How to update PyTorch to the latest version on CentOS
Apr 14, 2025 pm 06:15 PMUpdating PyTorch to the latest version on CentOS can be done as follows:
Method 1: Use pip
-
Upgrade pip : First make sure your pip is the latest version, because older versions of pip may not properly install the latest version of PyTorch.
pip install --upgrade pip
-
Uninstall an older version of PyTorch (if installed):
pip uninstall torch torchvision torchaudio
-
Install the latest version of PyTorch : Visit the PyTorch official website and select the installation command that suits your system. For example, if you are using CUDA 11.7, the command might be:
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu117
If you don't need GPU support, you can use the CPU version:
pip install torch torchvision torchaudio
Method 2: Use conda (if you use Anaconda)
-
Update conda : Make sure your conda is up to date.
conda update conda
-
Create a new environment (optional) : To avoid affecting other projects, it is recommended to install the latest version of PyTorch in a new environment.
conda create -n pytorch_env python=3.9 conda activate pytorch_env
-
Install the latest version of PyTorch : Use conda to install the latest version of PyTorch. Visit the PyTorch official website and select the installation command that suits your system. For example:
conda install pytorch torchvision torchaudio cudatoolkit=11.7 -c pytorch
If you don't need GPU support, you can use the CPU version:
conda install pytorch torchvision torchaudio cpuonly -c pytorch
Verify installation
No matter which method is used to install, you can verify whether PyTorch is installed successfully through the following command:
import torch print(torch.__version__)
This will output the currently installed PyTorch version number.
Things to note
- Make sure your system meets PyTorch's dependencies requirements.
- If you encounter any problems during the installation process, you can refer to the installation guide in the official PyTorch documentation.
Through the above steps, you should be able to successfully update PyTorch to the latest version on CentOS.
The above is the detailed content of How to update PyTorch to the latest version on CentOS. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undress AI Tool
Undress images for free

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

The key to dealing with API authentication is to understand and use the authentication method correctly. 1. APIKey is the simplest authentication method, usually placed in the request header or URL parameters; 2. BasicAuth uses username and password for Base64 encoding transmission, which is suitable for internal systems; 3. OAuth2 needs to obtain the token first through client_id and client_secret, and then bring the BearerToken in the request header; 4. In order to deal with the token expiration, the token management class can be encapsulated and automatically refreshed the token; in short, selecting the appropriate method according to the document and safely storing the key information is the key.

The way to access nested JSON objects in Python is to first clarify the structure and then index layer by layer. First, confirm the hierarchical relationship of JSON, such as a dictionary nested dictionary or list; then use dictionary keys and list index to access layer by layer, such as data "details"["zip"] to obtain zip encoding, data "details"[0] to obtain the first hobby; to avoid KeyError and IndexError, the default value can be set by the .get() method, or the encapsulation function safe_get can be used to achieve secure access; for complex structures, recursively search or use third-party libraries such as jmespath to handle.

Asynchronous programming is made easier in Python with async and await keywords. It allows writing non-blocking code to handle multiple tasks concurrently, especially for I/O-intensive operations. asyncdef defines a coroutine that can be paused and restored, while await is used to wait for the task to complete without blocking the entire program. Running asynchronous code requires an event loop. It is recommended to start with asyncio.run(). Asyncio.gather() is available when executing multiple coroutines concurrently. Common patterns include obtaining multiple URL data at the same time, reading and writing files, and processing of network services. Notes include: Use libraries that support asynchronously, such as aiohttp; CPU-intensive tasks are not suitable for asynchronous; avoid mixed

To test the API, you need to use Python's Requests library. The steps are to install the library, send requests, verify responses, set timeouts and retry. First, install the library through pipinstallrequests; then use requests.get() or requests.post() and other methods to send GET or POST requests; then check response.status_code and response.json() to ensure that the return result is in compliance with expectations; finally, add timeout parameters to set the timeout time, and combine the retrying library to achieve automatic retry to enhance stability.

In Python, variables defined inside a function are local variables and are only valid within the function; externally defined are global variables that can be read anywhere. 1. Local variables are destroyed as the function is executed; 2. The function can access global variables but cannot be modified directly, so the global keyword is required; 3. If you want to modify outer function variables in nested functions, you need to use the nonlocal keyword; 4. Variables with the same name do not affect each other in different scopes; 5. Global must be declared when modifying global variables, otherwise UnboundLocalError error will be raised. Understanding these rules helps avoid bugs and write more reliable functions.

In Python, there is no need for temporary variables to swap two variables. The most common method is to unpack with tuples: a, b=b, a. This method first evaluates the right expression to generate a tuple (b, a), and then unpacks it to the left variable, which is suitable for all data types. In addition, arithmetic operations (addition, subtraction, multiplication and division) can be used to exchange numerical variables, but only numbers and may introduce floating point problems or overflow risks; it can also be used to exchange integers, which can be implemented through three XOR operations, but has poor readability and is usually not recommended. In summary, tuple unpacking is the simplest, universal and recommended way.

To create modern and efficient APIs using Python, FastAPI is recommended; it is based on standard Python type prompts and can automatically generate documents, with excellent performance. After installing FastAPI and ASGI server uvicorn, you can write interface code. By defining routes, writing processing functions, and returning data, APIs can be quickly built. FastAPI supports a variety of HTTP methods and provides automatically generated SwaggerUI and ReDoc documentation systems. URL parameters can be captured through path definition, while query parameters can be implemented by setting default values ??for function parameters. The rational use of Pydantic models can help improve development efficiency and accuracy.

Add timeout control to Python's for loop. 1. You can record the start time with the time module, and judge whether it is timed out in each iteration and use break to jump out of the loop; 2. For polling class tasks, you can use the while loop to match time judgment, and add sleep to avoid CPU fullness; 3. Advanced methods can consider threading or signal to achieve more precise control, but the complexity is high, and it is not recommended for beginners to choose; summary key points: manual time judgment is the basic solution, while is more suitable for time-limited waiting class tasks, sleep is indispensable, and advanced methods are suitable for specific scenarios.
