Index _ | A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | R | S | T | U | V | W _ __author__ (in module analogvnn) __call__ (analogvnn.backward.BackwardModule.BackwardModule attribute) __call__() (analogvnn.graph.AccumulateGrad.AccumulateGrad method) (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph method) (analogvnn.graph.BackwardGraph.BackwardGraph method) (analogvnn.graph.ForwardGraph.ForwardGraph method) (analogvnn.nn.module.Layer.Layer method) (analogvnn.nn.module.Model.Model method) (analogvnn.nn.module.Sequential.Sequential method) (analogvnn.parameter.PseudoParameter.PseudoParameter method) __constants__ (analogvnn.nn.activation.ELU.SELU attribute) (analogvnn.nn.activation.ReLU.PReLU attribute) (analogvnn.nn.Linear.Linear attribute) (analogvnn.nn.module.Model.Model attribute) (analogvnn.nn.noise.GaussianNoise.GaussianNoise attribute) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise attribute) (analogvnn.nn.noise.PoissonNoise.PoissonNoise attribute) (analogvnn.nn.noise.UniformNoise.UniformNoise attribute) (analogvnn.nn.normalize.LPNorm.LPNorm attribute) (analogvnn.nn.precision.ReducePrecision.ReducePrecision attribute) (analogvnn.nn.precision.StochasticReducePrecision.StochasticReducePrecision attribute) __enter__() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) __exit__ (analogvnn.utils.TensorboardModelLog.TensorboardModelLog attribute) __getattr__() (analogvnn.backward.BackwardModule.BackwardModule method) __package__ (in module analogvnn) __post_init__() (analogvnn.utils.render_autograd_graph.AutoGradDot method) __repr__() (analogvnn.graph.AccumulateGrad.AccumulateGrad method) (analogvnn.graph.ArgsKwargs.ArgsKwargs method) (analogvnn.parameter.PseudoParameter.PseudoParameter method) __version__ (in module analogvnn) _add_layer_data() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) _autograd_backward (analogvnn.backward.BackwardModule.BackwardModule attribute) _backward_function (analogvnn.backward.BackwardFunction.BackwardFunction attribute) _backward_module (analogvnn.nn.module.Layer.Layer attribute) _calculate_gradients() (analogvnn.graph.BackwardGraph.BackwardGraph method) _call_impl (analogvnn.parameter.PseudoParameter.PseudoParameter attribute) _call_impl_backward() (analogvnn.backward.BackwardModule.BackwardModule method) _call_impl_forward() (analogvnn.backward.BackwardModule.BackwardModule method) (analogvnn.nn.module.Layer.Layer method) _called (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) _compiled (analogvnn.nn.module.Model.Model attribute) _create_edge_label() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph static method) _create_static_sub_graph() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph method) _detach_tensor() (analogvnn.graph.ForwardGraph.ForwardGraph static method) _device (analogvnn.utils.is_cpu_cuda.CPUCuda attribute) _disable_autograd_backward (analogvnn.backward.BackwardModule.BackwardModule attribute) _empty_holder_tensor (analogvnn.backward.BackwardModule.BackwardModule attribute) _forward_wrapper() (analogvnn.nn.module.Layer.Layer method) _ignore_tensor (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) _inputs (analogvnn.nn.module.Layer.Layer attribute) (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) _inputs_kwargs (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) _is_static (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) _layer (analogvnn.backward.BackwardModule.BackwardModule attribute) _log_record (analogvnn.utils.TensorboardModelLog.TensorboardModelLog attribute) _loss (analogvnn.graph.ModelGraphState.ModelGraphState attribute) _module (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) _outputs (analogvnn.nn.module.Layer.Layer attribute) (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) _pass() (analogvnn.graph.BackwardGraph.BackwardGraph method) (analogvnn.graph.ForwardGraph.ForwardGraph method) _reindex_out_args() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph static method) _seen (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) _set_autograd_backward() (analogvnn.backward.BackwardModule.BackwardModule method) _static_graphs (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) _transformation (analogvnn.parameter.PseudoParameter.PseudoParameter attribute) _transformed (analogvnn.parameter.PseudoParameter.PseudoParameter attribute) _use_autograd_graph (analogvnn.nn.module.Layer.Layer attribute) _zero (analogvnn.nn.activation.ReLU.PReLU attribute) A AccumulateGrad (class in analogvnn.graph.AccumulateGrad) accuracy_function (analogvnn.nn.module.Model.Model attribute) Activation (class in analogvnn.nn.activation.Activation) AcyclicDirectedGraph (class in analogvnn.graph.AcyclicDirectedGraph) add_connection() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph method) add_edge() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph method) (analogvnn.utils.render_autograd_graph.AutoGradDot method) add_fn() (analogvnn.utils.render_autograd_graph.AutoGradDot method) add_graph() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) add_ignore_tensor() (analogvnn.utils.render_autograd_graph.AutoGradDot method) add_seen() (analogvnn.utils.render_autograd_graph.AutoGradDot method) add_sequence() (analogvnn.nn.module.Sequential.Sequential method) add_summary() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) add_tensor() (analogvnn.utils.render_autograd_graph.AutoGradDot method) allow_loops (analogvnn.graph.ModelGraphState.ModelGraphState attribute) alpha (analogvnn.nn.activation.ELU.SELU attribute) (analogvnn.nn.activation.ReLU.PReLU attribute) analogvnn module analogvnn.backward module analogvnn.backward.BackwardFunction module analogvnn.backward.BackwardIdentity module analogvnn.backward.BackwardModule module analogvnn.backward.BackwardUsingForward module analogvnn.fn module analogvnn.fn.dirac_delta module analogvnn.fn.reduce_precision module analogvnn.fn.test module analogvnn.fn.to_matrix module analogvnn.fn.train module analogvnn.graph module analogvnn.graph.AccumulateGrad module analogvnn.graph.AcyclicDirectedGraph module analogvnn.graph.ArgsKwargs module analogvnn.graph.BackwardGraph module analogvnn.graph.ForwardGraph module analogvnn.graph.GraphEnum module analogvnn.graph.ModelGraph module analogvnn.graph.ModelGraphState module analogvnn.graph.to_graph_viz_digraph module analogvnn.nn module analogvnn.nn.activation module analogvnn.nn.activation.Activation module analogvnn.nn.activation.BinaryStep module analogvnn.nn.activation.ELU module analogvnn.nn.activation.Gaussian module analogvnn.nn.activation.Identity module analogvnn.nn.activation.ReLU module analogvnn.nn.activation.Sigmoid module analogvnn.nn.activation.SiLU module analogvnn.nn.activation.Tanh module analogvnn.nn.Linear module analogvnn.nn.module module analogvnn.nn.module.FullSequential module analogvnn.nn.module.Layer module analogvnn.nn.module.Model module analogvnn.nn.module.Sequential module analogvnn.nn.noise module analogvnn.nn.noise.GaussianNoise module analogvnn.nn.noise.LaplacianNoise module analogvnn.nn.noise.Noise module analogvnn.nn.noise.PoissonNoise module analogvnn.nn.noise.UniformNoise module analogvnn.nn.normalize module analogvnn.nn.normalize.Clamp module analogvnn.nn.normalize.LPNorm module analogvnn.nn.normalize.Normalize module analogvnn.nn.precision module analogvnn.nn.precision.Precision module analogvnn.nn.precision.ReducePrecision module analogvnn.nn.precision.StochasticReducePrecision module analogvnn.parameter module analogvnn.parameter.PseudoParameter module analogvnn.utils module analogvnn.utils.common_types module analogvnn.utils.get_model_summaries module analogvnn.utils.is_cpu_cuda module analogvnn.utils.render_autograd_graph module analogvnn.utils.TensorboardModelLog module analogvnn.utils.to_tensor_parameter module args (analogvnn.graph.ArgsKwargs.ArgsKwargs attribute) ArgsKwargs (class in analogvnn.graph.ArgsKwargs) ArgsKwargsInput (in module analogvnn.graph.ArgsKwargs) ArgsKwargsOutput (in module analogvnn.graph.ArgsKwargs) auto_apply() (analogvnn.backward.BackwardModule.BackwardModule method) AutoGradDot (class in analogvnn.utils.render_autograd_graph) B backward() (analogvnn.backward.BackwardFunction.BackwardFunction method) (analogvnn.backward.BackwardIdentity.BackwardIdentity method) (analogvnn.backward.BackwardModule.BackwardModule method) (analogvnn.backward.BackwardModule.BackwardModule.AutogradBackward static method) (analogvnn.backward.BackwardUsingForward.BackwardUsingForward method) (analogvnn.nn.activation.BinaryStep.BinaryStep method) (analogvnn.nn.activation.ELU.SELU method) (analogvnn.nn.activation.Gaussian.Gaussian method) (analogvnn.nn.activation.Gaussian.GeLU method) (analogvnn.nn.activation.Identity.Identity method) (analogvnn.nn.activation.ReLU.PReLU method) (analogvnn.nn.activation.Sigmoid.Logistic method) (analogvnn.nn.activation.SiLU.SiLU method) (analogvnn.nn.activation.Tanh.Tanh method) (analogvnn.nn.Linear.LinearBackpropagation method) (analogvnn.nn.module.Model.Model method) (analogvnn.nn.normalize.Clamp.Clamp method) (analogvnn.nn.normalize.Clamp.Clamp01 method) backward_function (analogvnn.backward.BackwardFunction.BackwardFunction property) (analogvnn.nn.module.Layer.Layer property) backward_graph (analogvnn.graph.ModelGraph.ModelGraph attribute) (analogvnn.nn.module.Model.Model attribute) BackwardFunction (class in analogvnn.backward.BackwardFunction) BackwardGraph (class in analogvnn.graph.BackwardGraph) BackwardIdentity (class in analogvnn.backward.BackwardIdentity) BackwardModule (class in analogvnn.backward.BackwardModule) BackwardModule.AutogradBackward (class in analogvnn.backward.BackwardModule) BackwardUsingForward (class in analogvnn.backward.BackwardUsingForward) bias (analogvnn.nn.Linear.Linear attribute) BinaryStep (class in analogvnn.nn.activation.BinaryStep) bit_precision (analogvnn.nn.precision.ReducePrecision.ReducePrecision property) (analogvnn.nn.precision.StochasticReducePrecision.StochasticReducePrecision property) C calc_high_low() (analogvnn.nn.noise.UniformNoise.UniformNoise static method) calc_leakage() (analogvnn.nn.noise.GaussianNoise.GaussianNoise static method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise static method) (analogvnn.nn.noise.UniformNoise.UniformNoise static method) calc_max_leakage() (analogvnn.nn.noise.PoissonNoise.PoissonNoise static method) calc_precision() (analogvnn.nn.noise.GaussianNoise.GaussianNoise static method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise static method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise static method) (analogvnn.nn.noise.UniformNoise.UniformNoise static method) calc_scale() (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise static method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise static method) calc_std() (analogvnn.nn.noise.GaussianNoise.GaussianNoise static method) calculate() (analogvnn.graph.BackwardGraph.BackwardGraph method) (analogvnn.graph.ForwardGraph.ForwardGraph method) call_super_init (analogvnn.nn.module.Layer.Layer attribute) cdf() (analogvnn.nn.noise.GaussianNoise.GaussianNoise method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise method) (analogvnn.nn.noise.UniformNoise.UniformNoise method) check_edge_parameters() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph static method) Clamp (class in analogvnn.nn.normalize.Clamp) Clamp01 (class in analogvnn.nn.normalize.Clamp) close() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) compile() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph method) (analogvnn.graph.BackwardGraph.BackwardGraph method) (analogvnn.graph.ForwardGraph.ForwardGraph method) (analogvnn.graph.ModelGraph.ModelGraph method) (analogvnn.nn.module.FullSequential.FullSequential method) (analogvnn.nn.module.Model.Model method) (analogvnn.nn.module.Sequential.Sequential method) convert_to_precision() (analogvnn.nn.precision.ReducePrecision.ReducePrecision static