hookeai.material_model_finder.train.training¶

Material model finder learning procedure.

Functions¶

train_model: Training of recurrent constitutive model.
save_material_models_state: Save material models states at given training epoch.
save_parameters_history: Save model learnable parameters history record.
read_parameters_history_from_file: Read model learnable parameters history from parameters record file.
save_best_parameters: Save best performance state model parameters.
read_best_parameters_from_file: Read best performance state model parameters from file.

Functions

`check_model_parameters_convergence`(...[, ...])	Check convergence of model parameters.
`get_learning_rate_scheduler`(optimizer, ...)	Get PyTorch optimizer learning rate scheduler.
`get_model_summary`(model[, input_data, ...])	Get summary of PyTorch model.
`get_pytorch_optimizer`(algorithm, params, ...)	Get PyTorch optimizer.
`read_best_parameters_from_file`(...)	Read best performance state model parameters from file.
`read_parameters_history_from_file`(...)	Read model learnable parameters history from parameters record file.
`save_best_parameters`(model, ...)	Save best performance state model parameters.
`save_loss_history`(model, n_max_epochs, ...)	Save training process loss history record.
`save_material_models_state`(model[, ...])	Save material models states to files.
`save_model_state`(model[, state_type, epoch, ...])	Save model state to file.
`save_parameters_history`(model, ...)	Save model learnable parameters history record.
`save_training_state`(model, optimizer, state_type)	Save model and optimizer states at given training epoch.
`train_model`(n_max_epochs, specimen_data, ...)	Training of recurrent constitutive model.
`write_training_summary_file`(device_type, ...)	Write summary data file for model training process.

Classes

MaterialModelFinder(model_directory[, ...])

Material model finder forward model.