[SETUP-BUG]

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System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):

• Edition Windows 11 Enterprise Version 21H2 Installed on ‎6/‎5/‎2021 OS build 22000.613 Experience Windows Feature Experience Pack 1000.22000.613.0

• MLflow installed from (source or binary): binary

• MLflow version (run mlflow --version): 1.25.1

• Python version: 3.10.4

• Exact command to reproduce: with(mlflow_start_run(), { mlflow_set_tag(“mlflow.runName”, “randomForest”) fit <- train(as.factor(Y_AcceptedOffer) ~ ., data=treatedTrain, method=“rf”, metric=metric, trControl=control)

  jpeg(filename=“1.jpeg”) print(plot(fit)) dev.off()

  Save the plot and log it as an artifact

  mlflow_log_artifact(“1.jpeg”) accu_train <- get_accuracy(fit, treatedTrain) accu_test <- get_accuracy(fit, treatedTest)

  message(" accu_train: “, accu_train) message(” accu_test: “, accu_test) message(” splitPercent: “, splitPercent) message(” seed: “, seed) message(” device: ", getOption(“device”)) mlflow_log_metric(“accu_train”, accu_train) mlflow_log_metric(“accu_test”, accu_test) mlflow_log_param(“splitPercent”, splitPercent) mlflow_log_param(“seed”, seed) mlflow_log_param(“method”, “adaptive_cv”) mlflow_log_param(“number”, “9”)

})

Describe the problem

Provide the exact sequence of commands / steps that you executed before running into the problem.

library(mlflow) #getting this point is done in another script treatedTrain <- training treatedTest <- testing

control <- trainControl(method=“adaptive_cv”, number=9, verboseIter = TRUE,allowParallel = TRUE) metric <- “Accuracy”

Sys.setenv(MLFLOW_PYTHON_BIN = “C://python”) Sys.setenv(MLFLOW_BIN=“C://python//Scripts//mlflow”)

with(mlflow_start_run(), { mlflow_set_tag(“mlflow.runName”, “randomForest”) fit <- train(as.factor(Y_AcceptedOffer) ~ ., data=treatedTrain, method=“rf”, metric=metric, trControl=control)

jpeg(filename=“1.jpeg”) print(plot(fit)) dev.off()

Save the plot and log it as an artifact

mlflow_log_artifact(“1.jpeg”) accu_train <- get_accuracy(fit, treatedTrain) accu_test <- get_accuracy(fit, treatedTest)

message(" accu_train: “, accu_train) message(” accu_test: “, accu_test) message(” splitPercent: “, splitPercent) message(” seed: “, seed) message(” device: ", getOption(“device”)) mlflow_log_metric(“accu_train”, accu_train) mlflow_log_metric(“accu_test”, accu_test) mlflow_log_param(“splitPercent”, splitPercent) mlflow_log_param(“seed”, seed) mlflow_log_param(“method”, “adaptive_cv”) mlflow_log_param(“number”, “9”)

})

Other info / logs

Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached. Error message:

Error in wait_for(function() mlflow_rest(“experiments”, “list”, client = client), : Operation failed after waiting for 10 seconds

[dbczumar]

@mkspwr What is the error that you’re facing? cc @WeichenXu123

[WeichenXu123]

A fixing PR for mlflow-R was merged: https://github.com/mlflow/mlflow/pull/5767 Could you build latest mlflow-R from master and retry ? 😃