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Add cs3darknet_x, cs3sedarknet_l, and darknetaa53 weights from TPU sessions. Move SE btwn conv1 & conv2 in DarkBlock. Improve SE/attn handling in Csp/DarkNet. Fix leaky_relu bug on older csp models.

fix_tests
Ross Wightman 2022-07-15 16:53:51 -07:00
parent 4283c0c478
commit 05313940e2
1 changed files with 65 additions and 31 deletions
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96
timm/models/cspnet.py
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@ -23,7 +23,7 @@ import torch.nn.functional as F
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from .helpers import build_model_with_cfg, named_apply, MATCH_PREV_GROUP
from .layers import ClassifierHead, ConvNormAct, ConvNormActAa, DropPath, create_attn, create_act_layer, make_divisible
from .layers import ClassifierHead, ConvNormAct, ConvNormActAa, DropPath, get_attn, create_act_layer, make_divisible
from .registry import register_model
@ -57,9 +57,10 @@ default_cfgs = {
'sedarknet21': _cfg(url=''),
'darknet53': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/darknet53_256_c2ns-3aeff817.pth',
interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=1.0,
),
'darknetaa53': _cfg(url=''),
interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=1.0),
'darknetaa53': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/darknetaa53_c2ns-5c28ec8a.pth',
test_input_size=(3, 288, 288), test_crop_pct=1.0),
'cs3darknet_s': _cfg(
url='', interpolation='bicubic'),
@ -71,7 +72,8 @@ default_cfgs = {
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3darknet_l_c2ns-16220c5d.pth',
interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=0.95),
'cs3darknet_x': _cfg(
url=''),
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3darknet_x_c2ns-4e4490aa.pth',
interpolation='bicubic', crop_pct=0.95, test_input_size=(3, 288, 288), test_crop_pct=1.0),
'cs3darknet_focus_s': _cfg(
url='', interpolation='bicubic'),
@ -84,6 +86,10 @@ default_cfgs = {
'cs3darknet_focus_x': _cfg(
url='', interpolation='bicubic'),
'cs3sedarknet_l': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tpu-weights/cs3sedarknet_l_c2ns-e8d1dc13.pth',
interpolation='bicubic', test_input_size=(3, 288, 288), test_crop_pct=0.95),
'cs3sedarknet_xdw': _cfg(
url='', interpolation='bicubic'),
}
@ -119,6 +125,7 @@ class CspStagesCfg:
bottle_ratio: Union[float, Tuple[float, ...]] = 1. # bottleneck-ratio of blocks in stage
avg_down: Union[bool, Tuple[bool, ...]] = False
attn_layer: Optional[Union[str, Tuple[str, ...]]] = None
attn_kwargs: Optional[Union[Dict, Tuple[Dict]]] = None
stage_type: Union[str, Tuple[str]] = 'csp' # stage type ('csp', 'cs2', 'dark')
block_type: Union[str, Tuple[str]] = 'bottle' # blocks type for stages ('bottle', 'dark')
@ -136,6 +143,7 @@ class CspStagesCfg:
self.bottle_ratio = _pad_arg(self.bottle_ratio, n)
self.avg_down = _pad_arg(self.avg_down, n)
self.attn_layer = _pad_arg(self.attn_layer, n)
self.attn_kwargs = _pad_arg(self.attn_kwargs, n)
self.stage_type = _pad_arg(self.stage_type, n)
self.block_type = _pad_arg(self.block_type, n)
@ -149,12 +157,20 @@ class CspModelCfg:
stem: CspStemCfg
stages: CspStagesCfg
zero_init_last: bool = True # zero init last weight (usually bn) in residual path
act_layer: str = 'relu'
act_layer: str = 'leaky_relu'
norm_layer: str = 'batchnorm'
aa_layer: Optional[str] = None # FIXME support string factory for this
def _cs3darknet_cfg(width_multiplier=1.0, depth_multiplier=1.0, avg_down=False, act_layer='silu', focus=False):
def _cs3darknet_cfg(
width_multiplier=1.0,
depth_multiplier=1.0,
