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affnet_config.py
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affnet_config.py
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# --------------------------------------------------------
# Copyright (c) 2023 Microsoft
# Licensed under The MIT License
# --------------------------------------------------------
from typing import Dict
import logger
def get_configuration(opts) -> Dict:
mode = getattr(opts, "model.classification.affnet.mode", "xx_small")
if mode is None:
logger.error("Please specify mode")
logger.info("model mode is：" + mode)
head_dim = getattr(opts, "model.classification.affnet.head_dim", None)
num_heads = getattr(opts, "model.classification.affnet.number_heads", 4)
if head_dim is not None:
if num_heads is not None:
logger.error(
"--model.classification.affnet.head-dim and --model.classification.affnet.number-heads "
"are mutually exclusive."
)
elif num_heads is not None:
if head_dim is not None:
logger.error(
"--model.classification.affnet.head-dim and --model.classification.affnet.number-heads "
"are mutually exclusive."
)
mode = mode.lower()
if mode == "xx_small":
mv2_exp_mult = 2
config = {
"layer1": {
"out_channels": 32,
"expand_ratio": mv2_exp_mult,
"num_blocks": 1,
"stride": 1,
"block_type": "mv2",
},
"layer2": {
"out_channels": 48,
"expand_ratio": mv2_exp_mult,
"num_blocks": 3,
"stride": 2,
"block_type": "mv2",
},
"layer3": { # 28x28
"out_channels": 64,
"transformer_channels": 64,
"ffn_dim": 128,
"transformer_blocks": 2,
"patch_h": 2, # 8,
"patch_w": 2, # 8,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer4": { # 14x14
"out_channels": 104,
"transformer_channels": 104,
"ffn_dim": 208,
"transformer_blocks": 4,
"patch_h": 2, # 4,
"patch_w": 2, # 4,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer5": { # 7x7
"out_channels": 144,
"transformer_channels": 144,
"ffn_dim": 288,
"transformer_blocks": 3,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"last_layer_exp_factor": 4,
}
elif mode == "x_small":
mv2_exp_mult = 4
config = {
"layer1": {
"out_channels": 32,
"expand_ratio": mv2_exp_mult,
"num_blocks": 1,
"stride": 1,
"block_type": "mv2",
},
"layer2": {
"out_channels": 48,
"expand_ratio": mv2_exp_mult,
"num_blocks": 3,
"stride": 2,
"block_type": "mv2",
},
"layer3": { # 28x28
"out_channels": 96,
"transformer_channels": 96,
"ffn_dim": 192,
"transformer_blocks": 2,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer4": { # 14x14
"out_channels": 160,
"transformer_channels": 160,
"ffn_dim": 320,
"transformer_blocks": 4,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer5": { # 7x7
"out_channels": 192,
"transformer_channels": 192,
"ffn_dim": 384,
"transformer_blocks": 3,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"last_layer_exp_factor": 4,
}
elif mode == "small":
mv2_exp_mult = 4
config = {
"layer1": {
"out_channels": 32,
"expand_ratio": mv2_exp_mult,
"num_blocks": 1,
"stride": 1,
"block_type": "mv2",
},
"layer2": {
"out_channels": 64,
"expand_ratio": mv2_exp_mult,
"num_blocks": 3,
"stride": 2,
"block_type": "mv2",
},
"layer3": { # 28x28
"out_channels": 128,
"transformer_channels": 128,
"ffn_dim": 256,
"transformer_blocks": 2,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer4": { # 14x14
"out_channels": 256,
"transformer_channels": 256,
"ffn_dim": 512,
"transformer_blocks": 4,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer5": { # 7x7
"out_channels": 320,
"transformer_channels": 320,
"ffn_dim": 640,
"transformer_blocks": 3,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"last_layer_exp_factor": 4,
}
elif mode == "base":
mv2_exp_mult = 4
config = {
"layer1": {
"out_channels": 64,
"expand_ratio": mv2_exp_mult,
"num_blocks": 1,
"stride": 1,
"block_type": "mv2",
},
"layer2": {
"out_channels": 128,
"expand_ratio": mv2_exp_mult,
"num_blocks": 3,
"stride": 2,
"block_type": "mv2",
},
"layer3": { # 28x28
"out_channels": 256,
"transformer_channels": 256,
"ffn_dim": 512,
"transformer_blocks": 2,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer4": { # 14x14
"out_channels": 512,
"transformer_channels": 512,
"ffn_dim": 1024,
"transformer_blocks": 4,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
"no_fuse": True
},
"layer5": { # 7x7
"out_channels": 640,
"transformer_channels": 640,
"ffn_dim": 1280,
"transformer_blocks": 3,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
"no_fuse": True
},
"last_layer_exp_factor": 4,
}
elif mode == "large":
mv2_exp_mult = 4
config = {
"layer1": {
"out_channels": 64,
"expand_ratio": mv2_exp_mult,
"num_blocks": 2,
"stride": 1,
"block_type": "mv2",
},
"layer2": {
"out_channels": 128,
"expand_ratio": mv2_exp_mult,
"num_blocks": 6,
"stride": 2,
"block_type": "mv2",
},
"layer3": { # 28x28
"out_channels": 256,
"transformer_channels": 256,
"ffn_dim": 512,
"transformer_blocks": 4,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
},
"layer4": { # 14x14
"out_channels": 512,
"transformer_channels": 512,
"ffn_dim": 1024,
"transformer_blocks": 18,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
"no_fuse": True
},
"layer5": { # 7x7
"out_channels": 768,
"transformer_channels": 768,
"ffn_dim": 1536,
"transformer_blocks": 6,
"patch_h": 2,
"patch_w": 2,
"stride": 2,
"mv_expand_ratio": mv2_exp_mult,
"head_dim": head_dim,
"num_heads": num_heads,
"block_type": "aff_block",
"no_fuse": True
},
"last_layer_exp_factor": 4,
}
else:
raise NotImplementedError
return config