method) (analogvnn.nn.precision.StochasticReducePrecision.StochasticReducePrecision static method) CPUCuda (class in analogvnn.utils.is_cpu_cuda) create_tensorboard() (analogvnn.nn.module.Model.Model method) D del_ignore_tensor() (analogvnn.utils.render_autograd_graph.AutoGradDot method) device (analogvnn.nn.module.Model.Model attribute) (analogvnn.utils.is_cpu_cuda.CPUCuda property) device_name (analogvnn.utils.is_cpu_cuda.CPUCuda attribute) divide (analogvnn.nn.precision.ReducePrecision.ReducePrecision attribute) dot (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) E ELU (class in analogvnn.nn.activation.ELU) extra_repr() (analogvnn.nn.activation.Identity.Identity method) (analogvnn.nn.Linear.Linear method) (analogvnn.nn.noise.GaussianNoise.GaussianNoise method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise method) (analogvnn.nn.noise.UniformNoise.UniformNoise method) (analogvnn.nn.precision.ReducePrecision.ReducePrecision method) (analogvnn.nn.precision.StochasticReducePrecision.StochasticReducePrecision method) F fit() (analogvnn.nn.module.Model.Model method) forward (analogvnn.parameter.PseudoParameter.PseudoParameter attribute) forward() (analogvnn.backward.BackwardModule.BackwardModule method) (analogvnn.backward.BackwardModule.BackwardModule.AutogradBackward static method) (analogvnn.nn.activation.BinaryStep.BinaryStep static method) (analogvnn.nn.activation.ELU.SELU method) (analogvnn.nn.activation.Gaussian.Gaussian static method) (analogvnn.nn.activation.Gaussian.GeLU static method) (analogvnn.nn.activation.Identity.Identity static method) (analogvnn.nn.activation.ReLU.PReLU method) (analogvnn.nn.activation.Sigmoid.Logistic static method) (analogvnn.nn.activation.SiLU.SiLU static method) (analogvnn.nn.activation.Tanh.Tanh static method) (analogvnn.nn.Linear.LinearBackpropagation method) (analogvnn.nn.module.Model.Model method) (analogvnn.nn.noise.GaussianNoise.GaussianNoise method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise method) (analogvnn.nn.noise.UniformNoise.UniformNoise method) (analogvnn.nn.normalize.Clamp.Clamp static method) (analogvnn.nn.normalize.Clamp.Clamp01 static method) (analogvnn.nn.normalize.LPNorm.LPNorm method) (analogvnn.nn.normalize.LPNorm.LPNormW method) (analogvnn.nn.precision.ReducePrecision.ReducePrecision method) (analogvnn.nn.precision.StochasticReducePrecision.StochasticReducePrecision method) forward_graph (analogvnn.graph.ModelGraph.ModelGraph attribute) (analogvnn.nn.module.Model.Model attribute) forward_input_output_graph (analogvnn.graph.ModelGraphState.ModelGraphState attribute) ForwardGraph (class in analogvnn.graph.ForwardGraph) from_args_kwargs_object() (analogvnn.graph.ArgsKwargs.ArgsKwargs static method) from_forward() (analogvnn.graph.BackwardGraph.BackwardGraph method) FullSequential (class in analogvnn.nn.module.FullSequential) G Gaussian (class in analogvnn.nn.activation.Gaussian) gaussian_dirac_delta() (in module analogvnn.fn.dirac_delta) GaussianNoise (class in analogvnn.nn.noise.GaussianNoise) GeLU (class in analogvnn.nn.activation.Gaussian) get_autograd_dot_from_module() (in module analogvnn.utils.render_autograd_graph) get_autograd_dot_from_outputs() (in module analogvnn.utils.render_autograd_graph) get_autograd_dot_from_trace() (in module analogvnn.utils.render_autograd_graph) get_layer() (analogvnn.backward.BackwardModule.BackwardModule method) get_model_summaries() (in module analogvnn.utils.get_model_summaries) get_module_device() (analogvnn.utils.is_cpu_cuda.CPUCuda method) get_tensor_name() (analogvnn.utils.render_autograd_graph.AutoGradDot method) grad (analogvnn.graph.AccumulateGrad.AccumulateGrad attribute) graph (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) GRAPH_NODE_TYPE (in module analogvnn.graph.GraphEnum) graph_state (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) GraphEnum (class in analogvnn.graph.GraphEnum) graphs (analogvnn.nn.module.Model.Model attribute) H has_forward() (analogvnn.backward.BackwardModule.BackwardModule method) high (analogvnn.nn.noise.UniformNoise.UniformNoise attribute) I Identity (class in analogvnn.nn.activation.Identity) identity() (analogvnn.parameter.PseudoParameter.PseudoParameter static method) ignore_tensor (analogvnn.utils.render_autograd_graph.AutoGradDot property) in_features (analogvnn.nn.Linear.Linear attribute) initialise() (analogvnn.nn.activation.Activation.InitImplement static method) (analogvnn.nn.activation.ELU.SELU static method) (analogvnn.nn.activation.ReLU.PReLU static method) (analogvnn.nn.activation.ReLU.ReLU static method) (analogvnn.nn.activation.Sigmoid.Logistic static method) (analogvnn.nn.activation.Tanh.Tanh static method) initialise_() (analogvnn.nn.activation.Activation.InitImplement static method) (analogvnn.nn.activation.ELU.SELU static method) (analogvnn.nn.activation.ReLU.PReLU static method) (analogvnn.nn.activation.ReLU.ReLU static method) (analogvnn.nn.activation.Sigmoid.Logistic static method) (analogvnn.nn.activation.Tanh.Tanh static method) InitImplement (class in analogvnn.nn.activation.Activation) INPUT (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) (analogvnn.graph.GraphEnum.GraphEnum attribute) (analogvnn.graph.ModelGraphState.ModelGraphState attribute) input_output_connections (analogvnn.graph.AccumulateGrad.AccumulateGrad attribute) InputOutput (class in analogvnn.graph.ArgsKwargs) inputs (analogvnn.graph.ArgsKwargs.InputOutput attribute) (analogvnn.graph.ModelGraphState.ModelGraphState property) (analogvnn.nn.module.Layer.Layer property) (analogvnn.utils.render_autograd_graph.AutoGradDot property) inputs_kwargs (analogvnn.utils.render_autograd_graph.AutoGradDot property) is_cpu (analogvnn.utils.is_cpu_cuda.CPUCuda property) is_cpu_cuda (in module analogvnn.utils.is_cpu_cuda) is_cuda (analogvnn.utils.is_cpu_cuda.CPUCuda property) is_empty() (analogvnn.graph.ArgsKwargs.ArgsKwargs method) is_seen() (analogvnn.utils.render_autograd_graph.AutoGradDot method) is_using_cuda (analogvnn.utils.is_cpu_cuda.CPUCuda property) K kwargs (analogvnn.graph.ArgsKwargs.ArgsKwargs attribute) L L1Norm (class in analogvnn.nn.normalize.LPNorm) L1NormM (class in analogvnn.nn.normalize.LPNorm) L1NormW (class in analogvnn.nn.normalize.LPNorm) L1NormWM (class in analogvnn.nn.normalize.LPNorm) L2Norm (class in analogvnn.nn.normalize.LPNorm) L2NormM (class in analogvnn.nn.normalize.LPNorm) L2NormW (class in analogvnn.nn.normalize.LPNorm) L2NormWM (class in analogvnn.nn.normalize.LPNorm) LaplacianNoise (class in analogvnn.nn.noise.LaplacianNoise) layer (analogvnn.backward.BackwardModule.BackwardModule property) Layer (class in analogvnn.nn.module.Layer) layer_data (analogvnn.utils.TensorboardModelLog.TensorboardModelLog attribute) leakage (analogvnn.nn.noise.GaussianNoise.GaussianNoise attribute) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise attribute) (analogvnn.nn.noise.PoissonNoise.PoissonNoise property) (analogvnn.nn.noise.UniformNoise.UniformNoise attribute) LeakyReLU (class in analogvnn.nn.activation.ReLU) Linear (class in analogvnn.nn.Linear) LinearBackpropagation (class in analogvnn.nn.Linear) log_prob() (analogvnn.nn.noise.GaussianNoise.GaussianNoise method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise method) (analogvnn.nn.noise.UniformNoise.UniformNoise method) Logistic (class in analogvnn.nn.activation.Sigmoid) loss (analogvnn.graph.ModelGraphState.ModelGraphState property) loss() (analogvnn.nn.module.Model.Model method) loss_function (analogvnn.nn.module.Model.Model attribute) low (analogvnn.nn.noise.UniformNoise.UniformNoise attribute) LPNorm (class in analogvnn.nn.normalize.LPNorm) LPNormW (class in analogvnn.nn.normalize.LPNorm) M make_autograd_obj_from_module() (in module analogvnn.utils.render_autograd_graph) make_autograd_obj_from_outputs() (in module analogvnn.utils.render_autograd_graph) make_max_1 (analogvnn.nn.normalize.LPNorm.LPNorm attribute) max_attr_chars (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) max_leakage (analogvnn.nn.noise.PoissonNoise.PoissonNoise