mindspore/model_zoo/research/cv/FaceRecognition/beta_config.yaml

# 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: "Ascend"
enable_profiling: False

# ==============================================================================
# Training options
train_stage: "beta"
is_distributed: 1

# dataset related
data_dir: "/cache/data/face_recognition_dataset/train_dataset/"
num_classes: 1
per_batch_size: 192
need_modelarts_dataset_unzip: True

# network structure related
backbone: "r100"
use_se: 0
emb_size: 256
act_type: "relu"
fp16: 1
pre_bn: 0
inference: 0
use_drop: 1
nc_16: 1

# loss related
margin_a: 1.0
margin_b: 0.2
margin_m: 0.3
margin_s: 64

# optimizer related
lr: 0.04
lr_scale: 1
lr_epochs: "8,14,18"
weight_decay: 0.0002
momentum: 0.9
max_epoch: 20
pretrained: "your_pretrained_model"
warmup_epochs: 2

# distributed parameter
local_rank: 0
world_size: 1
model_parallel: 0

# logging related
log_interval: 100
ckpt_path: "outputs"
max_ckpts: -1
dynamic_init_loss_scale: 65536
ckpt_steps: 1000

---

# 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'

train_stage: "Train stage, base or beta"
is_distributed: "If multi device"