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Update tensorflow image uris for VertexAI system tests #119

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Original file line number Diff line number Diff line change
Expand Up @@ -68,9 +68,8 @@ def TABULAR_DATASET(bucket_name):
}


CONTAINER_URI = "gcr.io/cloud-aiplatform/training/tf-cpu.2-2:latest"
CUSTOM_CONTAINER_URI = "us-central1-docker.pkg.dev/airflow-system-tests-resources/system-tests/housing"
MODEL_SERVING_CONTAINER_URI = "gcr.io/cloud-aiplatform/prediction/tf2-cpu.2-2:latest"
MODEL_SERVING_CONTAINER_URI = "us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-2:latest"
REPLICA_COUNT = 1
MACHINE_TYPE = "n1-standard-4"
ACCELERATOR_TYPE = "ACCELERATOR_TYPE_UNSPECIFIED"
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Original file line number Diff line number Diff line change
Expand Up @@ -68,8 +68,8 @@ def TABULAR_DATASET(bucket_name):
}


CONTAINER_URI = "gcr.io/cloud-aiplatform/training/tf-cpu.2-2:latest"
MODEL_SERVING_CONTAINER_URI = "gcr.io/cloud-aiplatform/prediction/tf2-cpu.2-2:latest"
CONTAINER_URI = "us-docker.pkg.dev/vertex-ai/training/tf-cpu.2-2:latest"
MODEL_SERVING_CONTAINER_URI = "us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-2:latest"
REPLICA_COUNT = 1

# VERTEX_AI_LOCAL_TRAINING_SCRIPT_PATH should be set for Airflow which is running on distributed system.
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Original file line number Diff line number Diff line change
Expand Up @@ -68,8 +68,8 @@ def TABULAR_DATASET(bucket_name):
}


CONTAINER_URI = "gcr.io/cloud-aiplatform/training/tf-cpu.2-2:latest"
MODEL_SERVING_CONTAINER_URI = "gcr.io/cloud-aiplatform/prediction/tf2-cpu.2-2:latest"
CONTAINER_URI = "us-docker.pkg.dev/vertex-ai/training/tf-cpu.2-2:latest"
MODEL_SERVING_CONTAINER_URI = "us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-2:latest"
REPLICA_COUNT = 1
MACHINE_TYPE = "n1-standard-4"
ACCELERATOR_TYPE = "ACCELERATOR_TYPE_UNSPECIFIED"
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Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,7 @@
),
}

CONTAINER_URI = "gcr.io/cloud-aiplatform/training/tf-cpu.2-2:latest"
CONTAINER_URI = "us-docker.pkg.dev/vertex-ai/training/tf-cpu.2-2:latest"

# LOCAL_TRAINING_SCRIPT_PATH should be set for Airflow which is running on distributed system.
# For example in Composer the correct path is `gcs/data/california_housing_training_script.py`.
Expand All @@ -99,7 +99,7 @@
},
"export_format_id": "custom-trained",
}
MODEL_SERVING_CONTAINER_URI = "gcr.io/cloud-aiplatform/prediction/tf2-cpu.2-2:latest"
MODEL_SERVING_CONTAINER_URI = "us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-2:latest"
MODEL_OBJ = {
"display_name": f"model-{ENV_ID}",
"artifact_uri": "{{ti.xcom_pull('custom_task')['artifactUri']}}",
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