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# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless you know exactly what you are doing)
enable_modelarts: False
# Url for modelarts
data_url: ""
train_url: ""
checkpoint_url: ""
# Path for local
data_path: "/cache/data"
output_path: "/cache/train"
load_path: "/cache/checkpoint_path"
device_target: "CPU"
enable_profiling: False
# ==============================================================================
# Training options
# distributed parameter
is_distributed: 0
local_rank: 0
world_size: 1
# test weight
weight: 'your_test_model'
test_dir: '/cache/data/face_recognition_dataset/'
need_modelarts_dataset_unzip: True
# model define
backbone: "r100"
use_se: 0
emb_size: 256
act_type: "relu"
pre_bn: 0
inference: 1
use_drop: 0
# test and dis batch size
test_batch_size: 128
dis_batch_size: 512
# log
log_interval: 100
ckpt_path: "outputs/models"
# test and dis image list
test_img_predix: ""
test_img_list: ""
dis_img_predix: ""
dis_img_list: ""
# export option
batch_size: 16
file_name: "fr.midnir"
file_format: "MINDIR"
export_pre_bn: 0
export_inference: 1
export_use_se: 0
export_emb_size: 256
export_act_type: "relu"
export_backbone: "r100"
export_use_drop: 0
head: "0"
---
# Help description for each configuration
enable_modelarts: "Whether training on modelarts, default: False"
data_url: "Url for modelarts"
train_url: "Url for modelarts"
data_path: "The location of the input data."
output_path: "The location of the output file."
device_target: 'Target device type'
enable_profiling: 'Whether enable profiling while training, default: False'
# export option
batch_size: "batch size"
file_name: "file name"
file_format: "file format, choices in ['MINDIR', 'AIR']"
export_pre_bn: "1: bn-conv-bn-conv-bn, 0: conv-bn-conv-bn"
export_inference: "use inference backbone"
export_use_se: "use se block or not"
export_emb_size: "embedding size of the network"
export_act_type: "activation layer type"
export_backbone: "backbone network"
export_use_drop: "whether use dropout in network"
head: "head type, default is 0"
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