forked from mindspore-Ecosystem/mindspore
!19527 cnn_direction_model gpu version
Merge pull request !19527 from panfengfeng/add_cnn_direction_model_gpu_version
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commit
17c9b7397d
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#!/bin/bash
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# Copyright 2021 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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if [ $# != 3 ] && [ $# != 4 ]
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then
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echo "Usage:
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sh scripts/run_distribute_train_gpu.sh [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [PRETRAINED_CKPT_PATH](optional)
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"
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exit 1
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fi
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if [ $1 -lt 1 ] && [ $1 -gt 8 ]
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then
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echo "error: DEVICE_NUM=$1 is not in (1-8)"
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exit 1
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fi
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get_real_path(){
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if [ "${1:0:1}" == "/" ]; then
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echo "$1"
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else
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echo "$(realpath -m $PWD/$1)"
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fi
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}
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PATH1=$(get_real_path $3)
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if [ $# == 4 ]
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then
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PATH2=$(get_real_path $4)
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fi
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if [ ! -d $PATH1 ]
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then
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echo "error: DATASET_PATH=$PATH1 is not a directory"
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exit 1
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fi
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if [ $# == 4 ] && [ ! -f $PATH2 ]
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then
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echo "error: PRETRAINED_CKPT_PATH=$PATH2 is not a file"
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exit 1
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fi
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export DEVICE_NUM=$1
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export RANK_SIZE=$1
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if [ -d "./train" ];
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then
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rm -rf ./train
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fi
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mkdir ./train
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cd ./train || exit
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export CUDA_VISIBLE_DEVICES="$2"
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if [ $# == 3 ]
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then
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mpirun -n $1 --allow-run-as-root --output-filename log_output --merge-stderr-to-stdout \
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python ../train.py \
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--run_distribute=True \
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--train_dataset_path=$PATH1 > train.log 2>&1 &
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fi
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if [ $# == 4 ]
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then
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mpirun -n $1 --allow-run-as-root --output-filename log_output --merge-stderr-to-stdout \
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python ../train.py \
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--run_distribute=True \
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--train_dataset_path=$PATH1 \
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--pre_trained=$PATH2 > train.log 2>&1 &
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fi
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@ -0,0 +1,48 @@
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#!/bin/bash
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# Copyright 2021 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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if [ $# != 2 ]
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then
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echo "Usage:
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sh scripts/run_eval_gpu.sh [DATASET_PATH] [PRETRAINED_CKPT_PATH]
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"
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exit 1
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fi
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get_real_path(){
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if [ "${1:0:1}" == "/" ]; then
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echo "$1"
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else
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echo "$(realpath -m $PWD/$1)"
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fi
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}
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PATH1=$(get_real_path $1)
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PATH2=$(get_real_path $2)
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if [ ! -f $PATH2 ]
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then
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echo "error: PRETRAINED_CKPT_PATH=$PATH2 is not a file"
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exit 1
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fi
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if [ -d "./eval" ];
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then
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rm -rf ./eval
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fi
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mkdir ./eval
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cd ./eval || exit
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python ../eval.py --eval_dataset_path=$PATH1 --checkpoint_path=$PATH2 > eval.log 2>&1 &
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@ -0,0 +1,61 @@
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#!/bin/bash
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# Copyright 2021 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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if [ $# != 1 ] && [ $# != 2 ]
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then
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echo "Usage:
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sh scripts/run_standalone_train_gpu.sh [DATASET_PATH] [PRETRAINED_CKPT_PATH](optional)
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"
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exit 1
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fi
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get_real_path(){
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if [ "${1:0:1}" == "/" ]; then
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echo "$1"
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else
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echo "$(realpath -m $PWD/$1)"
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fi
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}
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PATH1=$(get_real_path $1)
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if [ $# == 2 ]
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then
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PATH2=$(get_real_path $2)
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fi
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if [ $# == 2 ] && [ ! -f $PATH2 ]
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then
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echo "error: PRETRAINED_CKPT_PATH=$PATH2 is not a file"
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exit 1
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fi
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if [ -d "./train" ];
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then
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rm -rf ./train
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fi
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mkdir ./train
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cd ./train || exit
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if [ $# == 1 ]
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then
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python ../train.py --train_dataset_path=$PATH1 > train.log 2>&1 &
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fi
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if [ $# == 2 ]
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then
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python ../train.py --train_dataset_path=$PATH1 --pre_trained=$PATH2 > train.log 2>&1 &
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fi
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@ -23,7 +23,7 @@ import mindspore as ms
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from mindspore import Tensor
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from mindspore import context
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from mindspore import dataset as de
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from mindspore.communication.management import init
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from mindspore.communication.management import init, get_rank
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from mindspore.nn.loss import SoftmaxCrossEntropyWithLogits
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from mindspore.nn.metrics import Accuracy
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from mindspore.nn.optim.adam import Adam
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@ -101,21 +101,30 @@ def train():
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target = config.device_target
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ckpt_save_dir = config.save_checkpoint_path
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# init context
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device_id = get_device_id()
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rank_id = get_rank_id()
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rank_size = get_device_num()
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run_distribute = rank_size > 1
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context.set_context(mode=context.GRAPH_MODE,
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device_target=target,
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device_id=device_id, save_graphs=False)
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save_graphs=False)
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rank_size = get_device_num()
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run_distribute = rank_size > 1
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device_id = get_device_id()
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if target == "Ascend":
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# init context
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rank_id = get_rank_id()
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context.set_context(device_id=device_id)
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if run_distribute:
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context.set_auto_parallel_context(device_num=rank_size, parallel_mode=ParallelMode.DATA_PARALLEL)
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init()
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elif target == "GPU":
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rank_id = 0
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if run_distribute:
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context.set_auto_parallel_context(device_num=rank_size, parallel_mode=ParallelMode.DATA_PARALLEL)
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init()
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rank_id = get_rank()
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print("train args: ", config, "\ncfg: ", config,
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"\nparallel args: rank_id {}, device_id {}, rank_size {}".format(rank_id, device_id, rank_size))
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if run_distribute:
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context.set_auto_parallel_context(device_num=rank_size, parallel_mode=ParallelMode.DATA_PARALLEL)
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init()
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config.rank_save_ckpt_flag = 0
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if config.is_save_on_master:
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@ -130,6 +139,8 @@ def train():
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".mindrecord0", config=config, dataset_name=dataset_name)
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step_size = dataset.get_dataset_size()
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print("step_size ", step_size, flush=True)
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# define net
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net = CNNDirectionModel([3, 64, 48, 48, 64], [64, 48, 48, 64, 64], [256, 64], [64, 512])
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