feat: Made display_name parameter optional for most calls

google/cloud/aiplatform/base.py

@@ -686,6 +686,13 @@ def to_dict(self) -> Dict[str, Any]:
         """Returns the resource proto as a dictionary."""
         return json_format.MessageToDict(self.gca_resource._pb)
 
+    @classmethod
+    def _generate_display_name(cls, prefix: Optional[str] = None) -> str:
+        """Returns a display name containing class name and time string."""
+        if not prefix:
+            prefix = cls.__name__
+        return prefix + " " + datetime.datetime.now().isoformat(sep=" ")
+
 
 def optional_sync(
     construct_object_on_arg: Optional[str] = None,

google/cloud/aiplatform/datasets/dataset.py

@@ -106,6 +106,7 @@ def _validate_metadata_schema_uri(self) -> None:
     @classmethod
     def create(
         cls,
+        # TODO(b/223262536): Make the display_name parameter optional in the next major release
         display_name: str,
         metadata_schema_uri: str,
         gcs_source: Optional[Union[str, Sequence[str]]] = None,
@@ -211,7 +212,8 @@ def create(
             dataset (Dataset):
                 Instantiated representation of the managed dataset resource.
         """
-
+        if not display_name:
+            display_name = cls._generate_display_name()
         utils.validate_display_name(display_name)
         if labels:
             utils.validate_labels(labels)

google/cloud/aiplatform/datasets/image_dataset.py

@@ -36,7 +36,7 @@ class ImageDataset(datasets._Dataset):
     @classmethod
     def create(
         cls,
-        display_name: str,
+        display_name: Optional[str] = None,
         gcs_source: Optional[Union[str, Sequence[str]]] = None,
         import_schema_uri: Optional[str] = None,
         data_item_labels: Optional[Dict] = None,
@@ -54,7 +54,7 @@ def create(
 
         Args:
             display_name (str):
-                Required. The user-defined name of the Dataset.
+                Optional. The user-defined name of the Dataset.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
             gcs_source (Union[str, Sequence[str]]):
@@ -129,6 +129,8 @@ def create(
             image_dataset (ImageDataset):
                 Instantiated representation of the managed image dataset resource.
         """
+        if not display_name:
+            display_name = cls._generate_display_name()
 
         utils.validate_display_name(display_name)
         if labels:

google/cloud/aiplatform/datasets/tabular_dataset.py

@@ -36,7 +36,7 @@ class TabularDataset(datasets._ColumnNamesDataset):
     @classmethod
     def create(
         cls,
-        display_name: str,
+        display_name: Optional[str] = None,
         gcs_source: Optional[Union[str, Sequence[str]]] = None,
         bq_source: Optional[str] = None,
         project: Optional[str] = None,
@@ -52,7 +52,7 @@ def create(
 
         Args:
             display_name (str):
-                Required. The user-defined name of the Dataset.
+                Optional. The user-defined name of the Dataset.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
             gcs_source (Union[str, Sequence[str]]):
@@ -110,7 +110,8 @@ def create(
             tabular_dataset (TabularDataset):
                 Instantiated representation of the managed tabular dataset resource.
         """
-
+        if not display_name:
+            display_name = cls._generate_display_name()
         utils.validate_display_name(display_name)
         if labels:
             utils.validate_labels(labels)

google/cloud/aiplatform/datasets/text_dataset.py

@@ -36,7 +36,7 @@ class TextDataset(datasets._Dataset):
     @classmethod
     def create(
         cls,
-        display_name: str,
+        display_name: Optional[str] = None,
         gcs_source: Optional[Union[str, Sequence[str]]] = None,
         import_schema_uri: Optional[str] = None,
         data_item_labels: Optional[Dict] = None,
@@ -61,7 +61,7 @@ def create(
 
         Args:
             display_name (str):
-                Required. The user-defined name of the Dataset.
+                Optional. The user-defined name of the Dataset.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
             gcs_source (Union[str, Sequence[str]]):
@@ -136,7 +136,8 @@ def create(
             text_dataset (TextDataset):
                 Instantiated representation of the managed text dataset resource.
         """
-
+        if not display_name:
+            display_name = cls._generate_display_name()
         utils.validate_display_name(display_name)
         if labels:
             utils.validate_labels(labels)

google/cloud/aiplatform/datasets/time_series_dataset.py

@@ -36,7 +36,7 @@ class TimeSeriesDataset(datasets._ColumnNamesDataset):
     @classmethod
     def create(
         cls,
-        display_name: str,
+        display_name: Optional[str] = None,
         gcs_source: Optional[Union[str, Sequence[str]]] = None,
         bq_source: Optional[str] = None,
         project: Optional[str] = None,
@@ -51,7 +51,7 @@ def create(
 
         Args:
             display_name (str):
-                Required. The user-defined name of the Dataset.
+                Optional. The user-defined name of the Dataset.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
             gcs_source (Union[str, Sequence[str]]):
@@ -108,7 +108,8 @@ def create(
                 Instantiated representation of the managed time series dataset resource.
 
