run.py 1.83 KB
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"""Brain Mapper Run File

Description:
-------------
This file contains all the relevant functions for running BrainMapper.
The network can be ran in one of these modes:
    - train
    - evaluate path
    - evaluate whole


Usage
-------------
In order to run the network, in the terminal, the user needs to pass it relevant arguments:
    - (TODO: ADD ARGUMENTS)

"""

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import torch
from utils.data_utils import get_datasets
import BrainMapperUNet as BrainMapperUNet

# Set the default floating point tensor type to FloatTensor

torch.set_default_tensor_type(torch.FloatTensor)

def load_data(data_parameters):
    """Dataset Loader

    This function loads the training and testing datasets.
    TODO: Will need to define if all the training data is loaded as bulk or individually!

    Args:
        data_parameters (dict): Dictionary containing relevant information for the datafiles.
        data_parameters = {
            data_directory: 'path/to/directory'
            train_data_file: 'training_data'
            train_output_targets: 'training_targets'
            test_data_file: 'testing_data'
            test_target_file: 'testing_targets'
        }

    Returns:
        train_data (dataset object): Pytorch map-style dataset object, mapping indices to training data samples.
        test_data (dataset object): Pytorch map-style dataset object, mapping indices to testing data samples.

    Raises:
        None

    """
    print("Data is loading...")
    train_data, test_data = get_datasets(data_parameters)
    print("Data has loaded!")
    print("Training dataset size is {}".format(len(train_data)))
    print("Testing dataset size is {}".format(len(test_data)))

    return train_data, test_data
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def train():
    pass

def evaluate_path():
    pass

def evaluate_network():
    pass

def delete_files():
    pass

if __name__ == '__main__':
    pass