报错的原始代码:
%matplotlib inline import numpy as np import pandas as pd import torch from torch import nn from d2l import torch as d2l """使用 D2L 库的 DATA_HUB 机制,自动下载 Kaggle 房价预测数据集(训练集和测试集),并用 Pandas 读取为 DataFrame。""" # -----------------------------1.定义数据集在 DATA_HUB 中的条目------------------------------------------------------------ # DATA_HUB 是一个全局字典,存储了多个数据集的元信息。 # 每个键(如 'kaggle_house_train')对应一个元组,包含: # 第一个元素:文件的下载 URL(由 DATA_URL + 文件名拼接而成)。 # 第二个元素:文件的 SHA-1 哈希值,用于校验文件完整性。 # 这里注册了两个文件:训练集和测试集。 DATA_HUB['kaggle_house_train'] = ( DATA_URL + 'kaggle_house_pred_train.csv', '585e9cc93e70b39160e7921475f9bcd7d31219ce') DATA_HUB['kaggle_house_test'] = ( DATA_URL + 'kaggle_house_pred_test.csv', 'fa19780a7b011d9b009e8bff8e99922a8ee2eb90') # -----------------------------2.下载并读取 CSV 文件 ----------------------------- # pd.read_csv() 将下载的 CSV 文件读取为 Pandas DataFrame,分别赋给 train_data 和 test_data。 # Pandas DataFrame是一个二维的、带标签的、可以装不同数据类型的表格数据结构。 train_data = pd.read_csv(download('kaggle_house_train')) test_data = pd.read_csv(download('kaggle_house_test')) print(train_data.shape) print(test_data.shape)报错位置:
import torch解决方法(感谢千老师):
1.查找当前环境下全部包的版本
# 1. 查看当前使用的 Python 版本和路径 import sys print(f"Python Version: {sys.version}") print(f"Executable Path: {sys.executable}\n") # 2. 列出当前环境中所有已安装的库及其版本 import pkg_resources installed_packages = [(d.project_name, d.version) for d in pkg_resources.working_set] installed_packages.sort() # 按字母排序,方便查看 for pkg, version in installed_packages: print(f"{pkg}=={version}")运行输出:
C:\Users\ASUS\AppData\Local\Temp\ipykernel_19704\1993217012.py:7: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
import pkg_resources QtPy==2.4.3 anyio==4.13.0 argon2-cffi==25.1.0 argon2-cffi-bindings==25.1.0 arrow==1.4.0 asttokens==3.0.1 async-lru==2.3.0 attrs==26.1.0 autocommand==2.2.2 babel==2.18.0 backports.tarfile==1.2.0 beautifulsoup4==4.14.3 bleach==6.3.0 certifi==2026.4.22 cffi==2.0.0 charset-normalizer==3.4.7 colorama==0.4.6 comm==0.2.3 contourpy==1.3.2 cycler==0.12.1 d2l==1.0.3 debugpy==1.8.20 decorator==5.2.1 defusedxml==0.7.1 executing==2.2.1 fastjsonschema==2.21.2 filelock==3.29.0 fonttools==4.63.0 fqdn==1.5.1 fsspec==2026.4.0 h11==0.16.0 httpcore==1.0.9 httpx==0.28.1 idna==3.15 importlib-metadata==8.7.1 ipykernel==7.2.0 ipython==9.13.0 ipython-pygments-lexers==1.1.1 ipywidgets==8.1.8 isoduration==20.11.0 jaraco-context==6.1.0 jaraco-functools==4.4.0 jaraco.text==4.0.0 jedi==0.20.0 jinja2==3.1.6 json5==0.14.0 jsonpointer==3.1.1 jsonschema==4.26.0 jsonschema-specifications==2025.9.1 jupyter==1.0.0 jupyter-client==8.8.0 jupyter-console==6.6.3 jupyter-core==5.9.1 jupyter-events==0.12.1 jupyter-lsp==2.3.1 jupyter-server==2.18.2 jupyter-server-terminals==0.5.4 jupyterlab==4.5.7 jupyterlab-pygments==0.3.0 jupyterlab-server==2.28.0 jupyterlab-widgets==3.0.16 kiwisolver==1.5.0 lark==1.3.1 markupsafe==3.0.3 matplotlib==3.7.2 matplotlib-inline==0.1.6 mistune==3.2.1 more-itertools==10.8.0 mpmath==1.3.0 nbclient==0.10.4 nbconvert==7.17.1 nbformat==5.10.4 nest-asyncio==1.6.0 networkx==3.6.1 notebook==7.5.6 notebook-shim==0.2.4 numpy==1.23.5 overrides==7.7.0 packaging==26.0 pandas==2.0.3 pandocfilters==1.5.1 parso==0.8.7 pillow==12.2.0 pip==26.0.1 platformdirs==4.9.6 prometheus-client==0.25.0 prompt-toolkit==3.0.52 psutil==7.2.2 pure-eval==0.2.3 pycparser==3.0 pygments==2.20.0 pyparsing==3.0.9 python-dateutil==2.9.0.post0 python-json-logger==4.1.0 pytz==2026.2 pywinpty==3.0.3 pyyaml==6.0.3 pyzmq==27.1.0 qtconsole==5.7.2 referencing==0.37.0 requests==2.31.0 rfc3339-validator==0.1.4 rfc3986-validator==0.1.1 rfc3987-syntax==1.1.0 rpds-py==0.30.0 scipy==1.10.1 send2trash==2.1.0 setuptools==81.0.0 six==1.17.0 soupsieve==2.8.3 stack-data==0.6.3 sympy==1.14.0 terminado==0.18.1 tinycss2==1.4.0 tomli==2.4.0 torch==2.12.0 torchvision==0.27.0 tornado==6.5.5 traitlets==5.15.0 typing-extensions==4.15.0 tzdata==2026.2 uri-template==1.3.0 urllib3==2.7.0 wcwidth==0.7.0 webcolors==25.10.0 webencodings==0.5.1 websocket-client==1.9.0 wheel==0.46.3 widgetsnbextension==4.0.15 zipp==3.23.0
2.找到问题原因:
3.解决方法:
降级setuptools:在自己的jupyter_env环境中运行pip install "setuptools<81"
pip install "setuptools<81"4.最终结果:
完美解决OSError: [WinError 1114] 动态链接库(DLL)初始化例程失败。 Error loading "D:\miniconda3\envs\jupyter_e