DeepLearningExamples/TensorFlow/Classification/ConvNets/resnext101-32x4d/training/DGX2_RNxt101-32x4d_AMP_90E.sh
2020-06-27 09:24:41 +02:00

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#!/bin/bash
# Copyright (c) 2019 NVIDIA CORPORATION. All rights reserved.
#
# 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.
WORKSPACE=${1:-"/workspace/rn50v15_tf"}
DATA_DIR=${2:-"/data"}
OTHER=${@:3}
if [[ ! -z "${BIND_TO_SOCKET}" ]]; then
BIND_TO_SOCKET="--bind-to socket"
fi
mpiexec --allow-run-as-root ${BIND_TO_SOCKET} -np 16 python3 main.py --arch=resnext101-32x4d \
--mode=train_and_evaluate --iter_unit=epoch --num_iter=90 \
--batch_size=128 --warmup_steps=100 --use_cosine --label_smoothing 0.1 \
--lr_init=0.256 --lr_warmup_epochs=8 --momentum=0.875 --weight_decay=6.103515625e-05 \
--use_tf_amp --use_static_loss_scaling --loss_scale 128 \
--data_dir=${DATA_DIR}/tfrecords --data_idx_dir=${DATA_DIR}/dali_idx \
--results_dir=${WORKSPACE}/results --weight_init=fan_in ${OTHER}