fix: Minor docstring and snippet fixes (#873)

* docs: Update batch prediction job instance, predict format docstrings

* Update AutoML predict snippets to refer to correct YAML

Co-authored-by: Dan Lee <71398022+dandhlee@users.noreply.github.com>

.sample_configs/process_configs.yaml

@@ -266,7 +266,7 @@ predict_image_classification_sample:
     instance_dict: predict.instance.ImageClassificationPredictionInstance
     parameters_dict: predict.params.ImageClassificationPredictionParams
   comments:
-    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/classification.yaml
+    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/image_classification_1.0.0.yaml
       for the format of the predictions.
 predict_image_file_sample:
   max_depth: 1
@@ -278,7 +278,7 @@ predict_image_object_detection_sample:
     instance_dict: predict.instance.ImageObjectDetectionPredictionInstance
     parameters_dict: predict.params.ImageObjectDetectionPredictionParams
   comments:
-    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/image_object_detection.yaml
+    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/image_object_detection_1.0.0.yaml
       for the format of the predictions.
 predict_sample:
   max_depth: 1
@@ -290,38 +290,35 @@ predict_tabular_classification_sample:
   max_depth: 1
   resource_name: endpoint
   comments:
-    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/tables_classification.yaml
+    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/tabular_classification_1.0.0.yaml
       for the format of the predictions.
 predict_tabular_forecasting_sample: {}
 predict_tabular_regression_sample:
   max_depth: 1
   resource_name: endpoint
   comments:
-    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/tables_regression.yaml
+    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/tabular_regression_1.0.0.yaml
       for the format of the predictions.
 predict_text_classification_single_label_sample:
   max_depth: 1
   resource_name: endpoint
   schema_types:
     instance_dict: predict.instance.TextClassificationPredictionInstance
-  comments:
-    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/text_classification.yaml
-      for the format of the predictions.
 predict_text_entity_extraction_sample:
   max_depth: 1
   resource_name: endpoint
   schema_types:
     instance_dict: predict.instance.TextExtractionPredictionInstance
   comments:
-    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/text_extraction.yaml
+    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/text_extraction_1.0.0.yaml
       for the format of the predictions.
 predict_text_sentiment_analysis_sample:
   max_depth: 1
   resource_name: endpoint
   schema_types:
     instance_dict: predict.instance.TextSentimentPredictionInstance
   comments:
-    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/text_sentiment.yaml
+    predictions: See gs://google-cloud-aiplatform/schema/predict/prediction/text_sentiment_1.0.0.yaml
       for the format of the predictions.
 search_migratable_resources_sample: {}
 undeploy_model_sample:

google/cloud/aiplatform/jobs.py

@@ -380,13 +380,14 @@ def create(
 
                 Or an instance of aiplatform.Model.
             instances_format (str):
-                Required. The format in which instances are given, must be one
-                of "jsonl", "csv", "bigquery", "tf-record", "tf-record-gzip",
-                or "file-list". Default is "jsonl" when using `gcs_source`. If a
-                `bigquery_source` is provided, this is overridden to "bigquery".
+                Required. The format in which instances are provided. Must be one
+                of the formats listed in `Model.supported_input_storage_formats`.
+                Default is "jsonl" when using `gcs_source`. If a `bigquery_source`
+                is provided, this is overridden to "bigquery".
             predictions_format (str):
-                Required. The format in which Vertex AI gives the
-                predictions, must be one of "jsonl", "csv", or "bigquery".
+                Required. The format in which Vertex AI outputs the
+                predictions, must be one of the formats specified in
+                `Model.supported_output_storage_formats`.
                 Default is "jsonl" when using `gcs_destination_prefix`. If a
                 `bigquery_destination_prefix` is provided, this is overridden to
                 "bigquery".

