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Regenerate r doc and avoid R CMD check error (#2553)
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* making roxygen comment a normal comment to avoid R CMD check failure due to noncomplete internal doc.

Also, then simply regenerating docs.

* add missing namespace prefix
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lorenzwalthert committed Mar 17, 2020
1 parent d96210f commit 3dd46c6
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Showing 3 changed files with 9 additions and 6 deletions.
9 changes: 6 additions & 3 deletions docs/source/R-api.rst
Expand Up @@ -1301,9 +1301,9 @@ model types.

.. code:: r
list(list("mlflow_save_model"), list("crate"))(model, path, ...)
list(list("mlflow_save_model"), list("keras.engine.training.Model"))(model, path, conda_env = NULL, ...)
mlflow_save_model(model, path, ...)
list(list("mlflow_save_model"), list("crate"))(model, path, model_spec = list(), ...)
list(list("mlflow_save_model"), list("keras.engine.training.Model"))(model, path, model_spec = list(), conda_env = NULL, ...)
mlflow_save_model(model, path, model_spec = list(), ...)
.. _arguments-29:

Expand All @@ -1320,6 +1320,9 @@ Arguments
| | MLflow compatible model will be |
| | saved. |
+-----------------------------------+-----------------------------------+
| ``model_spec`` | MLflow model config this model |
| | flavor is being added to. |
+-----------------------------------+-----------------------------------+
| ``...`` | Optional additional arguments. |
+-----------------------------------+-----------------------------------+
| ``conda_env`` | Path to Conda dependencies file. |
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2 changes: 1 addition & 1 deletion mlflow/R/mlflow/NAMESPACE
Expand Up @@ -66,7 +66,7 @@ importFrom(httr,config)
importFrom(httr,content)
importFrom(httr,timeout)
importFrom(ini,read.ini)
importFrom(jsonlite,fromJSON, toJSON)
importFrom(jsonlite,fromJSON)
importFrom(openssl,rand_num)
importFrom(processx,process)
importFrom(processx,run)
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4 changes: 2 additions & 2 deletions mlflow/R/mlflow/R/tracking-runs.R
Expand Up @@ -489,12 +489,12 @@ mlflow_log_artifact <- function(path, artifact_path = NULL, run_id = NULL, clien
invisible(mlflow_list_artifacts(run_id = run_id, path = artifact_path, client = client))
}

#' Record logged model metadata with the trackin server.
# Record logged model metadata with the tracking server.
mlflow_record_logged_model <- function(model_spec, run_id = NULL, client = NULL) {
c(client, run_id) %<-% resolve_client_and_run_id(client, run_id)
mlflow_rest("runs", "log-model", client = client, verb = "POST", data = list(
run_id = run_id,
model_json = toJSON(model_spec, auto_unbox=TRUE)
model_json = jsonlite::toJSON(model_spec, auto_unbox=TRUE)
))
}

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