org.slf4j.Logger slf4jLogger = org.slf4j.LoggerFactory.getLogger('some-logger')
slf4jLogger.info('An info log message logged using SLF4j')
// END SNIPPET use-slf4j

org.apache.commons.logging.Log jclLogger = org.apache.commons.logging.LogFactory.getLog('some-logger')
jclLogger.info('An info log message logged using JCL')

org.apache.log4j.Logger log4jLogger = org.apache.log4j.Logger.getLogger('some-logger')
log4jLogger.info('An info log message logged using Log4j')

    auto decomposition = mlir::cast<FlatSymbolRefAttr>(calledComputations[0]);

    auto composite = rewriter.create<mlir::stablehlo::CompositeOp>(
        op.getLoc(), op.getResultTypes(), op.getOperands(), name.str(), attrs,
        decomposition.getValue());
    rewriter.replaceOp(op, composite.getResults());
    return success();
  }
};

    if (!input_op) {
      return failure();
    }

    Builder builder(op.getContext());
    auto new_gather_op = rewriter.create<TFL::GatherOp>(
        op.getLoc(),
        /*result=*/
        mlir::cast<TensorType>(op.getResult().getType())
            .clone(builder.getI4Type()),
        /*operand=*/op.getOperands(), op->getAttrs());

    }

    @Test
    void testGetLogger() {
        ToolchainModel model = new ToolchainModel();
        DefaultToolchain toolchain = newDefaultToolchain(model);
        assertEquals(logger, toolchain.getLog());
    }

    @Test
    void testMissingRequirementProperty() {
        ToolchainModel model = new ToolchainModel();
        model.setType("TYPE");
        DefaultToolchain toolchain = newDefaultToolchain(model);

    return failure();
  }

  results.clear();
  builder.setInsertionPointAfter(op);
  for (const auto& result_value : result_values) {
    results.push_back(builder.create<TF::ConstOp>(op->getLoc(), result_value));
  }
  return success();
}

bool IsOperationFoldable(Operation* op) {
  if (isa<TF::ConstOp>(op)) return true;

  if (op->getDialect()->getNamespace() != "tf" || !TF::CanBeFolded(op)) {

System.err.println 'this is stderr'

def slf4jLogger = org.slf4j.LoggerFactory.getLogger('some-logger')
slf4jLogger.warn('A warning using SLF4j')

def jclLogger = org.apache.commons.logging.LogFactory.getLog('some-logger')
jclLogger.warn('A warning using JCL')

def log4jLogger = org.apache.log4j.Logger.getLogger('some-logger')
log4jLogger.warn('A warning using Log4j')

  std::string device = "/job:localhost/replica:0/task:0/device:CPU:0";
  module->walk(
      [&](mlir::tf_device::ClusterOp descendant) { cluster = descendant; });
  mlir::OpBuilder builder(&context);
  auto loc = cluster->getLoc();

  // Wrap the cluster op into a Launch op
  auto launch_op = tensorflow::WrapOpInLaunch(&builder, loc, cluster, device);

  EXPECT_TRUE(llvm::isa<mlir::tf_device::LaunchOp>(launch_op));
  launch_op->erase();

    // This occurs when doing qi16 convolution, as bias is passed as a
    // non-quantized int64
    if (allTypesFp || allTypesQuantizedOrInt) return failure();

    Location loc = op->getLoc();
    SmallVector<Value> newOperands;
    newOperands.reserve(op->getNumOperands());
    for (auto operand : op->getOperands()) {
      if (QuantizedType::getQuantizedElementType(operand.getType())) {

         static_cast<float>(max.getValueAsDouble())});
    ElementsAttr axis_stats;
    IntegerAttr axis;

    quantfork::StatisticsOp stats_op = rewriter.create<quantfork::StatisticsOp>(
        op->getLoc(), op.getInput(), layer_stats, axis_stats, axis);
    op.getOutput().replaceAllUsesWith(stats_op.getResult());
    return success();
  }
};

static PassRegistration<ConvertCustomAggregationOpToQuantStatsPass> pass;

  const auto composite_resource_users =
      GetResourceOpsUsingCompositeArgsInReplicate(replicate_op);
  for (auto resource_user : composite_resource_users) {
    WrapOpInLaunch(builder, resource_user->getLoc(), resource_user,
                   tensorflow::GetDeviceAliasForLogicalCore(0));
  }
}

void TPUColocateCompositeResourceOps::runOnOperation() {