[BUG] MLflow R SDK mlflow_create_model_version params not passed correctly to rest client

[singankit]

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Willingness to contribute

The MLflow Community encourages bug fix contributions. Would you or another member of your organization be willing to contribute a fix for this bug to the MLflow code base?

• Yes. I can contribute a fix for this bug independently.
• Yes. I would be willing to contribute a fix for this bug with guidance from the MLflow community.
• No. I cannot contribute a bug fix at this time.

System information

• Have I written custom code (as opposed to using a stock example script provided in MLflow): No
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): All Platforms
• MLflow installed from (source or binary): MLflow R SDK from https://cloud.r-project.org/
• MLflow version (run mlflow --version): 1.20.2
• Python version: NA
• npm version, if running the dev UI: NA
• Exact command to reproduce: mlflow_create_model_version(name="test_model", source=run$artifact_uri, "/model")

Describe the problem

In MLflow R SDK mlflow_create_model_version fails with error test_model artifact path does not exists. This issue is that the parameter source in mlflow_create_model_version is not passed properly to mlflow_rest

Code to reproduce issue

Following code taken from an Mlflow R sample example

library(mlflow)
library(glmnet)

system("which mlflow")

# Read the wine-quality csv file
data <- read.csv("wine-quality.csv")

# Split the data into training and test sets. (0.75, 0.25) split.
sampled <- sample(1:nrow(data), 0.75 * nrow(data))
train <- data[sampled, ]
test <- data[-sampled, ]

# The predicted column is "quality" which is a scalar from [3, 9]
train_x <- as.matrix(train[, !(names(train) == "quality")])
test_x <- as.matrix(test[, !(names(train) == "quality")])
train_y <- train[, "quality"]
test_y <- test[, "quality"]

alpha <- mlflow_param("alpha", 0.5, "numeric")
lambda <- mlflow_param("lambda", 0.5, "numeric")

with(mlflow_start_run(), {
  model <- glmnet(train_x, train_y, alpha = alpha, lambda = lambda, family = "gaussian")
  predictor <- crate(~ glmnet::predict.glmnet(model, as.matrix(.x)), model)
  predicted <- predictor(test_x)
  mlflow_log_model(predictor, "model")
  mlflow_create_model_version(name="test_model", source= run$artifact_uri, "/model")
})

This example fails with error

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.

What component(s), interfaces, languages, and integrations does this bug affect?

Components

• area/artifacts: Artifact stores and artifact logging
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/projects: MLproject format, project running backends
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
• area/tracking: Tracking Service, tracking client APIs, autologging

Interface

• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• area/windows: Windows support

Language

• language/r: R APIs and clients
• language/java: Java APIs and clients
• language/new: Proposals for new client languages

Integrations

• integrations/azure: Azure and Azure ML integrations
• integrations/sagemaker: SageMaker integrations
• integrations/databricks: Databricks integrations

[lorenzwalthert]

Thanks @singankit. Looks like you have correctly identified the bug. Would b great if you can create a PR to fix it and add a test to demonstrate the correct behaviour.

[dbczumar]

Hi @singankit , we'd be very excited about your contribution of a fix for this issue. Please feel free to file a PR, and let me know if you have any questions about the implementation. Thank you in advance!

[bramrodenburg]

Issue is now fixed here: #5185

[singankit]

Thanks @bramrodenburg for the fix. Closing this bug.