}
    OpBuilder builder(call);
    auto new_call = builder.create<CallOp>(
        call.getLoc(), info.decomposed_callee.getFunctionType().getResults(),
        new_operands, call->getAttrs());
    new_call->setAttr(
        "f", SymbolRefAttr::get(
                 builder.getContext(),
                 const_cast<func::FuncOp&>(info.decomposed_callee).getName()));

  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(

      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();

    if (auto device = res->getAttrOfType<StringAttr>("device")) {
      if (!device.getValue().empty())
        result_id->setAttr("device", device);
      else
        result_id->setAttr("device", compile_device_op);
    } else if (compile_device_op) {
      result_id->setAttr("device", compile_device_op);
    }
    res.getOutput().replaceAllUsesWith(compile_op->getResult(0));
  }

  // tf.MyCustomOp is the result of conversion to a Custom op
  %2 = "tf.MyCustomOp"(%1, %0) {fused_activation_function = "RELU", int_attr = 2 : i32}  : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("MyCustomOp")
  %3 = "tfl.exp"(%2)  : (tensor<4xf32>) -> tensor<4xf32> loc("exp")
  func.return %3 : tensor<4xf32>

    // TODO(fengliuai): copy the regions.
    OperationState state(op->getLoc(), op->getName().getStringRef(),
                         parent_op->getOperands(), parent_op->getResultTypes(),
                         op->getAttrs(), op->getSuccessors());
    Operation* inlined = builder.create(state);

    parent_op->replaceAllUsesWith(inlined);
    parent_op->erase();
  }
  return success();
}

		TableConvertor: printerstorage.TableConvertor{TableGenerator: printers.NewTableGenerator().With(printersinternal.AddHandlers)},
	}
	options := &generic.StoreOptions{RESTOptions: optsGetter, AttrFunc: resourceclaim.GetAttrs}
	if err := store.CompleteWithOptions(options); err != nil {
		return nil, nil, err
	}

	statusStore := *store
	statusStore.UpdateStrategy = resourceclaim.StatusStrategy

        rewriter.getDenseI64ArrayAttr(kOihwToHwioPermutation));

    // [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f]
    const auto new_dimension_nums = rewriter.getAttr<ConvDimensionNumbersAttr>(
        /*inputBatchDimension=*/0, /*inputFeatureDimension=*/3,
        /*inputSpatialDimensions=*/SmallVector<int64_t>{1, 2},
        /*kernelInputFeatureDimension=*/2, /*kernelOutputFeatureDimension=*/3,

    cc_type v;                                                           \
    auto* cc_ctx = reinterpret_cast<InferenceContext*>(ctx);             \
    Status s = cc_ctx->GetAttr(attr_name, &v);                           \
    Set_TF_Status_from_Status(status, s);                                \
    if (s.ok()) {                                                        \

  for (const auto& attr_def : op_reg_data->op_def.attr()) {
    registered_attrs.insert(attr_def.name());
  }
  // Attributes are not in the registered attributes set will be ignored.
  for (auto& attr : inst->getAttrs()) {
    if (registered_attrs.find(attr.getName()) == registered_attrs.end()) {
      attrs_to_ignore->insert(
          absl::string_view(attr.getName().data(), attr.getName().size()));
    }
  }