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

import java.io.Serializable;

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

    String getLoc();

    String getLastmod();

    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)));

      ShapedType shaped_type =
          RankedTensorType::get({1}, TF::StringType::get(builder.getContext()));
      auto const_op = builder.create<TF::ConstOp>(
          asset.getLoc(),
          DenseStringElementsAttr::get(shaped_type, {filename}));
      for (auto init_op : init_table_from_text_file_ops_to_erase) {
        // Replace the InitializeTableFromTextFileV2Op to use the saved model's

            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.

        mlir::isa<quant::QuantizedType>(element_type)) {
      return;
    }
    op_builder->setInsertionPoint(const_op);
    Value scalar = op_builder->create<mhlo::ConstantOp>(
        const_op->getLoc(),
        DenseElementsAttr::get(
            RankedTensorType::get(/*shape=*/{}, element_type),
            splat_elements_attr.getSplatValue<Attribute>()));
    auto broadcast_dims = DenseIntElementsAttr::get(

    BlockArgument param = callee.getArgument(i);
    if (mlir::isa<TF::ResourceType>(getElementTypeOrSelf(param.getType()))) {
      removed_params.set(i);
      callee.getBody().addArgument(param.getType(), param.getLoc());
      param.replaceAllUsesWith(callee.getArguments().back());
      removed_params.push_back(false);
    }
  }
  // Remove old resource-type parameters.
  callee.getBody().front().eraseArguments(removed_params);

    auto name_from_loc = mlir::GetNameFromLoc(op->getLoc());
    if (!name_from_loc.empty()) return name_from_loc;
    // If the location is none of the expected types, then simply use name
    // generated using the op type.
    return std::string(op->getName().getStringRef());
  }
  auto val = op_or_val.dyn_cast<mlir::Value>();
  auto name_from_loc = mlir::GetNameFromLoc(val.getLoc());
  if (!name_from_loc.empty()) return name_from_loc;

}

static Value CreateTranspose(OpBuilder& builder, Value source,
                             ArrayRef<int64_t> perm) {
  return builder.create<stablehlo::TransposeOp>(source.getLoc(), source, perm)
      ->getResult(0);
}

// Transform pad(transpose(x)) to transpose(pad(x))
struct TransposeCommuteWithPad : public OpRewritePattern<stablehlo::PadOp> {

  // Create new TFL While op that will be used to replace TF While op.
  auto new_op = OpBuilder(op).create<TFL::WhileOp>(
      op->getLoc(), op->getResultTypes(), op->getOperands(),
      while_op.getIsStateless());
  Location loc = while_op->getLoc();
  CreateRegionWithCall(while_op.cond_function(), new_op.getCond(), loc);
  CreateRegionWithCall(while_op.body_function(), new_op.getBody(), loc);