Release version 2.6.7

ads/ads_version.json

@@ -1,3 +1,3 @@
 {
- "version": "2.6.6"
+ "version": "2.6.7"
 }

ads/automl/provider.py

@@ -28,6 +28,7 @@
  runtime_dependency,
  OptionalDependency,
 )
+from ads.common.decorator.deprecate import deprecated
 from ads.dataset.label_encoder import DataFrameLabelEncoder
 from ads.dataset.helper import is_text_data
 
@@ -305,6 +306,10 @@ def decide_estimator(self, **kwargs):
 
 # An installation of oracle labs automl is required only for this class
 class OracleAutoMLProvider(AutoMLProvider, ABC):
+ @deprecated(
+ "2.6.7",
+ details="Oracle AutoML is recommended to be directly instantiated by importing automlx package",
+ )
  def __init__(
  self, n_jobs=-1, loglevel=None, logger_override=None, model_n_jobs: int = 1
  ):

ads/common/data_serializer.py

@@ -66,10 +66,9 @@ def __init__(
  pass
  else:
  raise TypeError(
- "The provided data type is not json serializable. "
  "The supported data types are Dict, str, list, "
  "numpy.ndarray, pd.core.series.Series, "
- "pd.core.frame.DataFrame. Please "
+ "pd.core.frame.DataFrame, bytes. Please "
  "convert to the supported data types first. "
  )
 
@@ -106,6 +105,7 @@ def send(self, endpoint: str, dry_run: bool = False, **kwargs):
  )
  request_kwargs = {"json": self.to_dict()}
  request_kwargs["headers"] = headers
+
  if dry_run:
  request_kwargs["headers"]["Accept"] = "*/*"
  req = requests.Request("POST", endpoint, **request_kwargs).prepare()

ads/common/model_metadata.py

@@ -142,6 +142,7 @@ class MetadataCustomKeys(str, metaclass=ExtendedEnumMeta):
  VALIDATION_DATASET_NUMBER_OF_ROWS = "ValidationDatasetNumberOfRows"
  VALIDATION_DATASET_NUMBER_OF_COLS = "ValidationDataSetNumberOfCols"
  CLIENT_LIBRARY = "ClientLibrary"
+ MODEL_FILE_NAME = "ModelFileName"
 
 
 class MetadataCustomCategory(str, metaclass=ExtendedEnumMeta):

ads/common/model_metadata_mixin.py

@@ -173,14 +173,30 @@ def _populate_metadata_custom(self):
  category=MetadataCustomCategory.TRAINING_ENV,
  )
  )
- model_metadata_items.append(
- ModelCustomMetadataItem(
- key=MetadataCustomKeys.MODEL_SERIALIZATION_FORMAT,
- value=self.model_file_name.split(".")[-1],
- description="The model serialization format.",
- category=MetadataCustomCategory.TRAINING_PROFILE,
+
+ if self.model_file_name:
+ model_metadata_items.append(
+ ModelCustomMetadataItem(
+ key=MetadataCustomKeys.MODEL_SERIALIZATION_FORMAT,
+ value=self.model_file_name.split(".")[-1],
+ description="The model serialization format.",
+ category=MetadataCustomCategory.TRAINING_PROFILE,
+ )
  )
- )
+ model_metadata_items.append(
+ ModelCustomMetadataItem(
+ key=MetadataCustomKeys.MODEL_FILE_NAME,
+ value=self.model_file_name,
+ description="The model file name.",
+ category=MetadataCustomCategory.OTHER,
+ )
+ )
+ else:
+ logger.warning(
+ "Unable to extract a model serialization format. "
+ "The `model_file_name` is not provided."
+ )
+
  model_metadata_items.append(
  ModelCustomMetadataItem(
  key=MetadataCustomKeys.CLIENT_LIBRARY,