Upload batch prediction job sample (#2705)

* Upload examples of kfp v2

* Upload run experiment example.

* Upload batch prediction job sample.

community-content/vertex_pipeline_kfpv2/batch_prediction.py

@@ -0,0 +1,47 @@
+from kfp.v2 import dsl
+
+@dsl.component(base_image='python:3.8',packages_to_install=['google-cloud-aiplatform==1.36.0'])
+def batch_predict(
+    model_id: str,
+    job_name: str,
+    file_format: str,
+    file_sources: List[str],
+    out_sources: str,
+    machine_type: str,
+    min_replica_count: int,
+    max_replica_count: int,
+):
+    import json
+    from google.cloud import aiplatform
+
+    aiplatform.init(
+        project=project_id,
+        location=location,
+    )
+    
+    model = aiplatform.Model(model_id)
+    batch_job = model.batch_predict(
+        job_display_name=job_name,
+        instances_format=file_format,
+        gcs_source=file_sources,
+        gcs_destination_prefix=out_sources,
+        machine_type=machine_typem,
+        starting_replica_count=min_replica_count,
+        max_replica_count=max_replica_count,
+    )
+    batch_job.wait()
+
+
+@dsl.pipeline(name='batch-predict')
+def pipeline_batch_predict():
+    batch_predict('projects/990000000009/locations/us-west1/models/1100000000000000001',
+        'batch-predict-job', 'csv',
+        ['gs://yourbucket/predict/file.csv'], 'gs://yourbucket/results/',
+        'n1-standard-2', 1, 1)
+
+
+if __name__ == "__main__":
+    from kfp.v2 import compiler
+    compiler.Compiler().compile(
+        pipeline_func=pipeline_batch_predict,
+        package_path='batch_predict.json')