return mlir::isa<QuantizedType>(element_type);
}

bool IsOpFullyQuantized(Operation* op) {
  return llvm::all_of(op->getOperandTypes(), IsQuantizedTensorType) &&
         llvm::all_of(op->getResultTypes(), IsQuantizedTensorType);
}

bool IsOpNotQuantized(Operation* op) {
  return !llvm::any_of(op->getOperandTypes(), IsQuantizedTensorType) &&
         !llvm::any_of(op->getResultTypes(), IsQuantizedTensorType);
}

        return;
      }
    }

    auto new_func_type = builder.getFunctionType(block.getArgumentTypes(),
                                                 terminator->getOperandTypes());
    func.setType(new_func_type);
  });
}

// Creates an instance of the pass to decompose the TF ops.
std::unique_ptr<OperationPass<ModuleOp>> CreateRewriteQuantizedIOPass() {

      if (!mlir::tf_type::HasCompatibleElementTypes(type, result_type))
        return op->emitOpError()
               << "requires all return types to have compatible element types";
    }
    for (auto operand_type : op->getOperandTypes()) {
      if (!mlir::tf_type::HasCompatibleElementTypes(
              operand_type, type, /*may_ignore_ref_type_lhs=*/true))
        return op->emitError() << "requires all operands and results to have "

void VerifyQuantLegalization::runOnOperation() {
  Operation* func_op = getOperation();

  auto walk_result = func_op->walk([&](Operation* op) {
    // Verify all uq and qint types are lowered.
    if (llvm::any_of(op->getOperandTypes(), IsQuantType) ||
        llvm::any_of(op->getResultTypes(), IsQuantType) ||
        IsTFUniformQuantizedOp(op) || IsMhloUniformQuantizedOp(*op)) {
      op->emitOpError("is illegal as it is a UQ op or contains uq/qint types");

    Block *new_block = new Block;
    region.push_back(new_block);

    builder.setInsertionPointToEnd(&region.front());
    Operation *inner_op = builder.clone(*op);

    new_block->addArguments(op->getOperandTypes(),
                            SmallVector<Location>(op->getNumOperands(), loc));
    for (const auto &idx_args : llvm::enumerate(new_block->getArguments())) {
      inner_op->setOperand(idx_args.index(), idx_args.value());

              tensor_type.getElementType().getIntOrFloatBitWidth();
    }
    return size;
  };

  int64_t results_size = get_size(inst->getResultTypes());
  int64_t operands_size = get_size(inst->getOperandTypes());

  constexpr int kSizeFactor = 2;
// TODO(b/233827625): Remove TF_DISABLE_CONSTANT_FOLDING macro.
#ifdef TF_DISABLE_CONSTANT_FOLDING
  constexpr int64_t kResultsSizeThreshold = 0;
#else

                              Location loc) {
  auto& cond_region = dataset_while.getCond();
  Block* cond_block = builder.createBlock(&cond_region);
  auto while_input_types = dataset_while.getOperandTypes();
  cond_block->addArguments(
      while_input_types, SmallVector<Location>(while_input_types.size(), loc));
  builder.create<YieldOp>(loc, cond_block->getArgument(0));
}

                     func_op.getArgumentTypes().end());
    auto& return_op = func_op.getBody().getBlocks().front().back();
    result_types.append(return_op.getOperandTypes().begin(),
                        return_op.getOperandTypes().end());
    for (const auto& arg : func_op.getArguments()) {
      arg_locs.push_back(arg.getLoc());
    }
  }

  // Creates a new main function.

          /// propagated to the callee.
          return isa<CallOpInterface>(caller) &&
                 std::equal(caller->getOperandTypes().begin(),
                            caller->getOperandTypes().end(),
                            callers.front()->getOperandTypes().begin());
        })) {
      if (llvm::any_of(callers, [](Operation* op) {
            return isa<IfOp, WhileOp, CaseOp>(op);
          }))

    return emitOpError(
        "has unmatched operands/results number and spec attributes number");

  // Verify that quantization specifications are valid.
  for (auto input : llvm::zip(getOperandTypes(), getInputSpecs())) {
    Type inputType = std::get<0>(input);
    Attribute inputSpec = std::get<1>(input);
    if (!isValidQuantizationSpec(inputSpec, inputType)) {