brainspy.processors.simulation#
This package contains the files necessary for handling the software processors that handle internal differences within the main Processor class. Instead of having a driver, it is composed of a deep neural network model (with frozen weights). The SoftwareProcessor module expects input data that is already plateaued. SoftwareProcessors do not require any sort of ramping in the inputs, as this would reduce the overall performance in computing the outputs. However, plateaued data is allowed as it might help with simulating noise effects, providing a more accurate output than that without noise. For faster measurements, where noise simulation is not needed, a plateau of lenght 1 is recommended. Apart from the waveform difference, the SoftwareProcessor also applies to the output several effects such as the amplification correction of the device, clipping values, or relevant noise simulations. The hardware output is expected to be in nano-Amperes. Therefore, in order to be able to read it, it is amplified. The surrogate model can add an amplification correction factor so that the original output in nano-Amperes is received. See https://raw.githubusercontent.com/BraiNEdarwin/brains-py/master/docs/figures/processor.jpg for more information.
Modules
Module for creating and using a neural network model. |
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Package containing classes for generating noise. |
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File containing the main class for Software Processor, which goes inside the Processor class. |