# Train params
lr: 0.0001
lr_backbone: 0.00001
lr_drop: 200
weight_decay: 0.0001
clip_max_norm: 0.1
batch_size: 4
start_epoch: 0
epochs: 300
save_num_ckpt: 10
resume: ""
pretrained: "/home/w30005666/ckpt/ms_resnet_50.ckpt"
seed: 42

# Context
device_id: 0
device_target: "Ascend"
context_mode: "pynative"
coco_path: "/opt/npu/data/coco2017"
output_dir: "./outputs"
mindrecord_dir: "/home/w30005666/coco_mindrecord/"
clip_max_norm: 0.1
dropout: 0.1

# Loss
aux_loss: True

# Dataset parameters
dataset_file: 'coco'
coco_path: ""
train_data_type: "train2017"
val_data_type: 'val2017'
num_classes: 91
output_dir: ''
num_parallel_workers: 8
python_multiprocessing: False

max_size: 960
flip_ratio: 0.5

# Backbone
backbone: "resnet50"

# Transformer
enc_layers: 6
dec_layers: 6
dim_feedforward: 2048
hidden_dim: 256
dropout: 0.1
nheads: 8
num_queries: 100
pre_norm: False

# Matcher
set_cost_class: 1
set_cost_bbox: 5
set_cost_giou: 2

# Loss coefficients
dice_loss_coef: 1
bbox_loss_coef: 5
giou_loss_coef: 2
eos_coef: 0.1

# Distributed switch
distributed: 1