}

    public void test_toString() {
        String tag = "tag", id = "id", css = "css", attrName = "attrName", attrValue = "attrValue";
        PrunedTag prunedtag = new PrunedTag(tag);
        prunedtag.setAttr(attrName, attrValue);
        prunedtag.setId(id);
        prunedtag.setCss(css);
        assertEquals("PrunedTag [tag=" + tag + ", id=" + id + ", css=" + css + ", attrName=" + attrName + ", attrValue=" + attrValue + "]",

    if operation_id in operation_ids:
        message = (
            f"Duplicate Operation ID {operation_id} for function "
            + f"{route.endpoint.__name__}"
        )
        file_name = getattr(route.endpoint, "__globals__", {}).get("__file__")
        if file_name:
            message += f" at {file_name}"
        warnings.warn(message, stacklevel=1)
    operation_ids.add(operation_id)

      op_to_update->setAttr(kDeviceAttr, new_device_attr);
      PopulateDeviceForOpResults(*op_to_update, new_device_attr.getValue(),
                                 value_to_device);

      if (auto sink =
              llvm::dyn_cast<tf_executor::NextIterationSinkOp>(op_to_update)) {
        auto source = sink.GetSource();
        source->setAttr(kDeviceAttr, new_device_attr);

    }
  }

  if (!in_order) {
    // Functions do not get reused in practice, so skip the check for if the
    // callee has been updated.
    StringAttr callee_sym = cluster_func_op.getFuncAttr().getAttr();
    MoveResourceArgsToEnd(symtab.lookup<func::FuncOp>(callee_sym));
  }
  builder.setInsertionPoint(cluster_func_op);
  auto xla_launch_op = builder.create<TF::XlaLaunchOp>(

  EXPECT_TRUE(isa<TF::XlaCallModuleOp>(lifted_op));
  EXPECT_EQ(
      mlir::cast<StringAttr>(lifted_op->getAttr("_original_entry_function")),
      "composite_dot_general_fn_1");
  EXPECT_EQ(
      mlir::cast<ArrayAttr>(lifted_dot_general_op->getAttr("precision_config")),
      builder_.getArrayAttr(SmallVector<Attribute>(
          1, mlir::stablehlo::PrecisionAttr::get(

    input_matchers_ = std::move(inputs);
  }

  void set_control_deps(NodeSeqMatcher control_deps) {
    DCHECK(IsEmpty());
    control_deps_ = std::move(control_deps);
  }

  void set_attr(AttrKeyValuePair attr) {
    DCHECK(IsEmpty());
    attr_ = std::move(attr);
  }

  bool IsEmpty() const {
    return !name().has_value() && !op().has_value() && !inputs().has_value() &&

  static bool AllowDynamicRangeQuantizedOperand(
      Operation* quantized_op, const CustomMap& custom_op_map) {
    auto call_op = cast<TF::PartitionedCallOp>(quantized_op);
    StringRef function_name =
        call_op.getFAttr().cast<FlatSymbolRefAttr>().getValue();
    // The below can be generalized as there are more read-only ops added such
    // as slice.
    const bool is_gather = function_name.contains("gather");

      devices.push_back(builder.getNamedAttr(name, metadata));
    }
  }

  op->setAttr(kDevicesAttr, builder.getDictionaryAttr(devices));
}

mlir::LogicalResult GetDevicesFromOp(mlir::Operation* op,
                                     mlir::TF::RuntimeDevices* devices) {
  auto devices_attr = op->getAttr(kDevicesAttr);
  if (!devices_attr) return mlir::success();

}

// Returns the function attribute for the given call op which is lifted for
// quantization.
inline FlatSymbolRefAttr GetFuncAttr(TF::PartitionedCallOp call_op) {
  return mlir::dyn_cast<FlatSymbolRefAttr>(call_op.getFAttr());
}

inline FlatSymbolRefAttr GetFuncAttr(TF::XlaCallModuleOp call_op) {
  return call_op->getAttrOfType<FlatSymbolRefAttr>(
      TF::kStablehloEntryFunctionAttrName);
}

              getElementTypeOrSelf(operand.getType()))) {
        legalize_to_tfl = false;
        return WalkResult::interrupt();
      }
    }
    return WalkResult::advance();
  });
  module->setAttr(kLegalizeTflVariables,
                  BoolAttr::get(context, legalize_to_tfl));
}

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>> CreateAnalyzeVariablesPass() {