crslab.model.recommendation.textcnn package

Submodules

TextCNN

References

Kim, Yoon. “Convolutional Neural Networks for Sentence Classification.” in EMNLP 2014.

class crslab.model.recommendation.textcnn.textcnn.TextCNNModel(opt, device, vocab, side_data)[source]

Bases: crslab.model.base.BaseModel

movie_num

A integer indicating the number of items.

num_filters

A string indicating the number of filter in CNN.

embed

A integer indicating the size of embedding layer.

filter_sizes

A string indicating the size of filter in CNN.

dropout

A float indicating the dropout rate.

Parameters

  • opt (dict) – A dictionary record the hyper parameters.

  • device (torch.device) – A variable indicating which device to place the data and model.

  • vocab (dict) – A dictionary record the vocabulary information.

  • side_data (dict) – A dictionary record the side data.

build_model()[source]

build model

conv_and_pool(x, conv)[source]
forward(batch, mode)[source]

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

Module contents