UncompilableNodesMap* uncompilable_nodes) const;

  // Returns compilability of node def retrieved from `node`'s attribute with
  // name `attr_name`.
  bool ExtractNodeDefAndCheckCompilability(
      const Node& node, const std::string& attr_name,
      const std::string& call_name, NameAttrList* encapsulating_function,
      FunctionLibraryRuntime* lib_runtime,
      std::vector<StackFrameView>* stack_trace,

      }
    }

    auto check_i64_attr =
        [&](const std::string& attr_name) -> mlir::LogicalResult {
      if (!backend_config.contains(attr_name)) {
        return op.emitOpError()
               << "Missing " << attr_name << " attribute in backend_config";
      }
      auto attr = backend_config.getAs<IntegerAttr>(attr_name);
      if (!attr || !attr.getType().isInteger(64)) {
        return op.emitOpError()

      auto sizes = mlir::DenseI32ArrayAttr::get(context, {1, 1, 1, 0});
      auto attr_name =
          StringAttr::get(context, mlir::OpTrait::AttrSizedOperandSegments<
                                       void>::getOperandSegmentSizeAttr());
      attrs.push_back(NamedAttribute(attr_name, sizes));
    }

    // Insert fused operation right before the BiasAdd operation to guarantee

TF_CAPI_EXPORT extern void TF_AttrBuilderSetType(TF_AttrBuilder* builder,
                                                 const char* attr_name,
                                                 TF_DataType value);
TF_CAPI_EXPORT extern void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder,
                                                     const char* attr_name,
                                                     const TF_DataType* values,

    } else if (n->IsIfNode()) {
      for (const string& attr_name :
           std::vector<string>{"then_branch", "else_branch"}) {
        NameAttrList branch_func;
        TF_RETURN_IF_ERROR(GetNodeAttr(n->attrs(), attr_name, &branch_func));
        (*branch_func.mutable_attr())["_device_ordinal"] = device_ordinal_value;
        n->ClearAttr(attr_name);
        n->AddAttr(attr_name, branch_func);
      }
    } else if (n->IsWhileNode()) {

      continue;
    }
    const string attr_name =
        api_def_attr.has_default_value()
            ? strings::StrCat("attrs.", api_def_attr.rename_to(), "_")
            : AvoidCPPKeywords(api_def_attr.rename_to());
    strings::StrAppend(&body, spaces, ".Attr(\"", graph_attr.name(), "\", ",
                       attr_name, ")\n");
  }
  strings::StrAppend(&body, "  ;\n");

        all_attrs.insert(attr.getName().strref());
      }
      for (const auto& operand : llvm::enumerate(getArgumentTypes())) {
        if (auto attr_name = getArgAttrOfType<StringAttr>(
            operand.index(), kAttrArgumentNameAttr)) {
          all_attrs.insert(attr_name.getValue());
        }
      }
      return all_attrs;
    }
  }];

  let hasVerifier = 1;
  let hasCustomAssemblyFormat = 1;
}

  TF_DeleteBuffer(buffer);
  TF_DeleteStatus(s);
  return ret;
}

bool GetAttrValue(TF_Operation* oper, const char* attr_name,
                  tensorflow::AttrValue* attr_value, TF_Status* s) {
  TF_Buffer* buffer = TF_NewBuffer();
  TF_OperationGetAttrValueProto(oper, attr_name, buffer, s);
  bool ret = TF_GetCode(s) == TF_OK;
  if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);

                             llvm::StringRef attr_name) {
  return attr_name.compare(kOutputShapesAttrName) == 0 &&
         attr_value.value_case() == AttrValue::kList;
}

bool IsResourceOutputShapesAttribute(const AttrValue& attr_value,
                                     llvm::StringRef attr_name) {
  if (attr_name == "_handle_dtypes" || attr_name == "_handle_shapes")

                                                const char* attr_name,
                                                int64_t* dims, size_t num_dims,
                                                TF_Status* status) {
  ::tensorflow::TensorShape shape;
  auto* cc_ctx = reinterpret_cast<::tensorflow::OpKernelConstruction*>(ctx);
  ::tensorflow::Status s = cc_ctx->GetAttr(attr_name, &shape);
  ::tensorflow::Set_TF_Status_from_Status(status, s);