avg_down=False,
act_layer='silu',
focus=False,
attn_layer=None,
attn_kwargs=None,
):
if focus:
stem_cfg = CspStemCfg(
out_chs=make_divisible(64 * width_multiplier),
@ -172,6 +188,8 @@ def _cs3darknet_cfg(width_multiplier=1.0, depth_multiplier=1.0, avg_down=False,
bottle_ratio=1.,
block_ratio=0.5,
avg_down=avg_down,
attn_layer=attn_layer,
attn_kwargs=attn_kwargs,
stage_type='cs3',
block_type='dark',
),
@ -201,7 +219,7 @@ model_cfgs = dict(
bottle_ratio=0.5,
block_ratio=1.,
cross_linear=True,
)
),
),
cspresnet50w=CspModelCfg(
stem=CspStemCfg(out_chs=(32, 32, 64), kernel_size=3, stride=4, pool='max'),
@ -213,7 +231,7 @@ model_cfgs = dict(
bottle_ratio=0.25,
block_ratio=0.5,
cross_linear=True,
)
),
),
cspresnext50=CspModelCfg(
stem=CspStemCfg(out_chs=64, kernel_size=7, stride=4, pool='max'),
@ -226,7 +244,7 @@ model_cfgs = dict(
bottle_ratio=1.,
block_ratio=0.5,
cross_linear=True,
)
),
),
cspdarknet53=CspModelCfg(
stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''),
@ -240,7 +258,6 @@ model_cfgs = dict(
down_growth=True,
block_type='dark',
),
act_layer='leaky_relu',
),
darknet17=CspModelCfg(
stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''),
@ -253,7 +270,6 @@ model_cfgs = dict(
stage_type='dark',
block_type='dark',
),
act_layer='leaky_relu',
),
darknet21=CspModelCfg(
stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''),
@ -267,7 +283,6 @@ model_cfgs = dict(
block_type='dark',
),
act_layer='leaky_relu',
),
sedarknet21=CspModelCfg(
stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''),
@ -282,7 +297,6 @@ model_cfgs = dict(
block_type='dark',
),
act_layer='leaky_relu',
),
darknet53=CspModelCfg(
stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''),
@ -295,7 +309,6 @@ model_cfgs = dict(
stage_type='dark',
block_type='dark',
),
act_layer='leaky_relu',
),
darknetaa53=CspModelCfg(
stem=CspStemCfg(out_chs=32, kernel_size=3, stride=1, pool=''),
@ -309,7 +322,6 @@ model_cfgs = dict(
stage_type='dark',
block_type='dark',
),
act_layer='leaky_relu',
),
cs3darknet_s=_cs3darknet_cfg(width_multiplier=0.5, depth_multiplier=0.5),
@ -322,6 +334,8 @@ model_cfgs = dict(
cs3darknet_focus_l=_cs3darknet_cfg(focus=True),
cs3darknet_focus_x=_cs3darknet_cfg(width_multiplier=1.25, depth_multiplier=1.33, focus=True),
cs3sedarknet_l=_cs3darknet_cfg(attn_layer='se', attn_kwargs=dict(rd_ratio=.25)),
cs3sedarknet_xdw=CspModelCfg(
stem=CspStemCfg(out_chs=(32, 64), kernel_size=3, stride=2, pool=''),
stages=CspStagesCfg(
@ -333,6 +347,7 @@ model_cfgs = dict(
block_ratio=0.5,
attn_layer='se',
),
act_layer='silu',
),
)
@ -359,14 +374,16 @@ class BottleneckBlock(nn.Module):
super(BottleneckBlock, self).__init__()
mid_chs = int(round(out_chs * bottle_ratio))
ckwargs = dict(act_layer=act_layer, norm_layer=norm_layer)
attn_last = attn_layer is not None and attn_last
attn_first = attn_layer is not None and not attn_last
self.conv1 = ConvNormAct(in_chs, mid_chs, kernel_size=1, **ckwargs)
self.conv2 = ConvNormActAa(
mid_chs, mid_chs, kernel_size=3, dilation=dilation, groups=groups,
aa_layer=aa_layer, drop_layer=drop_block, **ckwargs)
self.attn2 = create_attn(attn_layer, channels=mid_chs) if not attn_last else None
self.attn2 = attn_layer(mid_chs, act_layer=act_layer) if attn_first else nn.Identity()
self.conv3 = ConvNormAct(mid_chs, out_chs, kernel_size=1, apply_act=False, **ckwargs)
self.attn3 = create_attn(attn_layer, channels=out_chs) if attn_last else None
self.attn3 = attn_layer(out_chs, act_layer=act_layer) if attn_last else nn.Identity()
self.drop_path = DropPath(drop_path) if drop_path else nn.Identity()
