mobilenet_v2_075_cls

→MobileNetV2ForImageClassification

mobilenet_v2_075_cls(pretrained: bool = False, overrides: object = {})

source edit

MobileNet-v2 image classifier at width multiplier $\alpha = 0.75$ .

Builds a MobileNetV2ForImageClassification with the paper-cited 0.75-width topology — approximately 2.6M parameters and 69.8% ImageNet-1k top-1 in Sandler et al., 2018 (Table 4).

Model Size

Parameters

pretrainedbool= False

Reserved for future pretrained-weight loading. Currently ignored.

**overridesobject= {}

Keyword overrides forwarded into MobileNetV2Config.

Returns

MobileNetV2ForImageClassification

Classifier with the MobileNet-v2 ( $\alpha = 0.75$ ) configuration applied (or with overrides merged on top of it).

Notes

See Sandler et al., "MobileNetV2: Inverted Residuals and Linear Bottlenecks", CVPR 2018 (arXiv:1801.04381), Table 4.

Examples

>>> import lucid
>>> from lucid.models.vision.mobilenet_v2 import mobilenet_v2_075_cls
>>> model = mobilenet_v2_075_cls()
>>> x = lucid.randn(1, 3, 224, 224)
>>> out = model(x)
>>> out.logits.shape
(1, 1000)

Used by 1

lucid.models.vision.mobilenet_v2

>>> import lucid >>> from lucid.models.vision.mobilenet_v2 import mobilenet_v2_075_cls >>> model = mobilenet_v2_075_cls() >>> x = lucid.randn(1, 3, 224, 224) >>> out = model(x) >>> out.logits.shape (1, 1000)