training_simulation Documentation
- memristor_crossbar.training_simulation.define_testing_data()[source][source]
Define the testing dataset.
- Returns:
A 2D NumPy array where each row represents a test sample.
- Return type:
np.ndarray
- memristor_crossbar.training_simulation.define_testing_outputs()[source][source]
Define the testing outputs.
- Returns:
A 2D NumPy array where each row corresponds to the output labels for the test samples.
- Return type:
np.ndarray
- memristor_crossbar.training_simulation.define_training_data()[source][source]
Define the training dataset.
- Returns:
A 2D NumPy array where each row represents a training sample.
- Return type:
np.ndarray
- memristor_crossbar.training_simulation.define_training_outputs()[source][source]
Define the training outputs.
- Returns:
A 2D NumPy array where each row corresponds to the output labels for the training samples.
- Return type:
np.ndarray
- memristor_crossbar.training_simulation.setup_logging(level=20)[source][source]
Configure the logging module for the application.
- Parameters:
level (int, optional) – The logging level, set to logging.INFO by default. This means that all log messages at this level and above (i.e., INFO, WARNING, ERROR, and CRITICAL) will be output.
Examples
>>> setup_logging()
