[GitHub] [airflow] kosteev commented on a change in pull request #21470: Create Auto ML operators for Vertex AI service

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kosteev commented on a change in pull request #21470:
URL: https://github.com/apache/airflow/pull/21470#discussion_r811151561



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File path: airflow/providers/google/cloud/operators/vertex_ai/auto_ml.py
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@@ -0,0 +1,707 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+"""This module contains Google Vertex AI operators."""
+
+from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Tuple, Union
+
+from google.api_core.exceptions import NotFound
+from google.api_core.retry import Retry
+from google.cloud.aiplatform import datasets
+from google.cloud.aiplatform.models import Model
+from google.cloud.aiplatform_v1.types.training_pipeline import TrainingPipeline
+
+from airflow.models import BaseOperator, BaseOperatorLink
+from airflow.models.xcom import XCom
+from airflow.providers.google.cloud.hooks.vertex_ai.auto_ml import AutoMLHook
+
+if TYPE_CHECKING:
+    from airflow.utils.context import Context
+
+VERTEX_AI_BASE_LINK = "https://console.cloud.google.com/vertex-ai"
+VERTEX_AI_MODEL_LINK = (
+    VERTEX_AI_BASE_LINK + "/locations/{region}/models/{model_id}/deploy?project={project_id}"
+)
+VERTEX_AI_TRAINING_PIPELINES_LINK = VERTEX_AI_BASE_LINK + "/training/training-pipelines?project={project_id}"
+
+
+class VertexAIModelLink(BaseOperatorLink):
+    """Helper class for constructing Vertex AI Model link"""
+
+    name = "Vertex AI Model"
+
+    def get_link(self, operator, dttm):
+        model_conf = XCom.get_one(
+            key='model_conf', dag_id=operator.dag.dag_id, task_id=operator.task_id, execution_date=dttm
+        )
+        return (
+            VERTEX_AI_MODEL_LINK.format(
+                region=model_conf["region"],
+                model_id=model_conf["model_id"],
+                project_id=model_conf["project_id"],
+            )
+            if model_conf
+            else ""
+        )
+
+
+class VertexAITrainingPipelinesLink(BaseOperatorLink):
+    """Helper class for constructing Vertex AI Training Pipelines link"""
+
+    name = "Vertex AI Training Pipelines"
+
+    def get_link(self, operator, dttm):
+        project_id = XCom.get_one(
+            key='project_id', dag_id=operator.dag.dag_id, task_id=operator.task_id, execution_date=dttm
+        )
+        return (
+            VERTEX_AI_TRAINING_PIPELINES_LINK.format(
+                project_id=project_id,
+            )
+            if project_id
+            else ""
+        )
+
+
+class AutoMLTrainingJobBaseOperator(BaseOperator):
+    """The base class for operators that launch AutoML jobs on VertexAI."""
+
+    def __init__(
+        self,
+        *,
+        project_id: str,
+        region: str,
+        display_name: str,
+        labels: Optional[Dict[str, str]] = None,
+        training_encryption_spec_key_name: Optional[str] = None,
+        model_encryption_spec_key_name: Optional[str] = None,
+        # RUN
+        training_fraction_split: Optional[float] = None,
+        test_fraction_split: Optional[float] = None,
+        model_display_name: Optional[str] = None,
+        model_labels: Optional[Dict[str, str]] = None,
+        sync: bool = True,
+        gcp_conn_id: str = "google_cloud_default",
+        delegate_to: Optional[str] = None,
+        impersonation_chain: Optional[Union[str, Sequence[str]]] = None,

Review comment:
       @MaksYermak Is this consistent with approach that we have in other google operators?
   I think it should be good as long as we consistent everywhere.




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