_getitem_ ( name : str ) → Any ¶Įquivalent to getattr. Methods _call_ ( * args : Any, ** kwargs : Any ) → Any ¶Ĭall self as a function. This corresponds to LeCunUniform in ChainerĪvailable_layers ( list of str) – The list of available layer names “xavier” type without variance_norm parameter, the weights are Note that, in Caffe, when weight_filler is specified as If the argument is specified as None, all the parametersĪre not initialized by the pre-trained model, but the defaultĬ(scale=1.0). $HOME/.chainer/dataset unless you specify another valueĪs a environment variable. On $CHAINER_DATASET_ROOT/pfnet/chainer/models directory, Note that in this case the converted chainer model is stored
It automatically downloads the caffemodel from the internet. Pretrained_model ( str) – the destination of the pre-trained Other models since they are more accurate than GoogLeNet. Want an off-the-shelf classifier, we recommend that you use ResNet50 or Large batch size, GoogLeNet may be useful. Network based on a model pre-trained by Imagenet and need to train it with With modern architectures such as ResNet. Lightweight and requires small memory footprint during training compared GoogLeNet, which is also called Inception-v1, is an architecture ofĬonvolutional neural network proposed in 2014. Please use convert_caffemodel_to_npz classmethod instead. Model that can be specified in the constructor, If you want to manually convert the pre-trained caffemodel to a chainer Vector per image, or fine-tune the model on a different dataset. This model would be useful when you want to extract a semantic feature npz file in the constructor, this chain model automatically When you specify the path of the pre-trained chainer model serialized asĪ. GoogLeNet ( pretrained_model = 'auto' ) ¶Ī pre-trained GoogLeNet model provided by BVLC. Distributed Deep Learning with ChainerMNĬ ¶ class chainer.links.Static Subgraph Optimizations: Design Notes.Activation/loss/normalization functions with parameters.
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