// Move all inner ops of the launch to the block containing the launch.
  auto body = launch.GetBody().without_terminator();
  Operation* launch_op = launch.getOperation();
  launch_op->getBlock()->getOperations().splice(
      launch_op->getIterator(), launch.GetBody().getOperations(), body.begin(),
      body.end());

  launch.erase();

  return success();
}

void LaunchToDeviceAttributePass::runOnOperation() {

  // SymbolRefAttrs of all ops are present.
  SymbolTable symbol_table = SymbolTable(getOperation());
  llvm::SetVector<func::FuncOp> reachable_funcs;
  for (auto func : getOperation().getOps<func::FuncOp>()) {
    auto walk_result = func.walk([&](func::CallOp op) -> WalkResult {
      if (!symbol_table.lookup<func::FuncOp>(op.getCallee()))
        return getOperation().emitError()
               << func.getName() << " is not in the funcs allowlist";

    default_device_ = std::string(default_device);
  }

  void runOnOperation() override {
    Builder builder(&getContext());
    Dialect* tf = getContext().getLoadedDialect<TensorFlowDialect>();
    getOperation().walk([&](Operation* op) {
      if (auto device_attr = op->getAttrOfType<StringAttr>(kDeviceAttr)) {
        // We assign default device to ops with device attribute that is empty.
        if (device_attr.getValue().empty()) {

  const Dialect* tf_dialect = getContext().getLoadedDialect("tf");
  if (!tf_dialect) {
    getOperation().emitError() << "'tf' dialect is not registered";
    return signalPassFailure();
  }

  // Get the number of devices per host.
  int device_num = 0;
  mlir::TF::RuntimeDevices devices;
  if (failed(tensorflow::GetDevicesFromOp(
          getOperation()->getParentOfType<ModuleOp>(), &devices)))
    return signalPassFailure();

  // Update types for all layout sensitive results.
  auto layout_sensitive = cast<LayoutSensitiveInterface>(op->getOperation());
  for (unsigned idx : layout_sensitive.GetLayoutDependentResults()) {
    OpResult result = op->getOperation()->getResult(idx);
    result.setType(ShuffleRankedTensorType(result.getType(), perm));
  }

  return success();
}

    : public impl::DeviceIndexSelectorPassBase<DeviceIndexSelector> {
  void runOnOperation() override;
};

}  // namespace

void DeviceIndexSelector::runOnOperation() {
  func::FuncOp func = getOperation();
  // Convert all the DeviceIndex ops to constant values.
  func.getBody().walk([](TF::DeviceIndexOp op) {
    // This just selects the default in all cases where DeviceIndex feeds into

  if (resource_handle_op == parallel_execute) return nullptr;

  if (resource_handle_op &&
      resource_handle_op->getBlock() ==
          parallel_execute.getOperation()->getBlock() &&
      parallel_execute.getOperation()->isBeforeInBlock(resource_handle_op))
    return nullptr;

  return assign_var;
}

// Finds AssignVariableOps that can be moved into a parallel_execute region and

		// we are not looking at stale state.
		if a.GetOperation() == admission.Delete {
			l.forceLiveLookupCache.Add(a.GetName(), true, forceLiveLookupTTL)
		}
		// allow all operations to namespaces
		return nil
	}

	// always allow deletion of other resources
	if a.GetOperation() == admission.Delete {
		return nil
	}

    return "generate a temporary file and invoke InitTextFileToImportPass";
  }

 private:
  void runOnOperation() override;
};

void InitTextFileToImportTestPass::runOnOperation() {
  ModuleOp module = getOperation();

  // Create a temporary vocab file.
  int fd;
  SmallString<256> filename;
  std::error_code error_code =
      llvm::sys::fs::createTemporaryFile("text", "vocab", fd, filename);

  std::vector<OpOperand*> uses;
  for (auto& use : tensor_list.getUses()) {
    uses.emplace_back(&use);
  }
  OpBuilder builder(tensor_list_op.getOperation());
  for (OpOperand* operand : uses) {
    auto new_op = builder.clone(*tensor_list_op.getOperation());
    operand->set(new_op->getResult(0));
  }
}

// This transformation pass replicates TensorList initialization ops.
class ReplicateTensorListInitOps