mobilenet_v1_050(pretrained: bool = False, overrides: object = {})MobileNet-v1 backbone at width multiplier .
Builds a MobileNetV1 with every channel count multiplied
by 0.5 — approximately 1.3M parameters. Howard et al., 2017
report 63.7% ImageNet-1k top-1 accuracy with this configuration
(Table 7), at roughly 27% of the FLOPs of the full-width model.
Model Size
Parameters
pretrainedbool= FalseReserved for future pretrained-weight loading. Currently
ignored.
**overridesobject= {}Keyword overrides forwarded into
MobileNetV1Config.Returns
MobileNetV1Backbone with the MobileNet-v1 ()
configuration applied (or with overrides merged on top
of it).
Notes
See Howard et al., "MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications", arXiv:1704.04861, 2017, Table 7.
Examples
>>> import lucid
>>> from lucid.models.vision.mobilenet import mobilenet_v1_050
>>> model = mobilenet_v1_050()
>>> x = lucid.randn(1, 3, 224, 224)
>>> out = model(x)
>>> out.last_hidden_state.shape
(1, 512, 1, 1)