src.pulsarsa.tools.network_visualizer package

Submodules

src.pulsarsa.tools.network_visualizer.drawing_neural_net module

class src.pulsarsa.tools.network_visualizer.drawing_neural_net.NetworkBoard(model: Module, notebook: bool = False, lut_range: tuple[float, float] = (-0.1, 0.1), saved_network_path: str | None = None, plot_module: list[str] = ['conv2d', 'convtranspose2d', 'linear', 'norm2d', 'maxpool2d'], timer_interval: int = 1000, centered_input_node_index: int = 0, object_z_depth: int = 5, object_xy_depth: int = 5, debug_messages: bool = False)

Bases: DrawingBoard

This method is used to visualize the neural network model in 3D using VTK. It creates a 3D representation of the model’s layers and connections, allowing for interactive exploration of the network architecture. As of version 1.0 release it supports only 2D convolutional networks containing Conv2d, ConvTranspose2d, Linear, BatchNorm2d, InstanceNorm2d, GroupNorm and MaxPool2d layers.

src.pulsarsa.tools.network_visualizer.drawing_tools module

Module contents

class src.pulsarsa.tools.network_visualizer.NetworkBoard(model: Module, notebook: bool = False, lut_range: tuple[float, float] = (-0.1, 0.1), saved_network_path: str | None = None, plot_module: list[str] = ['conv2d', 'convtranspose2d', 'linear', 'norm2d', 'maxpool2d'], timer_interval: int = 1000, centered_input_node_index: int = 0, object_z_depth: int = 5, object_xy_depth: int = 5, debug_messages: bool = False)

Bases: DrawingBoard

This method is used to visualize the neural network model in 3D using VTK. It creates a 3D representation of the model’s layers and connections, allowing for interactive exploration of the network architecture. As of version 1.0 release it supports only 2D convolutional networks containing Conv2d, ConvTranspose2d, Linear, BatchNorm2d, InstanceNorm2d, GroupNorm and MaxPool2d layers.