Task: detection
Genome: [[[1, 1], [1, 0]], [[5, 2], [9, 2]], [[3, 1], [3, 1]], [[5, 3], [7, 4]], [[8, 4], [7, 5]]]
Architecture: AdapterGenotype(ops=[('skip_connect', 1), ('skip_connect', 0), ('dil_conv_3x3', 2), ('spatial_attention', 2), ('sep_conv_3x3', 1), ('sep_conv_3x3', 1), ('dil_conv_3x3', 3), ('max_pool_3x3', 4), ('channel_attention', 4), ('max_pool_3x3', 5)], ops_concat=[6])
Params: 4.73257 MB
Forward FLOPs: 2987.487072 M
Training FLOPs: 8726.978784 M [thop]
Training Efficiency: 2.6% savings
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Epoch  | Train Loss | Valid mAP  | FLOPs     
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0      | 4.4535     | 48.7687    | 8726.98   
