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计算机视觉图像二分类预测脚本
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计算机视觉图像二分类预测脚本

import torch import torch.nn as nn from PIL import Image from torchvision import transforms # ========================================== # 1. 定义 Hors

Admin Admin 发布于 2026-05-27
卷积神经网络（CNN）图像二分类模型
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卷积神经网络（CNN）图像二分类模型

import torch import torch.nn as nn import torch.optim as optim # ========================================== # 1. 定义 HorsesHumansCNN 模型 # ============

Admin Admin 发布于 2026-05-27
“horse-or-human”的图像分类模型
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“horse-or-human”的图像分类模型

import urllib.request import zipfile import os from torchvision import datasets, transforms from torch.utils.data import DataLoader # ===============

Admin Admin 发布于 2026-05-27
PyTorch模型的结构摘要
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PyTorch模型的结构摘要

from torchsummary import summary model = FashionCNN().to(device) # Assuming your model is already defined and moved to the device summary(model, inp

Admin Admin 发布于 2026-05-27
卷积神经网络（CNN）
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卷积神经网络（CNN）

import torch import torch.nn as nn import torch.optim as optim from torchvision import datasets, transforms from torch.utils.data import DataLoader #

Admin Admin 发布于 2026-05-27
模型早停机制
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模型早停机制

# EARLY STOPPING VERSION import torch import torch.nn as nn import torch.optim as optim from torchvision import datasets, transforms from torch.utils.

Admin Admin 发布于 2026-05-26
单样本推理
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单样本推理

# CHECK SINGLE PREDICTION AND PLOT import matplotlib.pyplot as plt def predict_single_image(image, label, model): # Set the model to evaluation m

Admin Admin 发布于 2026-05-26
模型测试/验证函数
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模型测试/验证函数

# Function to test the model def test(dataloader, model): size = len(dataloader.dataset) num_batches = len(dataloader) model.eval() # Set

Admin Admin 发布于 2026-05-26
多层感知机
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多层感知机

import torch import torch.nn as nn import torch.optim as optim from torchvision import datasets, transforms from torch.utils.data import DataLoader #

Admin Admin 发布于 2026-05-26
线性回归
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线性回归

import torch import torch.nn as nn import torch.optim as optim # Define the model model = nn.Sequential(nn.Linear(1, 1)) # Define the optimizer and

Admin Admin 发布于 2026-05-26
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