rindow/rindow-neuralnetworks
Composer 安装命令:
composer require rindow/rindow-neuralnetworks
包简介
Neural networks library for deep learning
README 文档
README
Rindow Neural Network Library is a high-level neural network library for deep learning.
Overview
Like Keras in Python, you can easily write network models in PHP.
Website:
- Rindow project: https://rindow.github.io/
- Rindow Neural Networks: https://rindow.github.io/neuralnetworks
Speeding up
The external libraries rindow-matlib and OpenBLAS can be used to perform calculations at speeds close to CPU versions of TensorFlow. Models trained on laptops are available on popular web hosting. Deep learning is also available on popular PHP web hosting services.
GPU acceleration
It supports GPU acceleration using OpenCL. You can also use GPUs other than n-vidia if they support OpenCL. It can also be used with an integrated GPU installed in your laptop.
Linked library
- Rindow Math Matrix: Scientific calculation library
- Rindow Matlib: A fast matrix calculation library suitable for machine learning
- OpenBLAS: Fast Matrix Arithmetic Library
- Rindow Math Plot: Visualize machine learning results
- OpenCL: GPU computational programming interface
- CLBlast: High-speed matrix calculation library using OpenCL
Required environment
- PHP 8.1, 8.2, 8.3, 8.4
- For PHP 7.x, 8.0 environments, use Release 1.x.
Install
Click here for detailed instructions.
Please prepare in advance:
- Install php-cli, php-gd, and php-sqlite3 in advance using the method appropriate for each operating system.
- Install composer
Please install using Composer.
$ composer require rindow/rindow-neuralnetworks $ composer require rindow/rindow-math-plot
If you use it as is, it will take time to learn. In order to increase speed, we strongly recommend that you install a high-speed calculation library.
Please set up an external library.
Prebuilt binaries:
- Rindow-matlib: https://github.com/rindow/rindow-matlib/releases
- OpenBLAS: https://github.com/OpenMathLib/OpenBLAS/releases
Please set up according to your environment. Click here for detailed instructions.
$ composer require rindow/rindow-math-matlibffi
memory expansion:
Depending on the amount of data you use, you may need to increase the maximum amount of memory that PHP uses.
Especially when dealing with image data, the amount of sample data becomes enormous and requires more memory capacity than expected.
For example, change memory_limit in php.ini as follows.
memory_limit = 8G
Model description
The sample directory provides source code for simple image learning.
Please run as follows:
$ RINDOW_MATH_PLOT_VIEWER=/path/to/viewer $ export RINDOW_MATH_PLOT_VIEWER $ mkdir samples $ cd samples $ cp ../vendor/rindow/rindow-neuralnetworks/samples/basic-image-clasification.php . $ php basic-image-clasification.php
*Please specify an appropriate viewer for RINDOW_MATH_PLOT_VIEWER. (ex. viewnior)
If done correctly, a graph of the learning process will be displayed.
GPU/OpenCL support
Please download the binary.
Set up the binary files according to your environment. Detailed instructions here https://github.com/rindow/rindow-math-matrix-matlibffi/
Please set environment variables.
$ RINDOW_NEURALNETWORKS_BACKEND=rindowclblast::GPU $ export RINDOW_NEURALNETWORKS_BACKEND $ cd samples $ php basic-image-classification.php
*For RINDOW_NEURALNETWORKS_BACKEND, you can specify not only a name such as rindowclblast, but also the OpenCL device type and a set of Platform-ID and Device-ID. For example, "rindowclblast::GPU" or "rindowclblast::0,0"
rindow/rindow-neuralnetworks 适用场景与选型建议
rindow/rindow-neuralnetworks 是一款 基于 PHP 开发的 Composer 扩展包,目前已累计 11.36k 次下载、GitHub Stars 达 85, 最近一次更新时间为 2020 年 02 月 04 日, 在 PHP 生态内属于活跃度较高的组件。
它主要适用于以下技术方向: 「deep」 「machine learning」 「networks」 「Neural」 「learning」 「Deep learning」 等业务场景。在实际项目中,围绕这些方向常见需要落地的问题包括:接口对接、性能调优、并发安全、与既有框架(Laravel / ThinkPHP / Yii / Webman 等)的兼容适配,以及生产环境的日志埋点与稳定性保障。
我们在过去多个企业项目中使用过 rindow/rindow-neuralnetworks 或与其功能相近的方案,如果你在选型或落地过程中遇到问题,例如 版本兼容、二次改造、私有化封装、与内部系统对接、生产 BUG 排查,欢迎联系我们协助评估。
基于 rindow/rindow-neuralnetworks 在你已有业务上做功能扩展、字段裁剪、UI 适配、与内部账号 / 权限 / 日志系统的深度对接。
线上偶发问题、内存泄漏、慢查询、并发异常等排查修复;针对高流量场景做缓存、队列、索引层面的调优。
承接完整的项目从需求 → 设计 → 开发 → 上线 → 长期运维;也可按月提供技术保姆服务。
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统计信息
- 总下载量: 11.36k
- 月度下载量: 0
- 日度下载量: 0
- 收藏数: 86
- 点击次数: 21
- 依赖项目数: 0
- 推荐数: 0
其他信息
- 授权协议: BSD-3-Clause
- 更新时间: 2020-02-04