Mobilenet_v3

[Elwanda Menhennett]

Noteeach Keras Application expects a specific kind of input preprocessing.For MobileNet, call keras.applications.mobilenet.preprocess_inputon your inputs before passing them to the model.mobilenet.preprocess_input will scale input pixels between -1 and 1.

MobileNetV2 is very similar to the original MobileNet,except that it uses inverted residual blocks withbottlenecking features. It has a drastically lowerparameter count than the original MobileNet.MobileNets support any input size greaterthan 32 x 32, with larger image sizesoffering better performance.

Note: each Keras Application expects a specific kind of input preprocessing.For MobileNetV2, callkeras.applications.mobilenet_v2.preprocess_inputon your inputs before passing them to the model.mobilenet_v2.preprocess_input will scale input pixels between -1 and 1.

Note: each Keras Application expects a specific kind of input preprocessing.For MobileNetV3, by default input preprocessing is included as a part of themodel (as a Rescaling layer), and thuskeras.applications.mobilenet_v3.preprocess_input is actually apass-through function. In this use case, MobileNetV3 models expect theirinputs to be float tensors of pixels with values in the [0-255] range.At the same time, preprocessing as a part of the model (i.e. Rescalinglayer) can be disabled by setting include_preprocessing argument to False.With preprocessing disabled MobileNetV3 models expect their inputs to be floattensors of pixels with values in the [-1, 1] range.

I was basically running a model on kaggle and while

model = torchvision.model.resnet18(pretrained=true) works well, this

model = torchvision.models.mobilenet_v3_large(pretrained=True) generates an error:

AttributeError: module 'torchvision.models' has no attribute 'mobilenet_v3' This error does not occur with mobilenet_v2, but all the versions of mobilenet_v3. Am I doing something wrong here?

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