self.act3 = create_act_layer(act_layer)
@ -377,11 +394,9 @@ class BottleneckBlock(nn.Module):
shortcut = x
x = self.conv1(x)
x = self.conv2(x)
if self.attn2 is not None:
x = self.attn2(x)
x = self.attn2(x)
x = self.conv3(x)
if self.attn3 is not None:
x = self.attn3(x)
x = self.attn3(x)
x = self.drop_path(x) + shortcut
# FIXME partial shortcut needed if first block handled as per original, not used for my current impl
#x[:, :shortcut.size(1)] += shortcut
@ -410,11 +425,12 @@ class DarkBlock(nn.Module):
super(DarkBlock, self).__init__()
mid_chs = int(round(out_chs * bottle_ratio))
ckwargs = dict(act_layer=act_layer, norm_layer=norm_layer)
self.conv1 = ConvNormAct(in_chs, mid_chs, kernel_size=1, **ckwargs)
self.attn = attn_layer(mid_chs, act_layer=act_layer) if attn_layer is not None else nn.Identity()
self.conv2 = ConvNormActAa(
mid_chs, out_chs, kernel_size=3, dilation=dilation, groups=groups,
aa_layer=aa_layer, drop_layer=drop_block, **ckwargs)
self.attn = create_attn(attn_layer, channels=out_chs, act_layer=act_layer)
self.drop_path = DropPath(drop_path) if drop_path else nn.Identity()
def zero_init_last(self):
@ -423,9 +439,8 @@ class DarkBlock(nn.Module):
def forward(self, x):
shortcut = x
x = self.conv1(x)
x = self.attn(x)
x = self.conv2(x)
if self.attn is not None:
x = self.attn(x)
x = self.drop_path(x) + shortcut
return x
@ -688,7 +703,8 @@ def create_csp_stem(
return stem, feature_info
def _get_stage_fn(stage_type: str, stage_args):
def _get_stage_fn(stage_args):
stage_type = stage_args.pop('stage_type')
assert stage_type in ('dark', 'csp', 'cs3')
if stage_type == 'dark':
stage_args.pop('expand_ratio', None)
@ -702,14 +718,25 @@ def _get_stage_fn(stage_type: str, stage_args):
return stage_fn, stage_args
def _get_block_fn(stage_type: str, stage_args):
assert stage_type in ('dark', 'bottle')
if stage_type == 'dark':
def _get_block_fn(stage_args):
block_type = stage_args.pop('block_type')
assert block_type in ('dark', 'bottle')
if block_type == 'dark':
return DarkBlock, stage_args
else:
return BottleneckBlock, stage_args
def _get_attn_fn(stage_args):
attn_layer = stage_args.pop('attn_layer')
attn_kwargs = stage_args.pop('attn_kwargs', None) or {}
if attn_layer is not None:
attn_layer = get_attn(attn_layer)
if attn_kwargs:
attn_layer = partial(attn_layer, **attn_kwargs)
return attn_layer, stage_args
def create_csp_stages(
cfg: CspModelCfg,
drop_path_rate: float,
@ -734,8 +761,9 @@ def create_csp_stages(
feature_info = []
stages = []
for stage_idx, stage_args in enumerate(stage_args):
stage_fn, stage_args = _get_stage_fn(stage_args.pop('stage_type'), stage_args)
block_fn, stage_args = _get_block_fn(stage_args.pop('block_type'), stage_args)
stage_fn, stage_args = _get_stage_fn(stage_args)
block_fn, stage_args = _get_block_fn(stage_args)
attn_fn, stage_args = _get_attn_fn(stage_args)
stride = stage_args.pop('stride')
if stride != 1 and prev_feat:
feature_info.append(prev_feat)
@ -752,6 +780,7 @@ def create_csp_stages(
first_dilation=first_dilation,
dilation=dilation,
block_fn=block_fn,
attn_layer=attn_fn, # will be passed through stage as block_kwargs
**block_kwargs,
)]
prev_chs = stage_args['out_chs']
@ -968,6 +997,11 @@ def cs3darknet_focus_x(pretrained=False, **kwargs):
return _create_cspnet('cs3darknet_focus_x', pretrained=pretrained, **kwargs)
@register_model
def cs3sedarknet_l(pretrained=False, **kwargs):
return _create_cspnet('cs3sedarknet_l', pretrained=pretrained, **kwargs)
@register_model
def cs3sedarknet_xdw(pretrained=False, **kwargs):
return _create_cspnet('cs3sedarknet_xdw', pretrained=pretrained, **kwargs)