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TensorFlow with Poetry

This guide walks you through setting up TensorFlow in a Poetry-managed Python project.

🔍 Checking for Compatible TensorFlow Versions

To ensure compatibility with your system's configuration, visit:

📋 Prerequisites

Before setting up this project, ensure you have a basic understanding of the following tools:

  • Poetry: A dependency management tool (similar to npm for Node.js).

🛠️ Setup

Based on your hardware, update your pyproject.toml file with the appropriate configuration.

This configuration installs a version of Tensorflow optimized for CPU usage.

pyproject.toml
[project]
name = "project-name"
version = "0.1.0"
requires-python = ">=3.11,<3.12"
dependencies = [
    "tensorflow (>=2.18.0)",
    "tensorflow-io-gcs-filesystem (==0.31.0)",
    "tf-keras (>=2.18.0)",
    "tensorflow-intel (>=2.18.0) ; sys_platform != 'linux'"
]

[tool.poetry]
package-mode = false

[build-system]
requires = ["poetry-core>=2.0.0,<3.0.0"]
build-backend = "poetry.core.masonry.api"
Warning
  • TensorFlow no longer supports GPU acceleration on Windows.
  • NumPy 2.0 may cause compatibility issues with older Tensorflow & Python. If you experience problems, try specifying one of these NumPy versions in your dependencies:
    • numpy = "1.26.4"
    • numpy = "1.26.3"
Note
  • The configuration above is set up for Python versions between 3.11 (inclusive) and 3.12 (exclusive). Adjust the Python version in your pyproject.toml file if your project uses a different version.
  • For any issues related to version compatibility or performance, double-check your system’s drivers and ensure all dependencies are up-to-date.

🚀 Future Updates

Guidance for configuring TensorFlow with GPU support on Linux is forthcoming. Stay tuned for updates. In the meantime, you can refer to the official TensorFlow Installation Guide for the latest information.