FilterOutBlockArgControlDep(op->getOperands().drop_front(), new_operands);

    auto source_op = builder.create<tf_executor::NextIterationSourceOp>(
        op->getLoc(), op->getOperand(0).getType());
    builder.create<tf_executor::NextIterationSinkOp>(
        op->getLoc(), source_op.getToken(), /*input=*/op->getOperand(0),
        /*controlInputs=*/new_operands);
    op->replaceAllUsesWith(

 */
package org.codelibs.fess.crawler.entity;

import java.io.Serializable;

/**
 * @author shinsuke
 *
 */
public interface Sitemap extends Serializable {

    String getLoc();

    String getLastmod();

std::pair<std::string, std::string> GetFuncNameAndNodeName(
    TF::PartitionedCallOp call_op, const FlatSymbolRefAttr &f_attr) {
  std::optional<QuantizationUnitLoc::QuantizationUnit> quant_unit =
      FindQuantizationUnitFromLoc(call_op->getLoc());
  return std::make_pair(quant_unit->func_name(), quant_unit->node_name());
}

std::pair<std::string, std::string> GetFuncNameAndNodeName(
    TF::XlaCallModuleOp call_op, const FlatSymbolRefAttr &f_attr) {

    return failure();
  }
  auto op = builder.create<CustomOp>(
      func_.getLoc(), func_.getFunctionType().getResults(),
      func_.getArguments(), kMaxUnpooling,
      CustomOption(&builder, custom_option_buffer));
  builder.create<func::ReturnOp>(func_.getLoc(), op.getResults());

  return success();
}

LogicalResult ConvertMaxUnpoolingFunc::VerifySignature() {

  OpBuilder builder(&module->getBodyRegion());
  context.loadDialect<TF::TensorFlowDialect>();

  Value value = CreateConstValue<int8_t>(builder, module->getLoc(),
                                         unpacked_shape, unpacked_values);
  Value packed_value = PackOperand(builder, module->getLoc(), value, pack_dim);
  DenseIntElementsAttr packed_value_attr;
  ASSERT_TRUE(matchPattern(packed_value, m_Constant(&packed_value_attr)));

        maxs.push_back(rmax);
      }
      quant_type = quantfork::fakeQuantAttrsToType(
          op.getLoc(), num_bits, *op.getAxis(), mins, maxs, narrow_range,
          expressed, is_signed);
      if (legacy_float_scale) {
        quant_type = DownCastScale(quant_type, mins, maxs, op->getLoc());
      }
    } else if (auto stats =
                   op.getLayerStats().dyn_cast<DenseFPElementsAttr>()) {

            mlir::quant::QuantizedType::castToExpressedType(input_type);
        builder->setInsertionPoint(op);
        auto dequantize_op = builder->create<TFL::DequantizeOp>(
            op->getLoc(), dequantized_input_type, input.get());
        dequantized_inputs.push_back(dequantize_op);
      } else {
        dequantized_inputs.push_back(input.get());
      }
    }

    // Result types.

        }
        return deploymentDescriptor;
    }

    /**
     * A location for dependency libraries to include in the 'lib' directory of the EAR archive.
     */
    @Internal
    public CopySpec getLib() {
        return ((CopySpecInternal) lib).addChild();
    }

    /**
     * Adds dependency libraries to include in the 'lib' directory of the EAR archive.
     *

      rewriter.setInsertionPointAfter(op);
      // create new F16 constant op in that location
      ConstantOp new_const = rewriter.create<ConstantOp>(
          op->getLoc(), new_result_type, new_value_attr);
      ConvertOp dcast =
          rewriter.create<ConvertOp>(op->getLoc(), old_result_type, new_const);
      // replace all convert ops with dq op.
      convert_op->replaceAllUsesWith(dcast);

      auto dynamic_key =
          rewriter.create<TF::_XlaCompileMlirPlaceholderProgramKeyOp>(
              func.getLoc(), /*program=*/result_type, llvm::ArrayRef<Value>{});

      auto recv_at_host = rewriter.create<TF::_XlaRecvAtHostOp>(
          func.getLoc(), op.getOperandTypes(), /*dynamic_key=*/dynamic_key,
          op.getSendKeyAttr(),
          /*device_ordinal=*/rewriter.getI64IntegerAttr(0),