mobilenet_v1_025

→MobileNetV1

mobilenet_v1_025(pretrained: bool = False, overrides: object = {})

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MobileNet-v1 backbone at width multiplier $\alpha = 0.25$ .

Builds a MobileNetV1 with every channel count multiplied by 0.25 — approximately 0.5M parameters. Howard et al., 2017 report 50.6% ImageNet-1k top-1 accuracy with this configuration (Table 7) — the smallest MobileNet-v1 variant, targeted at extreme edge deployments where parameter count is the binding constraint.

Model Size

Parameters

pretrainedbool= False

Reserved for future pretrained-weight loading. Currently ignored.

**overridesobject= {}

Keyword overrides forwarded into MobileNetV1Config.

Returns

MobileNetV1

Backbone with the MobileNet-v1 ( $\alpha = 0.25$ ) 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_025
>>> model = mobilenet_v1_025()
>>> x = lucid.randn(1, 3, 224, 224)
>>> out = model(x)
>>> out.last_hidden_state.shape
(1, 256, 1, 1)

Used by 1

lucid.models.vision.mobilenet

>>> import lucid >>> from lucid.models.vision.mobilenet import mobilenet_v1_025 >>> model = mobilenet_v1_025() >>> x = lucid.randn(1, 3, 224, 224) >>> out = model(x) >>> out.last_hidden_state.shape (1, 256, 1, 1)