conv_op.getLhsDilationAttr(), conv_op.getRhsDilationAttr(),
        conv_op.getWindowReversalAttr(), conv_op.getDimensionNumbers(),
        conv_op.getFeatureGroupCount(), conv_op.getBatchGroupCount(),
        conv_op.getPrecisionConfigAttr());
    // For static case, replace the convolution op now.
    if (!is_dynamic_broadcast) {
      rewriter.replaceOp(mul_op, {new_conv});
    } else {

  auto padding = op.getPadding();
  auto lhs_dilation = op.getLhsDilation();
  auto rhs_dilation = op.getRhsDilation();
  auto feature_group_count = op.getFeatureGroupCount();
  int64_t batch_group_count = op.getBatchGroupCount();

  auto input_args_have_static_shape = [&]() -> bool {
    return mlir::cast<TensorType>(input_tensor.getType()).hasStaticShape() &&
           mlir::cast<TensorType>(kernel_tensor.getType()).hasStaticShape() &&

        transposed_kernel_2d_op.getResult(), window_strides_2d, padding_2d,
        lhs_dilation_2d, rhs_dilation_2d, window_reversal_2d, dnums_2d,
        conv_op.getFeatureGroupCount(), conv_op.getBatchGroupCount(),
        conv_op.getPrecisionConfigAttr());

    OpResult conv2d_output = conv2d_op->getResult(0);
    auto conv2d_output_type = mlir::cast<ShapedType>(conv2d_output.getType());

    //

                vhlo_op.getFeatureGroupCount())
                .getValue()
                .getSExtValue(),
            mlir::cast<mlir::vhlo::IntegerV1Attr>(vhlo_op.getBatchGroupCount())
                .getValue()
                .getSExtValue(),
            precision_config);

        return tflite::CreateOperator(
            builder_, opcode_index, builder_.CreateVector(operands),