google/cloud/aiplatform/models.py

@@ -2099,10 +2099,10 @@ def batch_predict(
                 BigQuery URI to a table, up to 2000 characters long. For example:
                 `bq://projectId.bqDatasetId.bqTableId`
             instances_format: str = "jsonl"
-                Required. The format in which instances are given, must be one
-                of "jsonl", "csv", "bigquery", "tf-record", "tf-record-gzip",
-                or "file-list". Default is "jsonl" when using `gcs_source`. If a
-                `bigquery_source` is provided, this is overridden to "bigquery".
+                The format in which instances are provided. Must be one
+                of the formats listed in `Model.supported_input_storage_formats`.
+                Default is "jsonl" when using `gcs_source`. If a `bigquery_source`
+                is provided, this is overridden to "bigquery".
             gcs_destination_prefix: Optional[str] = None
                 The Google Cloud Storage location of the directory where the
                 output is to be written to. In the given directory a new
@@ -2145,8 +2145,9 @@ def batch_predict(
                 ```google.rpc.Status`` <Status>`__ represented as a STRUCT,
                 and containing only ``code`` and ``message``.
             predictions_format: str = "jsonl"
-                Required. The format in which Vertex AI gives the
-                predictions, must be one of "jsonl", "csv", or "bigquery".
+                Required. The format in which Vertex AI outputs the
+                predictions, must be one of the formats specified in
+                `Model.supported_output_storage_formats`.
                 Default is "jsonl" when using `gcs_destination_prefix`. If a
                 `bigquery_destination_prefix` is provided, this is overridden to
                 "bigquery".

samples/snippets/prediction_service/predict_image_classification_sample.py

@@ -52,7 +52,7 @@ def predict_image_classification_sample(
     )
     print("response")
     print(" deployed_model_id:", response.deployed_model_id)
-    # See gs://google-cloud-aiplatform/schema/predict/prediction/classification.yaml for the format of the predictions.
+    # See gs://google-cloud-aiplatform/schema/predict/prediction/image_classification_1.0.0.yaml for the format of the predictions.
     predictions = response.predictions
     for prediction in predictions:
         print(" prediction:", dict(prediction))

samples/snippets/prediction_service/predict_tabular_classification_sample.py

@@ -46,7 +46,7 @@ def predict_tabular_classification_sample(
     )
     print("response")
     print(" deployed_model_id:", response.deployed_model_id)
-    # See gs://google-cloud-aiplatform/schema/predict/prediction/tables_classification.yaml for the format of the predictions.
+    # See gs://google-cloud-aiplatform/schema/predict/prediction/tabular_classification_1.0.0.yaml for the format of the predictions.
     predictions = response.predictions
     for prediction in predictions:
         print(" prediction:", dict(prediction))

samples/snippets/prediction_service/predict_tabular_regression_sample.py

@@ -46,7 +46,7 @@ def predict_tabular_regression_sample(
     )
     print("response")
     print(" deployed_model_id:", response.deployed_model_id)
-    # See gs://google-cloud-aiplatform/schema/predict/prediction/tables_regression.yaml for the format of the predictions.
+    # See gs://google-cloud-aiplatform/schema/predict/prediction/tabular_regression_1.0.0.yaml for the format of the predictions.
     predictions = response.predictions
     for prediction in predictions:
         print(" prediction:", dict(prediction))

samples/snippets/prediction_service/predict_text_classification_single_label_sample.py

@@ -45,7 +45,7 @@ def predict_text_classification_single_label_sample(
     )
     print("response")
     print(" deployed_model_id:", response.deployed_model_id)
-    # See gs://google-cloud-aiplatform/schema/predict/prediction/text_classification.yaml for the format of the predictions.
+
     predictions = response.predictions
     for prediction in predictions:
         print(" prediction:", dict(prediction))

samples/snippets/prediction_service/predict_text_entity_extraction_sample.py

@@ -46,7 +46,7 @@ def predict_text_entity_extraction_sample(
     )
     print("response")
     print(" deployed_model_id:", response.deployed_model_id)
-    # See gs://google-cloud-aiplatform/schema/predict/prediction/text_extraction.yaml for the format of the predictions.
+    # See gs://google-cloud-aiplatform/schema/predict/prediction/text_extraction_1.0.0.yaml for the format of the predictions.
     predictions = response.predictions
     for prediction in predictions:
         print(" prediction:", dict(prediction))

samples/snippets/prediction_service/predict_text_sentiment_analysis_sample.py

@@ -45,7 +45,7 @@ def predict_text_sentiment_analysis_sample(
     )
     print("response")
     print(" deployed_model_id:", response.deployed_model_id)
-    # See gs://google-cloud-aiplatform/schema/predict/prediction/text_sentiment.yaml for the format of the predictions.
+    # See gs://google-cloud-aiplatform/schema/predict/prediction/text_sentiment_1.0.0.yaml for the format of the predictions.
     predictions = response.predictions
     for prediction in predictions:
         print(" prediction:", dict(prediction))