superIX / swin2_mose /weights /config-70.yml
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swin2mose (#1)
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dataset:
root_path: data/sen2venus
stats:
use_minmax: true
tensor_05m_b2b3b4b8: {
mean: [444.21923828125, 715.9031372070312, 813.4345703125, 2604.867919921875],
std: [279.85552978515625, 385.3569641113281, 648.458984375, 796.9918212890625],
min: [-1025.0, -3112.0, -5122.0, -3851.0],
max: [14748.0, 14960.0, 16472.0, 16109.0]
}
tensor_10m_b2b3b4b8: {
mean: [443.78643798828125, 715.4202270507812, 813.0512084960938, 2602.813232421875],
std: [283.89276123046875, 389.26361083984375, 651.094970703125, 811.5682373046875],
min: [-848.0, -902.0, -946.0, -323.0],
max: [19684.0, 17982.0, 17064.0, 15958.0]
}
hr_name: tensor_05m_b2b3b4b8
lr_name: tensor_10m_b2b3b4b8
collate_fn: mods.v3.collate_fn
denorm: mods.v3.uncollate_fn
printable: mods.v3.printable
super_res: {
version: 'v2',
model: {
upscale: 2,
use_lepe: true,
use_cpb_bias: false,
use_rpe_bias: true,
mlp_ratio: 1,
MoE_config: {
k: 2,
num_experts: 8,
with_noise: false,
with_smart_merger: v1,
},
depths: [6, 6, 6, 6],
embed_dim: 90,
img_range: 1.,
img_size: 64,
in_chans: 4,
num_heads: [6, 6, 6, 6],
resi_connection: 1conv,
upsampler: pixelshuffledirect,
window_size: 16,
}
}