `raw_device_name`. This
// is for performance optimization by reusing an exiting unused op rather than
// creating a new op every time. If `raw_device_name` is `NULL` or empty, it
// does not set the device name. If it's not `NULL`, then it attempts to parse
// and set the device name. It's effectively `TFE_OpSetDevice`, but it is faster

  } while (0)

#define VALIDATE_MEMBER(STRUCT_NAME, STRUCT_OBJ, NAME)           \
  do {                                                           \
    if (STRUCT_OBJ.NAME == 0) {                                  \
      return absl::Status(absl::StatusCode::kFailedPrecondition, \
                          "'" #NAME "' field in " #STRUCT_NAME   \
                          " must be set.");                      \

  tensorflow::DeviceNameUtils::ParseFullName(device_name, &parsed_name);
  std::string device_type = parsed_name.type;
  int device_id = 0;
  if (parsed_name.has_id) {
    device_id = parsed_name.id;
  }

  ctx.device_id = device_id;
  if (device_type == "CPU") {
    ctx.device_type = DLDeviceType::kDLCPU;
  } else if (device_type == "GPU") {
#if TENSORFLOW_USE_ROCM

    tensorflow::NameAttrList func_name;
    func_name.set_name(string(value, value + length));
    op_->node_builder.Attr(attr_name, func_name);
    return absl::OkStatus();
  }
  Status SetAttrTensor(const char* attr_name,
                       AbstractTensorInterface* tensor) override {
    return tensorflow::errors::Unimplemented(
        "SetAttrTensor has not been implemented yet.");
  }

    std::string name = "Conj_Log1p_Grad_X";
    TF_RETURN_IF_ERROR(SafeConj(ctx, X, &temp_output, name.c_str()));

    AbstractTensorHandlePtr Conj_X(temp_output);

    // Creates Ones
    name = "OnesLike_Log1p_Grad_X";
    TF_RETURN_IF_ERROR(OnesLike(ctx, Conj_X.get(), &temp_output, name.c_str()));

    AbstractTensorHandlePtr Ones_X(temp_output);

    name = "Add_Log1p_Grad_X";

  }
}

void TFE_OpSetAttrInt(TFE_Op* op, const char* attr_name, int64_t value) {
  auto s = tensorflow::unwrap(op)->SetAttrInt(attr_name, value);
  if (!s.ok()) {
    LOG(WARNING) << "Unable to set attribute: " << attr_name;
  }
}

void TFE_OpSetAttrFloat(TFE_Op* op, const char* attr_name, float value) {
  auto s = tensorflow::unwrap(op)->SetAttrFloat(attr_name, value);
  if (!s.ok()) {