diff --git a/src_erl/NerlnetApp/src/Bridge/onnWorkers/workerGeneric.erl b/src_erl/NerlnetApp/src/Bridge/onnWorkers/workerGeneric.erl
index 5f69f6851..8aea95829 100644
--- a/src_erl/NerlnetApp/src/Bridge/onnWorkers/workerGeneric.erl
+++ b/src_erl/NerlnetApp/src/Bridge/onnWorkers/workerGeneric.erl
@@ -171,13 +171,11 @@ idle(cast, _Param, State = #workerGeneric_state{myName = _MyName}) ->
 %% Waiting for receiving results or loss function
 %% Got nan or inf from loss function - Error, loss function too big for double
 wait(cast, {loss, nan , TrainTime , BatchID , SourceName}, State = #workerGeneric_state{myName = MyName, distributedBehaviorFunc = DistributedBehaviorFunc}) ->
-  io:format("~p got loss tensor nan for batch ~p~n", [MyName, BatchID]),
   stats:increment_by_value(get(worker_stats_ets), nan_loss_count, 1),
   WorkerToken = ets:lookup_element(get(generic_worker_ets), distributed_system_token, ?ETS_KEYVAL_VAL_IDX),
   gen_statem:cast(get(client_pid),{loss, MyName , SourceName ,nan , TrainTime, WorkerToken ,BatchID}),
   NextStateBehavior = DistributedBehaviorFunc(post_train, {get(generic_worker_ets),[]}), %% First call sends empty list , then it will be updated by the federated server and clients
   EndStreamWaitingList = ets:lookup_element(get(generic_worker_ets), end_streams_waiting_list, ?ETS_KEYVAL_VAL_IDX),
-  io:format("EndStreamWaitingList: ~p~n",[EndStreamWaitingList]),
   case length(EndStreamWaitingList) of
     0 -> ok;
     _ -> 
@@ -193,13 +191,11 @@ wait(cast, {loss, nan , TrainTime , BatchID , SourceName}, State = #workerGeneri
 
 
 wait(cast, {loss, {LossTensor, LossTensorType} , TrainTime , BatchID , SourceName}, State = #workerGeneric_state{myName = MyName, modelID=_ModelID, distributedBehaviorFunc = DistributedBehaviorFunc}) ->
-  io:format("~p got loss tensor for batch ~p~n", [MyName, BatchID]),
   BatchTimeStamp = erlang:system_time(nanosecond),
   WorkerToken = ets:lookup_element(get(generic_worker_ets), distributed_system_token, ?ETS_KEYVAL_VAL_IDX),
   gen_statem:cast(get(client_pid),{loss, MyName, SourceName ,{LossTensor, LossTensorType} , TrainTime , WorkerToken, BatchID , BatchTimeStamp}),
   NextStateBehavior = DistributedBehaviorFunc(post_train, {get(generic_worker_ets),[]}), %% First call sends empty list , then it will be updated by the federated server and clients
   EndStreamWaitingList = ets:lookup_element(get(generic_worker_ets), end_streams_waiting_list, ?ETS_KEYVAL_VAL_IDX),
-  io:format("EndStreamWaitingList: ~p~n",[EndStreamWaitingList]),
   case length(EndStreamWaitingList) of
     0 -> ok;
     _ -> 
diff --git a/src_erl/NerlnetApp/src/Client/clientStatem.erl b/src_erl/NerlnetApp/src/Client/clientStatem.erl
index 3183a1c7a..c9c220fad 100644
--- a/src_erl/NerlnetApp/src/Client/clientStatem.erl
+++ b/src_erl/NerlnetApp/src/Client/clientStatem.erl
@@ -279,7 +279,6 @@ training(cast, In = {start_stream , Data}, State = #client_statem_state{etsRef =
 
 training(cast, In = {end_stream , Data}, State = #client_statem_state{etsRef = EtsRef}) ->
   {SourceName, _ClientName, WorkerName} = binary_to_term(Data),
-  % io:format("~p send end_stream to worker ~p~n",[SourceName, WorkerName]),
   ClientStatsEts = get(client_stats_ets),
   stats:increment_messages_received(ClientStatsEts),
   stats:increment_bytes_received(ClientStatsEts , nerl_tools:calculate_size(In)),
@@ -294,7 +293,6 @@ training(cast, In = {stream_ended , Pair}, State = #client_statem_state{etsRef =
   ListOfActiveWorkersSources = ets:lookup_element(EtsRef, active_workers_streams, ?DATA_IDX),
   UpdatedListOfActiveWorkersSources = ListOfActiveWorkersSources -- [Pair],
   ets:update_element(EtsRef, active_workers_streams, {?DATA_IDX, UpdatedListOfActiveWorkersSources}),
-  io:format("Updated List of Active Workers ~p~n",[UpdatedListOfActiveWorkersSources]),
   case length(UpdatedListOfActiveWorkersSources) of 
     0 ->  ets:update_element(EtsRef, all_workers_done, {?DATA_IDX, true});
     _ ->  ok
@@ -308,7 +306,6 @@ training(cast, In = {idle}, State = #client_statem_state{myName = MyName, etsRef
   stats:increment_bytes_received(ClientStatsEts , nerl_tools:calculate_size(In)),
   MessageToCast = {idle},
   WorkersDone = ets:lookup_element(EtsRef , all_workers_done , ?DATA_IDX),
-  % io:format("Client ~p Workers Done? ~p~n",[MyName, WorkersDone]),
   case WorkersDone of
     true ->   cast_message_to_workers(EtsRef, MessageToCast),
               Workers =  clientWorkersFunctions:get_workers_names(EtsRef),
@@ -408,7 +405,6 @@ predict(cast, In = {idle}, State = #client_statem_state{myName = MyName, etsRef
   stats:increment_bytes_received(ClientStatsEts , nerl_tools:calculate_size(In)),
   MessageToCast = {idle},
   WorkersDone = ets:lookup_element(EtsRef , all_workers_done , ?DATA_IDX),
-  % io:format("Client ~p Workers Done? ~p~n",[MyName, WorkersDone]),
   case WorkersDone of
     true ->   cast_message_to_workers(EtsRef, MessageToCast),
               Workers =  clientWorkersFunctions:get_workers_names(EtsRef),