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同样的参数，CPU跑15min，GPU 2min43s 1 #根据地名分辨国家 2 import math 3 import time 4 import torch 5 # 绘图 6 import matplotlib.pyplot as plt 7 import numpy as np 8 # 读 阅读全文
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CNN用于图像识别 最后accuracy on test set：98% 1 import torch 2 import torch.nn as nn 3 from torchvision import transforms 4 from torchvision import datasets 5 阅读全文
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课堂练习： 1 import torch 2 from torchvision import transforms 3 from torchvision import datasets 4 from torch.utils.data import DataLoader 5 import torch. 阅读全文
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课堂练习，课后作业不想做了…… 1 import torch 2 from torchvision import transforms 3 from torchvision import datasets 4 from torch.utils.data import DataLoader 5 imp 阅读全文
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课堂练习： 1 import torch 2 import numpy as np 3 from torch.utils.data import Dataset 4 from torch.utils.data import DataLoader 5 6 # prepare dataset 7 cla 阅读全文
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1 import numpy as np 2 import torch 3 import matplotlib.pyplot as plt 4 import os 5 os.environ['KMP_DUPLICATE_LIB_OK']='True' 6 7 #1 prepare dataset 8 阅读全文
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Seq2Path: Generating Sentiment Tuples as Paths of a Tree Seq2Path：生成情感元组作为树的路径 Author Information:Yue Mao, Yi Shen, Jingchao Yang, Xiaoying Zhu, Longj 阅读全文
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A Unified Generative Framework for Aspect-Based Sentiment Analysis Paper：https://arxiv.org/pdf/2106.04300.pdf Code：https://github.com/yhcc/BARTABSA Au 阅读全文
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1 import torch 2 import torch.nn.functional as F 3 4 # 1prepare dataset 5 x_data = torch.Tensor([[1.0], [2.0], [3.0]]) 6 y_data = torch.Tensor([[0], [ 阅读全文
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1 import torch 2 3 # 1prepare dataset 4 # x,y是矩阵，3行1列 也就是说总共有3个数据，每个数据只有1个特征 5 x_data = torch.tensor([[1.0], [2.0], [3.0]]) 6 y_data = torch.tensor([[ 阅读全文