TensorFlow DLL加载失败求助：初始化例程执行失败

Hey there, sorry you're stuck with this frustrating DLL error in TensorFlow! Let's walk through some targeted fixes that often resolve this exact issue, even after the steps you've already tried:

• Match TensorFlow version to Python 3.6 compatibility
  Python 3.6 works best with specific TensorFlow releases—skip the latest version and install TensorFlow 1.15.0 (the last stable build fully supported for Python 3.6). Run this in your Anaconda Prompt (make sure you're in the right environment first):
  pip install tensorflow==1.15.0

• Reinstall Visual C++ Redistributables (both architectures)
  Even if you installed the 2015 package, sometimes both x86 and x64 versions are required. Uninstall all existing Visual C++ Redistributable packages (2015, 2017, 2019, 2022), then download and install both x86 and x64 variants of Visual C++ Redistributable for Visual Studio 2015 Update 3. Restart your PC after installation.

• Build a fresh conda environment from scratch
  Conflicting packages in your existing environment might be causing the DLL issue. Create a clean space for TensorFlow:

  1. Open Anaconda Prompt and run:
     conda create -n tf_env python=3.6
  2. Activate the new environment:
     conda activate tf_env
  3. Install TensorFlow 1.15.0 and Jupyter Notebook:
     pip install tensorflow==1.15.0 jupyter
  4. Launch Jupyter directly from this environment and test TensorFlow again.

• Switch to CPU-only TensorFlow (if GPU isn't needed)
  If you're not using an NVIDIA GPU, the GPU-enabled TensorFlow might be trying to load missing CUDA DLLs. Install the CPU-only version explicitly:
  pip install tensorflow-cpu==1.15.0

• Identify missing DLLs with Dependency Walker
  Use Dependency Walker to open the tensorflow_core/_pywrap_tensorflow_internal.pyd file (usually found in Lib\site-packages\tensorflow_core within your conda environment). This tool will flag exactly which DLL is failing to initialize—often it's a corrupted system DLL or missing CUDA/cuDNN component you didn't catch earlier.

内容的提问来源于stack exchange，提问作者ibrahim