hookeai.model_architectures.hybrid_base_model.train.training

Training of hybrid model.

Classes

EarlyStopper

Early stopping procedure (implicit regularizaton).

Functions

train_model

Training of hybrid model.

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

data_scaler_transform(model, tensor, ...[, mode])

Perform data scaling operation on features PyTorch tensor.

fit_data_scalers(model, dataset[, ...])

Fit model data scalers.

get_learning_rate_scheduler(optimizer, ...)

Get PyTorch optimizer learning rate scheduler.

get_model_summary(model[, input_data, ...])

Get summary of PyTorch model.

get_pytorch_loss(loss_type, **kwargs)

Get PyTorch-based loss function.

get_pytorch_optimizer(algorithm, params, ...)

Get PyTorch optimizer.

get_time_series_data_loader(dataset[, ...])

Get time series data set data loader.

load_model_state(model[, model_load_state, ...])

Load model state from file.

predict(dataset, model_directory[, model, ...])

Make predictions with hybrid model for given dataset.

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_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.

seed_worker(worker_id)

Set workers seed in PyTorch data loaders to preserve reproducibility.

train_model(n_max_epochs, dataset, ...[, ...])

Training of hybrid model.

write_training_summary_file(device_type, ...)

Write summary data file for model training process.

Classes

EarlyStopper(validation_dataset[, ...])

Early stopping procedure (implicit regularizaton).

HybridModel(n_features_in, n_features_out, ...)

Hybrid model.