Welcome to DeepClassifier’s documentation!¶
DeepClassifier is a python package based on pytorch, which is easy-use and general for text classification task.🤩
QuickStart¶
I will show you that how to install DeepClassifier.🤩
installation
`python
pip install -u deepclassifier
`
Models¶
I will show you that the pramamters of models.🤩
TextCNN model¶
I will show you that the pramamters of textcnn.🤩
Initialization¶
class TextCNN(nn.Module):
- def __init__(self,embedding_dim,dropout_rate,
num_class,vocab_size=0,seq_length=0, num_layers=3,kernel_sizes=[3, 4, 5], strides=[1, 1, 1],paddings=[0, 0, 0], num_filters=[100, 100, 100], embedding_matrix=None, requires_grads=False):
In default,the way to initialize embedding is loading pretrained embedding look-up table!
- param embedding_dim
embedding dim
- param dropout_rate
drouput rate
- param num_class
the number of label
- param vocab_size
vocabulary size
- param seq_length
max length of sequence after padding
- param num_layers
the number of cnn
- param kernel_sizes
list of conv kernel size
- param strides
list of conv strides
- param paddings
list of padding
- param num_filters
list of num filters
- param embedding_matrix
pretrained embedding look-up table,shape is:[vocab_size,embedding_dim]
- param requires_grads
whether to update gradient of embedding in training