return IntegerAttr::get(IntegerType::get(context, 64), v);
  });
  // TODO(b/157276506): change type of strides to DenseElementsAttr
  auto strides = ArrayAttr::get(context, llvm::to_vector<4>(attrs));
  conv2d->setAttr("strides", strides);
}

// Transforms input shape for the first convolution.
void HandleConv2DInput(TF::Conv2DOp conv2d, int64_t block_size) {
  auto input = conv2d.getInput();

    }
    // Recreate the attributes dictionary to only contain "value".
    NamedAttrList attributes;
    attributes.append(NamedAttribute(value_str_attr, cst->getAttr("value")));
    cst->setAttrs(attributes.getDictionary(&getContext()));
  });

  auto& side_effect_analysis = getAnalysis<mlir::TF::SideEffectAnalysis>();
  for (auto func : getOperation().getOps<mlir::func::FuncOp>())

                                    xla_call_module_op.getArgs());

  // Transfer the `kQuantizationMethodAttr` attribute to the `CallOp`,
  // indicating what `Method` has been applied to the quantized unit.
  call_op->setAttr(
      kQuantizationMethodAttr,
      xla_call_module_op->getAttrOfType<StringAttr>(kQuantizationMethodAttr));

  rewriter.replaceOp(xla_call_module_op, call_op);
}

  // quantization pass. These ops can be removed without losing original
  // program accuracy.
  // TODO: b/323478683 - Make the attribute being part of op definition.
  quantize->setAttr(kVolatileOpAttrName, builder_.getUnitAttr());

  // `original_result` has a use to `quantize`, so this will replace that use
  // by the result of `dequantize`. Remember to reset that use afterwards

    }
    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()));
    for (const auto& entry : info.buffer_ret_to_size_ret) {

    }
    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()));
    for (const auto& entry : info.ret_forward_input) {

  Value reduced = builder.create<TF::EinsumOp>(
      loc, RankedTensorType::get(output_shape, builder.getIntegerType(32)),
      input_arguments, builder.getStringAttr(einsum_equation));

  reduced.getDefiningOp()->setAttr(
      kTfQuantCreatedEinsum,
      BoolAttr::get(reduced.getDefiningOp()->getContext(), true));
  auto mul_op = builder.create<TF::MulOp>(loc, zp, reduced);

  auto new_call = builder.create<CallOpType>(
      call_op.getLoc(),
      lifting_info.lifted_callee.getFunctionType().getResults(), new_operands,
      call_op->getAttrs());
  new_call->setAttr("f",
                    SymbolRefAttr::get(builder.getContext(),
                                       lifting_info.lifted_callee.getName()));
  AddLoadsStoresOutsideControlFlowOp(

        *sharding_proto.add_tuple_shardings() =
            ::xla::sharding_builder::AssignDevice(0);
        data_and_token->setAttr(
            kShardingAttr,
            rewriter.getStringAttr(sharding_proto.SerializeAsString()));
      } else {
        data_and_token->setAttr(kShardingAttr, op.get_XlaShardingAttr());
      }
    }

    if (op->hasAttr("layouts")) {

}

// KeyctlRestrictKeyring implements the KEYCTL_RESTRICT_KEYRING command. This
// command limits the set of keys that can be linked to the keyring, regardless
// of keyring permissions. The command requires the "setattr" permission.
//
// When called with an empty keyType the command locks the keyring, preventing
// any further keys from being linked to the keyring.
//