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Add stem_bias option to MNV5. Resolve the norm layer so can pass string. #2538

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Merged
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Jul 6, 2025
Merged

Add stem_bias option to MNV5. Resolve the norm layer so can pass string. #2538

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30 changes: 24 additions & 6 deletions timm/models/mobilenetv5.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,13 +7,25 @@

from timm.data import IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
from timm.layers import (
SelectAdaptivePool2d, Linear, LayerType, PadType, RmsNorm2d, ConvNormAct, create_conv2d, get_norm_act_layer,
to_2tuple
SelectAdaptivePool2d,
Linear,
LayerType,
RmsNorm2d,
ConvNormAct,
create_conv2d,
get_norm_layer,
get_norm_act_layer,
to_2tuple,
)
from ._builder import build_model_with_cfg
from ._efficientnet_blocks import SqueezeExcite, UniversalInvertedResidual
from ._efficientnet_builder import BlockArgs, EfficientNetBuilder, decode_arch_def, efficientnet_init_weights, \
round_channels, resolve_act_layer
from ._efficientnet_builder import (
BlockArgs,
EfficientNetBuilder,
decode_arch_def,
efficientnet_init_weights,
round_channels,
)
from ._features import feature_take_indices
from ._features_fx import register_notrace_module
from ._manipulate import checkpoint_seq, checkpoint
Expand Down Expand Up @@ -115,6 +127,7 @@ def __init__(
num_classes: int = 1000,
in_chans: int = 3,
stem_size: int = 16,
stem_bias: bool = False,
fix_stem: bool = False,
num_features: int = 2048,
pad_type: str = '',
Expand Down Expand Up @@ -155,7 +168,7 @@ def __init__(
"""
super().__init__()
act_layer = act_layer or nn.GELU
norm_layer = norm_layer or RmsNorm2d
norm_layer = get_norm_layer(norm_layer) or RmsNorm2d
norm_act_layer = get_norm_act_layer(norm_layer, act_layer)
se_layer = se_layer or SqueezeExcite
self.num_classes = num_classes
Expand All @@ -173,6 +186,7 @@ def __init__(
kernel_size=3,
stride=2,
padding=pad_type,
bias=stem_bias,
norm_layer=norm_layer,
act_layer=act_layer,
)
Expand Down Expand Up @@ -396,6 +410,7 @@ def __init__(
block_args: BlockArgs,
in_chans: int = 3,
stem_size: int = 64,
stem_bias: bool = False,
fix_stem: bool = False,
pad_type: str = '',
msfa_indices: Sequence[int] = (-2, -1),
Expand All @@ -412,7 +427,7 @@ def __init__(
):
super().__init__()
act_layer = act_layer or nn.GELU
norm_layer = norm_layer or RmsNorm2d
norm_layer = get_norm_layer(norm_layer) or RmsNorm2d
se_layer = se_layer or SqueezeExcite
self.num_classes = 0 # Exists to satisfy ._hub module APIs.
self.drop_rate = drop_rate
Expand All @@ -427,6 +442,7 @@ def __init__(
kernel_size=3,
stride=2,
padding=pad_type,
bias=stem_bias,
norm_layer=norm_layer,
act_layer=act_layer,
)
Expand Down Expand Up @@ -786,12 +802,14 @@ def _cfg(url: str = '', **kwargs):
# encoder-only configs
'mobilenetv5_300m_enc': _cfg(
#hf_hub_id='timm/',
mean=(0., 0., 0.), std=(1., 1., 1.),
input_size=(3, 768, 768),
num_classes=0),

# WIP classification configs for testing
'mobilenetv5_300m': _cfg(
# hf_hub_id='timm/',
mean=(0., 0., 0.), std=(1., 1., 1.),
input_size=(3, 768, 768),
num_classes=0),
'mobilenetv5_base.untrained': _cfg(
Expand Down