if (resource_type.getSubtypes().size() == 1)
    return resource_type.getSubtypes().front();

  return UnrankedTensorType::get(element_type);
}

static bool HasResourceSubtype(Value resource) {
  return resource.getType()
             .cast<TensorType>()
             .getElementType()
             .cast<ResourceType>()
             .getSubtypes()
             .size() == 1;
}

    if (!tensor) return nullptr;
    TF::ResourceType resource =
        llvm::dyn_cast<TF::ResourceType>(tensor.getElementType());
    if (!resource || resource.getSubtypes().size() != 1) return nullptr;
    return resource.getSubtypes().front();
  } else if (auto global_tensor_op =
                 dyn_cast<tf_saved_model::GlobalTensorOp>(source)) {
    return global_tensor_op.getType();
  }

    type = op->getResult(0)
               .getType()
               .cast<ShapedType>()
               .getElementType()
               .cast<TF::TensorFlowTypeWithSubtype>()
               .GetSubtypes()
               .back();
  }
  return IsSupportedVariableType(type);
}

bool IsSupportedVariableType(ShapedType type) {
  auto element_type = type.getElementType();
  // Check complex types.

                                    .cast<TF::ResourceType>()
                                    .getSubtypes()))
      return false;

  return true;
}

Type GetResourceSubtype(Type type) {
  return type.cast<TensorType>()
      .getElementType()
      .cast<TF::ResourceType>()
      .getSubtypes()
      .front();
}

Type GetResourceSubtype(Value resource) {

  }

  auto element_type = getElementTypeOrSelf(first_operand_type);
  if (mlir::isa<TF::ResourceType>(element_type)) {
    first_operand_type =
        mlir::cast<TF::ResourceType>(element_type).getSubtypes().front();
  }

  auto tensor_type = mlir::dyn_cast_or_null<TensorType>(first_operand_type);
  if (!(tensor_type && tensor_type.hasRank())) {
    return op->emitError()

    return type;
  }
  if (!variant_ty.getSubtypes().empty()) {
    // Short-circut if the variant type has subtype info.
    return UnrankedTensorType::get(
        variant_ty.getSubtypes()[0].getElementType());
  }
  Type value_type = value.getType();
  Type element_type;
  variant_ty = value_type.dyn_cast<TF::VariantType>();
  if (variant_ty && !variant_ty.getSubtypes().empty()) {

mlir::LogicalResult ValidateResourceArgument(func::FuncOp function,
                                             BlockArgument resource_arg,
                                             TF::ResourceType resource_type) {
  if (resource_type.getSubtypes().size() != 1)
    return function.emitError()
           << "expects resource type of argument "
           << resource_arg.getArgNumber() << " to have one subtype, got "
           << resource_type;

          "result isn't");
    } else if (lhs_element_type_with_subtype.GetSubtypes().size() > 1) {
      DCOMMENT(
          "Unexpected `TensorFlowTypeWithSubtype` original type with size>1");
    } else if (lhs_element_type_with_subtype.GetSubtypes().empty()) {
      subtype = rhs_element_type_with_subtype.GetSubtypes().front();
    } else {

      auto arg_type = mlir::cast<RankedTensorType>(arg.getType());
      assert(arg_type.getRank() == 0);
      llvm::ArrayRef<TensorType> underlying_type =
          mlir::cast<TF::ResourceType>(arg_type.getElementType()).getSubtypes();

      // If the arg type already matches the global_tensor type, we don't need
      // to do anything.
      if (!underlying_type.empty() &&
          underlying_type[0] == global_tensor.getType()) {

    Type elementType = getElementTypeOrSelf(op->getResult(0));
    Type newType = nullptr;
    if (auto variant = dyn_cast<TF::VariantType>(elementType)) {
      ArrayRef<TensorType> sub = variant.getSubtypes();
      if (sub.size() == 1) {
        auto inner = sub[0];
        if (!isa<TF::VariantType>(inner)) {
          newType = inner;
        }
      }
    }
    if (!newType) {
      return failure();