dags/solutions_team/solutionsteam_tf_dlrm_benchmarks.py (108 lines of code) (raw):

# Copyright 2024 Google LLC # # Licensed 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. """A DAG to run all supported ML models with the nightly TensorFlow version.""" import time import datetime from airflow import models from dags import composer_env from dags.common.vm_resource import TpuVersion, Project, Zone, RuntimeVersion, V5_NETWORKS, V5E_SUBNETWORKS, V5P_SUBNETWORKS from dags.solutions_team.configs.tensorflow import solutionsteam_tf_release_supported_config as tf_config from dags.solutions_team.configs.tensorflow import common # Release tests only need to run once, they can be run manually as needed SCHEDULED_TIME = None VERSION = f"{tf_config.MAJOR_VERSION}.{tf_config.MINOR_VERSION}" with models.DAG( dag_id=f"tf_dlrm_{tf_config.MAJOR_VERSION}_{tf_config.MINOR_VERSION}", schedule=SCHEDULED_TIME, tags=["solutions_team", "tf", "se", VERSION, "supported", "xlml"], start_date=datetime.datetime(2024, 1, 4), catchup=False, ) as dag: embedding_dim = 32 tf_dlrm_v4_8 = tf_config.get_tf_dlrm_config( tpu_version=TpuVersion.V4, tpu_cores=8, tpu_zone=Zone.US_CENTRAL2_B.value, time_out_in_min=60, bottom_mlp=[512, 256, embedding_dim], embedding_dim=embedding_dim, train_steps=10000, extraFlags="--mode=train", is_pjrt=False, runtime_version=RuntimeVersion.V2_ALPHA_TPUV5.value, ) embedding_dim = 128 tf_dlrm_v4_64 = tf_config.get_tf_dlrm_config( tpu_version=TpuVersion.V4, tpu_cores=64, tpu_zone=Zone.US_CENTRAL2_B.value, time_out_in_min=60, bottom_mlp=[512, 256, embedding_dim], embedding_dim=embedding_dim, train_steps=10000, extraFlags="--mode=train", is_pod=True, is_pjrt=False, runtime_version=RuntimeVersion.V2_ALPHA_TPUV5.value, ) embedding_dim = 128 tf_dlrm_v4_128 = tf_config.get_tf_dlrm_config( tpu_version=TpuVersion.V4, tpu_cores=128, tpu_zone=Zone.US_CENTRAL2_B.value, time_out_in_min=60, bottom_mlp=[512, 256, embedding_dim], embedding_dim=embedding_dim, train_steps=10000, extraFlags="--mode=train", is_pod=True, is_pjrt=False, runtime_version=RuntimeVersion.V2_ALPHA_TPUV5.value, ) embedding_dim = 32 tf_dlrm_v5p_8 = tf_config.get_tf_dlrm_config( project_name=Project.TPU_PROD_ENV_AUTOMATED.value, tpu_version=TpuVersion.V5P, tpu_cores=8, tpu_zone=Zone.US_EAST5_A.value, time_out_in_min=60, bottom_mlp=[512, 256, embedding_dim], embedding_dim=embedding_dim, train_steps=10000, extraFlags="--mode=train", is_pod=False, is_pjrt=True, network=V5_NETWORKS, subnetwork=V5P_SUBNETWORKS, runtime_version=RuntimeVersion.V2_ALPHA_TPUV5.value, ) embedding_dim = 64 tf_dlrm_v5p_64 = tf_config.get_tf_dlrm_config( project_name=Project.TPU_PROD_ENV_AUTOMATED.value, tpu_version=TpuVersion.V5P, tpu_cores=64, tpu_zone=Zone.US_EAST5_A.value, time_out_in_min=60, bottom_mlp=[512, 256, embedding_dim], embedding_dim=embedding_dim, train_steps=10000, extraFlags="--mode=train", is_pod=True, is_pjrt=True, network=V5_NETWORKS, subnetwork=V5P_SUBNETWORKS, runtime_version=RuntimeVersion.V2_ALPHA_TPUV5.value, ) embedding_dim = 128 tf_dlrm_v5p_128 = tf_config.get_tf_dlrm_config( project_name=Project.TPU_PROD_ENV_AUTOMATED.value, tpu_version=TpuVersion.V5P, tpu_cores=128, tpu_zone=Zone.US_EAST5_A.value, time_out_in_min=60, bottom_mlp=[512, 256, embedding_dim], embedding_dim=embedding_dim, train_steps=10000, extraFlags="--mode=train", is_pod=True, is_pjrt=True, network=V5_NETWORKS, subnetwork=V5P_SUBNETWORKS, runtime_version=RuntimeVersion.V2_ALPHA_TPUV5.value, ) # Test dependencies # tf_dlrm_v4_8 >> tf_dlrm_v4_64 >> tf_dlrm_v4_128 # tf_dlrm_v5p_64 >> tf_dlrm_v5p_128