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Pytorch 学习笔记数据操作 数据操作

线性回归线性回归的从零开始实现线性回归的简洁实现 线性回归的从零开始实现 import torch from IPython import display from matplotlib import pyplot as plt import numpy as np import random num_inputs = 2 num_examples = 1000 w = [2, -3.4] b ...

pytorch 计算flops和params from thop import profile import torch from resnet_18 import Resnet_18, resnet18 model = Resnet_18() input = torch.randn(1, 3, 256, 256) flops, params = profile(model, inputs = ...

tensorboard可视化resnet18 可视化resnet18 #-*-coding:utf-8-*- import torch import torchvision from torch.autograd import Variable from tensorboardX import SummaryWriter # 模拟输入数据 input_data = Variable(torch....

torch.stack用法详解 针对二维数据dim=0,1,2dim=0dim=1dim=2针对三维数据dim=0,1,2,3dim=0或1 是一样的dim=2dim=3 针对二维数据dim=0,1,2 dim=0 dim=1 dim=2 针对三维数据dim=0,1,2,3 dim=0或1 是一样的 dim=2 dim=3 所以可以看出dim是根据数据的维度从最后一维往前取d,d-...