Edit TensorFlow model for training

Before adding a TensorFlow model to IBM Spectrum Conductor Deep Learning Impact, edit the model to enable distributed training capabilities or deep learning insights.

By default, IBM Spectrum Conductor Deep Learning Impact supports single-node training for TensorFlow models without deep learning insights. To change the training engine, add deep learning insights, or add hyperparameter tuning capabilities the model must be configured accordingly.

IBM Spectrum Conductor Deep Learning Impact supports the following training engines:
  • Single node training
  • Distributed training
IBM Spectrum Conductor Deep Learning Impact supports single-node training for TensorFlow models with no extra configurations needed. For distributed engines, some additional configurations are required.
Each TensorFlow model has the following files:
  • main.py: TensorFlow train model program main entrance. This file is required for all TensorFlow models using any training engine.
  • inference.py: TensorFlow inference model program main entrance. This file is required for running validation or inference tests.
  • edi.py: TensorFlow elastic distributed inference model program main entrance. This file is required to publish training models to the elastic distributed inference engine.

To get the deep learning insights feature for TensorFlow models, edit the TensorFlow model to include deep learning insights, see Edit a TensorFlow training model for deep learning insights.