TfPyTh provides functions to wrap TensorFlow graphs as callable PyTorch functions and vice versa. It allows combining codebases from both frameworks into single trainable models with full gradient support. Tensors are copied through CPU memory since the frameworks use incompatible GPU array interfaces.