         """
-
+        if not display_name:
+            display_name = cls._generate_display_name()
         utils.validate_display_name(display_name)
         if labels:
             utils.validate_labels(labels)

google/cloud/aiplatform/datasets/video_dataset.py

@@ -36,7 +36,7 @@ class VideoDataset(datasets._Dataset):
     @classmethod
     def create(
         cls,
-        display_name: str,
+        display_name: Optional[str] = None,
         gcs_source: Optional[Union[str, Sequence[str]]] = None,
         import_schema_uri: Optional[str] = None,
         data_item_labels: Optional[Dict] = None,
@@ -54,7 +54,7 @@ def create(
 
         Args:
             display_name (str):
-                Required. The user-defined name of the Dataset.
+                Optional. The user-defined name of the Dataset.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
             gcs_source (Union[str, Sequence[str]]):
@@ -129,7 +129,8 @@ def create(
             video_dataset (VideoDataset):
                 Instantiated representation of the managed video dataset resource.
         """
-
+        if not display_name:
+            display_name = cls._generate_display_name()
         utils.validate_display_name(display_name)
         if labels:
             utils.validate_labels(labels)

google/cloud/aiplatform/jobs.py

@@ -349,6 +349,7 @@ def completion_stats(self) -> Optional[gca_completion_stats.CompletionStats]:
     @classmethod
     def create(
         cls,
+        # TODO(b/223262536): Make the job_display_name parameter optional in the next major release
         job_display_name: str,
         model_name: Union[str, "aiplatform.Model"],
         instances_format: str = "jsonl",
@@ -537,6 +538,8 @@ def create(
             (jobs.BatchPredictionJob):
                 Instantiated representation of the created batch prediction job.
         """
+        if not job_display_name:
+            job_display_name = cls._generate_display_name()
 
         utils.validate_display_name(job_display_name)
 
@@ -1032,6 +1035,7 @@ class CustomJob(_RunnableJob):
 
     def __init__(
         self,
+        # TODO(b/223262536): Make display_name parameter fully optional in next major release
         display_name: str,
         worker_pool_specs: Union[List[Dict], List[aiplatform.gapic.WorkerPoolSpec]],
         base_output_dir: Optional[str] = None,
@@ -1136,6 +1140,9 @@ def __init__(
             staging_bucket, "aiplatform-custom-job"
         )
 
+        if not display_name:
+            display_name = self.__class__._generate_display_name()
+
         self._gca_resource = gca_custom_job_compat.CustomJob(
             display_name=display_name,
             job_spec=gca_custom_job_compat.CustomJobSpec(
@@ -1193,6 +1200,7 @@ def _log_web_access_uris(self):
     @classmethod
     def from_local_script(
         cls,
+        # TODO(b/223262536): Make display_name parameter fully optional in next major release
         display_name: str,
         script_path: str,
         container_uri: str,
@@ -1521,6 +1529,7 @@ class HyperparameterTuningJob(_RunnableJob):
 
     def __init__(
         self,
+        # TODO(b/223262536): Make display_name parameter fully optional in next major release
         display_name: str,
         custom_job: CustomJob,
         metric_spec: Dict[str, str],
@@ -1717,6 +1726,9 @@ def __init__(
             ],
         )
 
+        if not display_name:
+            display_name = self.__class__._generate_display_name()
+
         self._gca_resource = (
             gca_hyperparameter_tuning_job_compat.HyperparameterTuningJob(
                 display_name=display_name,

google/cloud/aiplatform/models.py

@@ -197,7 +197,7 @@ def network(self) -> Optional[str]:
     @classmethod
     def create(
         cls,
-        display_name: str,
+        display_name: Optional[str] = None,
         description: Optional[str] = None,
         labels: Optional[Dict[str, str]] = None,
         metadata: Optional[Sequence[Tuple[str, str]]] = (),
@@ -212,7 +212,7 @@ def create(
 
         Args:
             display_name (str):
-                Required. The user-defined name of the Endpoint.
+                Optional. The user-defined name of the Endpoint.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
             project (str):
@@ -263,6 +263,9 @@ def create(
 
         api_client = cls._instantiate_client(location=location, credentials=credentials)
 
