improve docstr of preprocessors (#1227)

* improve docstr of preprocessors * Update SynapseML version * RFix test --------- Co-authored-by: Li Jiang <[email protected]>
microsoft · Sep 29, 2023 · fda9fa0 · fda9fa0
1 parent 830ec45
commit fda9fa0
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Showing 2 changed files with 12 additions and 10 deletions.
diff --git a/flaml/automl/automl.py b/flaml/automl/automl.py
@@ -476,12 +476,12 @@ def save_best_config(self, filename):
 
  @property
  def feature_transformer(self):
- """Returns AutoML Transformer"""
+ """Returns feature transformer which is used to preprocess data before applying training or inference."""
  return getattr(self, "_transformer", None)
 
  @property
  def label_transformer(self):
- """Returns AutoML label transformer"""
+ """Returns label transformer which is used to preprocess labels before scoring, and inverse transform labels after inference."""
  return getattr(self, "_label_transformer", None)
 
  @property

diff --git a/test/spark/test_0sparkml.py b/test/spark/test_0sparkml.py
@@ -17,13 +17,14 @@
  from pyspark.ml.feature import VectorAssembler
  from flaml.automl.spark.utils import to_pandas_on_spark
 
+ postfix_version = "-spark3.3," if pyspark.__version__ > "3.2" else ","
  spark = (
  pyspark.sql.SparkSession.builder.appName("MyApp")
  .master("local[2]")
  .config(
  "spark.jars.packages",
  (
- "com.microsoft.azure:synapseml_2.12:0.10.2,"
+ f"com.microsoft.azure:synapseml_2.12:0.11.3{postfix_version}"
  "org.apache.hadoop:hadoop-azure:3.3.5,"
  "com.microsoft.azure:azure-storage:8.6.6,"
  f"org.mlflow:mlflow-spark:{mlflow.__version__}"
@@ -172,15 +173,16 @@ def test_spark_input_df():
  try:
  model = automl.model.estimator
  predictions = model.transform(test_data)
+ predictions.show()
 
- from synapse.ml.train import ComputeModelStatistics
+ # from synapse.ml.train import ComputeModelStatistics
 
- metrics = ComputeModelStatistics(
- evaluationMetric="classification",
- labelCol="Bankrupt?",
- scoredLabelsCol="prediction",
- ).transform(predictions)
- metrics.show()
+ # metrics = ComputeModelStatistics(
+ #  evaluationMetric="classification",
+ #  labelCol="Bankrupt?",
+ #  scoredLabelsCol="prediction",
+ # ).transform(predictions)
+ # metrics.show()
  except AttributeError:
  print("No fitted model because of too short training time.")