API Reference

`aihwkit`	Analog hardware library for PyTorch.
`aihwkit.cloud`	Functionality related to the cloud client for AIHW Composer API.
`aihwkit.cloud.client`	Client for connecting to the the AIHW Composer API.
`aihwkit.cloud.client.entities`	Data classes for the AIHW Composer API.
`aihwkit.cloud.client.exceptions`	Exceptions related to the cloud client.
`aihwkit.cloud.client.session`	Session handler for the AIHW Composer API.
`aihwkit.cloud.client.utils`	Utilities for the AIHW Composer API.
`aihwkit.cloud.client.v1`	Helpers for the AIHW Composer API (version 1).
`aihwkit.cloud.client.v1.api_client`	API client the AIHW Composer API.
`aihwkit.cloud.client.v1.i_api_client`	API client the AIHW Composer API.
`aihwkit.cloud.client.v1.parsers`	Parsers for the AIHW Composer API.
`aihwkit.cloud.client.v1.stubs`	API stubs for the AIHW Composer API.
`aihwkit.cloud.converter`	Conversion utilities for interacting with the AIHW Composer API.
`aihwkit.exceptions`	Custom Exceptions for aihwkit.
`aihwkit.experiments`	High-level interface for executing Experiments.
`aihwkit.experiments.experiments`	Experiments for aihwkit.
`aihwkit.experiments.experiments.inferencing`	Basic inferencing Experiment.
`aihwkit.experiments.experiments.training`	Basic training Experiment.
`aihwkit.experiments.runners.base`	Base class for an Experiment Runner.
`aihwkit.experiments.runners.cloud`	Base class for an Experiment Runner.
`aihwkit.experiments.runners.i_cloud`	Base class for an Experiment Runner.
`aihwkit.experiments.runners.i_local`	Runner that executes Experiments locally.
`aihwkit.experiments.runners.local`	Runner that executes Experiments locally.
`aihwkit.experiments.runners.i_metrics`	Helper for retrieving Metrics of an Experiment.
`aihwkit.experiments.runners.metrics`	Helper for retrieving Metrics of an Experiment.
`aihwkit.extension`	AIHWKIT extension
`aihwkit.inference`	High level inference tools.
`aihwkit.inference.calibration`	High level inference tools.
`aihwkit.inference.calibration.calibration`	Calibration for inference.
`aihwkit.inference.compensation`	Compensation methods such as drift compensation during analog inference.
`aihwkit.inference.compensation.base`	Base drift compensation for inference.
`aihwkit.inference.compensation.drift`	Global drift compensation for inference.
`aihwkit.inference.converter`	Converter of weight matrix values into conductance values and back for analog inference.
`aihwkit.inference.converter.base`	Base conductance converter for the phenomenological noise models for inference.
`aihwkit.inference.converter.conductance`	Conductance converters for the phenomenological noise models for inference.
`aihwkit.inference.converter.fusion`	Conductance converter for the fusion chip.
`aihwkit.inference.noise`	Noise models to apply to converted weight values during analog inference.
`aihwkit.inference.noise.base`	Base class for the phenomenological noise models for inference.
`aihwkit.inference.noise.custom`	Phenomenological noise model for inference.
`aihwkit.inference.noise.pcm`	Phenomenological noise models for PCM devices for inference.
`aihwkit.inference.noise.reram`	Phenomenological noise models for ReRAM devices for inference.
`aihwkit.linalg`	Linear Algebra functionality.
`aihwkit.linalg.matrix`	Defines an analog matrix
`aihwkit.simulator`	RPU simulator bindings.
`aihwkit.simulator.configs`	Configurations for resistive processing units.
`aihwkit.simulator.presets`	Configurations presets for resistive processing units.
`aihwkit.simulator.rpu_base`	Bindings for the RPU simulator.
`aihwkit.simulator.tiles`	High level analog tiles.
`aihwkit.simulator.parameters.io`	Forward / backward / update related parameters for resistive processing units.
`aihwkit.simulator.tiles.analog_mvm`	Implementation of analog MVM for torch tiles.
`aihwkit.simulator.tiles.analog_mvm_irdrop_t`	Low level implementation of torch-based tile.
`aihwkit.simulator.tiles.torch_tile_irdrop_t`	Low level implementation of torch-based tile.
`aihwkit.nn`	Neural network modules.
`aihwkit.nn.conversion`	Digital/analog model conversion utilities.
`aihwkit.nn.modules`	Neural network modules.
`aihwkit.nn.modules.base`	Base class for adding functionality to analog layers.
`aihwkit.nn.modules.container`	Analog Modules that contain children Modules.
`aihwkit.nn.modules.conv`	Convolution layers.
`aihwkit.nn.modules.conv_mapped`	Mapped convolution layers.
`aihwkit.nn.modules.linear`	Analog layers.
`aihwkit.nn.modules.linear_mapped`	Analog mapped linear layer.
`aihwkit.nn.modules.rnn`	Analog RNN related modules.
`aihwkit.nn.modules.rnn.cells`	Analog cells for RNNs.
`aihwkit.nn.modules.rnn.layers`	Analog RNN layers
`aihwkit.nn.modules.rnn.rnn`	Analog RNN modules.
`aihwkit.optim`	Analog Optimizers.
`aihwkit.optim.analog_optimizer`	Analog-aware inference optimizer.
`aihwkit.optim.context`	Parameter context for analog tiles.
`aihwkit.utils`	Utilities and helpers for aihwkit.
`aihwkit.utils.visualization`	Visualization utilities.
`aihwkit.utils.analog_info`	Analog Information utility.
`aihwkit.utils.fitting`	Fitting utilities.
`aihwkit.utils.legacy`	Conversion script of legacy checkpoints (pre v0.8) to the new format.
`aihwkit.utils.visualization_web`	Visualization utilities (web).
`aihwkit.utils.export`	Exporting utilities
`aihwkit.version`	Package version string.