+        if not display_name:
+            display_name = cls._generate_display_name()
+
         utils.validate_display_name(display_name)
         if labels:
             utils.validate_labels(labels)
@@ -1654,7 +1657,6 @@ def update(
     @base.optional_sync()
     def upload(
         cls,
-        display_name: str,
         serving_container_image_uri: str,
         *,
         artifact_uri: Optional[str] = None,
@@ -1670,6 +1672,7 @@ def upload(
         prediction_schema_uri: Optional[str] = None,
         explanation_metadata: Optional[explain.ExplanationMetadata] = None,
         explanation_parameters: Optional[explain.ExplanationParameters] = None,
+        display_name: Optional[str] = None,
         project: Optional[str] = None,
         location: Optional[str] = None,
         credentials: Optional[auth_credentials.Credentials] = None,
@@ -1692,7 +1695,7 @@ def upload(
 
         Args:
             display_name (str):
-                Required. The display name of the Model. The name can be up to 128
+                Optional. The display name of the Model. The name can be up to 128
                 characters long and can be consist of any UTF-8 characters.
             serving_container_image_uri (str):
                 Required. The URI of the Model serving container.
@@ -1832,6 +1835,8 @@ def upload(
                 is specified.
                 Also if model directory does not contain a supported model file.
         """
+        if not display_name:
+            display_name = cls._generate_display_name()
         utils.validate_display_name(display_name)
         if labels:
             utils.validate_labels(labels)
@@ -2231,7 +2236,7 @@ def _deploy(
 
     def batch_predict(
         self,
-        job_display_name: str,
+        job_display_name: Optional[str] = None,
         gcs_source: Optional[Union[str, Sequence[str]]] = None,
         bigquery_source: Optional[str] = None,
         instances_format: str = "jsonl",
@@ -2269,7 +2274,7 @@ def batch_predict(
 
         Args:
             job_display_name (str):
-                Required. The user-defined name of the BatchPredictionJob.
+                Optional. The user-defined name of the BatchPredictionJob.
                 The name can be up to 128 characters long and can be consist
                 of any UTF-8 characters.
             gcs_source: Optional[Sequence[str]] = None
@@ -2636,7 +2641,7 @@ def upload_xgboost_model_file(
         cls,
         model_file_path: str,
         xgboost_version: Optional[str] = None,
-        display_name: str = "XGBoost model",
+        display_name: Optional[str] = None,
         description: Optional[str] = None,
         instance_schema_uri: Optional[str] = None,
         parameters_schema_uri: Optional[str] = None,
@@ -2769,6 +2774,9 @@ def upload_xgboost_model_file(
                 is specified.
                 Also if model directory does not contain a supported model file.
         """
+        if not display_name:
+            display_name = cls.__class__.__generate_display_name("XGBoost model")
+
         XGBOOST_SUPPORTED_MODEL_FILE_EXTENSIONS = [
             ".pkl",
             ".joblib",
@@ -2835,7 +2843,7 @@ def upload_scikit_learn_model_file(
         cls,
         model_file_path: str,
         sklearn_version: Optional[str] = None,
-        display_name: str = "Scikit-learn model",
+        display_name: Optional[str] = None,
         description: Optional[str] = None,
         instance_schema_uri: Optional[str] = None,
         parameters_schema_uri: Optional[str] = None,
@@ -2969,6 +2977,9 @@ def upload_scikit_learn_model_file(
                 is specified.
                 Also if model directory does not contain a supported model file.
         """
+        if not display_name:
+            display_name = cls._generate_display_name("Scikit-Learn model")
+
         SKLEARN_SUPPORTED_MODEL_FILE_EXTENSIONS = [
             ".pkl",
             ".joblib",
@@ -3034,7 +3045,7 @@ def upload_tensorflow_saved_model(
         saved_model_dir: str,
         tensorflow_version: Optional[str] = None,
         use_gpu: bool = False,
-        display_name: str = "Tensorflow model",
+        display_name: Optional[str] = None,
         description: Optional[str] = None,
         instance_schema_uri: Optional[str] = None,
         parameters_schema_uri: Optional[str] = None,
@@ -3170,6 +3181,9 @@ def upload_tensorflow_saved_model(
                 is specified.
                 Also if model directory does not contain a supported model file.
         """
+        if not display_name:
+            display_name = cls._generate_display_name("Tensorflow model")
+
         container_image_uri = aiplatform.helpers.get_prebuilt_prediction_container_uri(
             region=location,
             framework="tensorflow",

google/cloud/aiplatform/pipeline_jobs.py

@@ -92,6 +92,7 @@ class PipelineJob(base.VertexAiStatefulResource):
 
     def __init__(
         self,
+        # TODO(b/223262536): Make the display_name parameter optional in the next major release
         display_name: str,
         template_path: str,
         job_id: Optional[str] = None,
@@ -160,6 +161,8 @@ def __init__(
         Raises:
             ValueError: If job_id or labels have incorrect format.
         """
+        if not display_name:
+            display_name = self.__class__._generate_display_name()
         utils.validate_display_name(display_name)
 
         if labels: