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d047b7417e
* refactor(WalkForward): cleaned up training & evaluation code * refactor: added run_whole_pipeline(), moved all previous models to archive
41 lines
1.4 KiB
Python
41 lines
1.4 KiB
Python
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#%%
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from create_dataset import load_format_data, create_dataloaders
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from train_predict import train_model, predict
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from models.built_in_models import create_TemporalFusionTransformer
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from models.custom_model import create_FullyConnectedModel
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from options import training_options, model_options_tft, model_options_fcn, dataset_options_tft, dataset_options_fcn
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import warnings
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warnings.filterwarnings("ignore")
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#%%
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def run_pipeline(model_name, data_dir):
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data = load_format_data(data_dir)
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dataset_options, model_options, _create_model = select_model(model_name)
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training_dataset, train_dataloader, val_dataloader = create_dataloaders(data, dataset_options)
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model = _create_model( training_dataset, model_options )
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trainer = train_model(model, train_dataloader, val_dataloader, training_options)
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predict(trainer, model, val_dataloader)
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#%%
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def select_model(model_name):
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if model_name == "FullyConnectedLayer":
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return dataset_options_fcn, model_options_fcn, create_FullyConnectedModel
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elif model_name == "TemporalFusionTransformer":
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return dataset_options_tft, model_options_tft, create_TemporalFusionTransformer
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else:
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assert False, "No such model exists."
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#%%
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run_pipeline("FullyConnectedLayer", '../data/')
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# #%%
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# if __name__ == '__main__':
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# run_pipeline("FullyConnectedLayer", '../data/')
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