# 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: "./output"
device_target: "GPU"

network: "EDSR4GhostSRMs"  # EDSR_mindspore / EDSR_GhostSR_ms

# ==============================================================================
ckpt_save_dir: "./ckpt/"

self_ensemble: True
save_sr: True

# dataset options
dataset_name: "benchmark"
scale: 2
need_unzip_in_modelarts: False

# net options
pre_trained: ""
rgb_range: 255
rgb_mean: [ 0.4488, 0.4371, 0.4040 ]
rgb_std: [ 1.0, 1.0, 1.0 ]
n_colors: 3
n_feats: 256
kernel_size: 3
n_resblocks: 32
res_scale: 0.1

---
# helper

enable_modelarts: "set True if run in modelarts, default: False"
# Url for modelarts
data_url: "modelarts data path"
train_url: "modelarts code path"
checkpoint_url: "modelarts checkpoint save path"
# Path for local
data_path: "local data path, data will be download from 'data_url', default: /cache/data"
output_path: "local output path, checkpoint will be upload to 'checkpoint_url', default: /cache/train"
device_target: "choice from ['Ascend'], default: Ascend"

# ==============================================================================
# train options
ckpt_save_dir: "the relative path to save checkpoint, root path is 'output_path', defalue: ./ckpt/"

self_ensemble: "set True if wanna do self-ensemble while evaluating, defalue: True"
save_sr: "set True if wanna save sr and hr image while evaluating, defalue: True"

# dataset options
dataset_name: "dataset name, defalue: DIV2K"
scale: "scale for super resolution reconstruction, choice from [2,3,4], defalue: 4"
need_unzip_in_modelarts: "set True if wanna unzip data after download data from s3, defalue: False"
need_unzip_files: "list of zip files to unzip, only work while 'need_unzip_in_modelarts'=True"

# net options
pre_trained: "load pre-trained model, x2/x3/x4 models can be loaded for each other, choice from [[S3_ABS_PATH], [RELATIVE_PATH below 'output_path'], [LOCAL_ABS_PATH], ''], defalue: ''"
rgb_range: "pix value range, defalue: 255"
rgb_mean: "rgb mean, defalue: [0.4488, 0.4371, 0.4040]"
rgb_std: "rgb standard deviation, defalue: [1.0, 1.0, 1.0]"
n_colors: "the number of RGB image channels, defalue: 3"
n_feats: "the number of output features for each Conv2d, defalue: 256"
kernel_size: "kernel size for Conv2d, defalue: 3"
n_resblocks: "the number of resblocks, defalue: 32"
res_scale: "zoom scale of res branch, defalue: 0.1"