TensorFlow/Keras to PyTorch Conversion

A systematic approach to converting TF/Keras models to PyTorch with numerical precision verification. Derived from real production experience converting ProteinBERT (6-layer attention model, 16M params, 145 weight arrays) and DeepFRI (GCN + CNN protein function prediction with CuDNNLSTM language model).

When to Use

• Target platform has no TF support (e.g. Ascend NPU with torch_npu)
• Need PyTorch ecosystem features (torchscript, ONNX, distributed)
• Migrating research code from TF to PyTorch for maintenance
• Converting pretrained TF weights to PyTorch format

Conversion Workflow