forked from OSSInnovation/mindspore
!2279 add model zoo script of wide and deep for gpu
Merge pull request !2279 from zyli2020/add_model_script_of_wide_deep_for_gpu
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commit
164e6674b2
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@ -0,0 +1,28 @@
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#!/bin/bash
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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# bash run_multigpu_train.sh
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script_self=$(readlink -f "$0")
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self_path=$(dirname "${script_self}")
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RANK_SIZE=$1
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EPOCH_SIZE=$2
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DATASET=$3
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mpirun --allow-run-as-root -n $RANK_SIZE \
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python -s ${self_path}/../train_and_eval_distribute.py \
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--device_target="GPU" \
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--data_path=$DATASET \
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--epochs=$EPOCH_SIZE > log.txt 2>&1 &
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@ -31,5 +31,5 @@ do
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cd ${execute_path}/device_$i/ || exit
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export RANK_ID=$i
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export DEVICE_ID=$i
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python -s ${self_path}/../train_and_eval_multinpu.py --data_path=$DATASET --epochs=$EPOCH_SIZE >train_deep$i.log 2>&1 &
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python -s ${self_path}/../train_and_eval_distribute.py --data_path=$DATASET --epochs=$EPOCH_SIZE >train_deep$i.log 2>&1 &
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done
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@ -20,6 +20,8 @@ def argparse_init():
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argparse_init
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"""
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parser = argparse.ArgumentParser(description='WideDeep')
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parser.add_argument("--device_target", type=str, default="Ascend", choices=["Ascend", "GPU"],
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help="device where the code will be implemented. (Default: Ascend)")
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parser.add_argument("--data_path", type=str, default="./test_raw_data/")
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parser.add_argument("--epochs", type=int, default=15)
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parser.add_argument("--full_batch", type=bool, default=False)
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@ -44,6 +46,7 @@ class WideDeepConfig():
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WideDeepConfig
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"""
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def __init__(self):
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self.device_target = "Ascend"
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self.data_path = "./test_raw_data/"
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self.full_batch = False
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self.epochs = 15
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@ -72,6 +75,7 @@ class WideDeepConfig():
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"""
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parser = argparse_init()
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args, _ = parser.parse_known_args()
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self.device_target = args.device_target
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self.data_path = args.data_path
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self.epochs = args.epochs
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self.full_batch = args.full_batch
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@ -30,10 +30,6 @@ from src.metrics import AUCMetric
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from src.config import WideDeepConfig
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=True)
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context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, mirror_mean=True)
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init()
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def get_WideDeep_net(config):
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@ -105,4 +101,13 @@ def train_and_eval(config):
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if __name__ == "__main__":
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wide_deep_config = WideDeepConfig()
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wide_deep_config.argparse_init()
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context.set_context(mode=context.GRAPH_MODE, device_target=wide_deep_config.device_target, save_graphs=True)
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if wide_deep_config.device_target == "Ascend":
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init("hccl")
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elif wide_deep_config.device_target == "GPU":
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init("nccl")
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context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, mirror_mean=True,
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device_num=get_group_size())
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train_and_eval(wide_deep_config)
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