• Python realizes text classification with CNN and LSTM


    model.py: #!/usr/bin/python # -*- coding: utf-8 -*- import torch from torch import nn import numpy as np from torch.autograd import Variable import torch.nn.functional as F class TextRNN(nn.Module): “Text classification, RNN model” def __init__(self): super(TextRNN, self).__init__() #Three data to be input Self. Embedding = NN. Embedding (5000, 64) # # self.rnn = nn.LSTM(input_size=64, hidden_size=128, num_layers=2, bidirectional=True) […]

  • An example of MNIST handwritten numeral recognition and classification by using LSTM in Python


    The code is as follows. I think the most important thing for beginners is to learn the format of RNN reading data. # -*- coding: utf-8 -*- “”” Created on Tue Oct 9 08:53:25 2018 @author: www “”” import sys sys.path.append(‘..’) import torch import datetime from torch.autograd import Variable from torch import nn from torch.utils.data […]

  • An example of poetry writing based on LSTM neural network under Python


    Using tens of thousands of Tang poems as materials, the double-layer LSTM neural network is trained to write poems in the way of Tang poems. The code structure is divided into four parts One model.py The double layer LSTM model is defined Two data.py It defines the processing method of Tang poetry data from the […]

  • Examples of implementing LSTM and Gru with Python


    In order to solve the problem that traditional RNN can’t rely on long time, two variants of RNN, LSTM and Gru, are introduced. LSTM Long short term memory, called long short term memory network, means long short-term memory, which still solves the problem of short-term memory. This kind of short-term memory is relatively long and […]

  • Example of POS implemented by Python + LSTM


    After learning for a few days, I finally understood how to use python This is the code of the official document for direct handling After that, they will try to implement other NLP tasks by themselves # Author: Robert Guthrie import torch import torch.autograd as autograd import torch.nn as nn import torch.nn.functional as F import […]

  • Explanation of LSTM parameter using based on Python


    lstm(*input, **kwargs) The multi-layer long short time memory (LSTM) neural network is applied to the input sequence. Parameters: input_ Size: enter the number of expected features in ‘x’ hidden_ Size: number of properties in hidden state ‘H’ num_ Layers: the number of loop layers. For example, set ‘num’_ Layers = 2 ‘means that two lstms […]