attribute) mean (analogvnn.nn.noise.UniformNoise.UniformNoise property) model (analogvnn.utils.TensorboardModelLog.TensorboardModelLog attribute) Model (class in analogvnn.nn.module.Model) ModelGraph (class in analogvnn.graph.ModelGraph) ModelGraphState (class in analogvnn.graph.ModelGraphState) module analogvnn analogvnn.backward analogvnn.backward.BackwardFunction analogvnn.backward.BackwardIdentity analogvnn.backward.BackwardModule analogvnn.backward.BackwardUsingForward analogvnn.fn analogvnn.fn.dirac_delta analogvnn.fn.reduce_precision analogvnn.fn.test analogvnn.fn.to_matrix analogvnn.fn.train analogvnn.graph analogvnn.graph.AccumulateGrad analogvnn.graph.AcyclicDirectedGraph analogvnn.graph.ArgsKwargs analogvnn.graph.BackwardGraph analogvnn.graph.ForwardGraph analogvnn.graph.GraphEnum analogvnn.graph.ModelGraph analogvnn.graph.ModelGraphState analogvnn.graph.to_graph_viz_digraph analogvnn.nn analogvnn.nn.activation analogvnn.nn.activation.Activation analogvnn.nn.activation.BinaryStep analogvnn.nn.activation.ELU analogvnn.nn.activation.Gaussian analogvnn.nn.activation.Identity analogvnn.nn.activation.ReLU analogvnn.nn.activation.Sigmoid analogvnn.nn.activation.SiLU analogvnn.nn.activation.Tanh analogvnn.nn.Linear analogvnn.nn.module analogvnn.nn.module.FullSequential analogvnn.nn.module.Layer analogvnn.nn.module.Model analogvnn.nn.module.Sequential analogvnn.nn.noise analogvnn.nn.noise.GaussianNoise analogvnn.nn.noise.LaplacianNoise analogvnn.nn.noise.Noise analogvnn.nn.noise.PoissonNoise analogvnn.nn.noise.UniformNoise analogvnn.nn.normalize analogvnn.nn.normalize.Clamp analogvnn.nn.normalize.LPNorm analogvnn.nn.normalize.Normalize analogvnn.nn.precision analogvnn.nn.precision.Precision analogvnn.nn.precision.ReducePrecision analogvnn.nn.precision.StochasticReducePrecision analogvnn.parameter analogvnn.parameter.PseudoParameter analogvnn.utils analogvnn.utils.common_types analogvnn.utils.get_model_summaries analogvnn.utils.is_cpu_cuda analogvnn.utils.render_autograd_graph analogvnn.utils.TensorboardModelLog analogvnn.utils.to_tensor_parameter module (analogvnn.graph.AccumulateGrad.AccumulateGrad attribute) (analogvnn.utils.render_autograd_graph.AutoGradDot property) N name (analogvnn.nn.activation.Identity.Identity attribute) named_registered_children() (analogvnn.nn.module.Layer.Layer method) (analogvnn.nn.module.Model.Model method) Noise (class in analogvnn.nn.noise.Noise) Normalize (class in analogvnn.nn.normalize.Normalize) O on_compile() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) optimizer (analogvnn.nn.module.Model.Model attribute) out_features (analogvnn.nn.Linear.Linear attribute) OUTPUT (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) (analogvnn.graph.GraphEnum.GraphEnum attribute) (analogvnn.graph.ModelGraphState.ModelGraphState attribute) outputs (analogvnn.graph.ArgsKwargs.InputOutput attribute) (analogvnn.graph.ModelGraphState.ModelGraphState property) (analogvnn.nn.module.Layer.Layer property) (analogvnn.utils.render_autograd_graph.AutoGradDot property) P p (analogvnn.nn.normalize.LPNorm.LPNorm attribute) param_map (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) parameterize() (analogvnn.parameter.PseudoParameter.PseudoParameter class method) parametrize_module() (analogvnn.parameter.PseudoParameter.PseudoParameter class method) parse_args_kwargs() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph method) pdf() (analogvnn.nn.noise.GaussianNoise.GaussianNoise method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise method) (analogvnn.nn.noise.UniformNoise.UniformNoise method) PoissonNoise (class in analogvnn.nn.noise.PoissonNoise) precision (analogvnn.nn.noise.GaussianNoise.GaussianNoise attribute) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise attribute) (analogvnn.nn.noise.PoissonNoise.PoissonNoise attribute) (analogvnn.nn.noise.UniformNoise.UniformNoise attribute) (analogvnn.nn.precision.ReducePrecision.ReducePrecision attribute) (analogvnn.nn.precision.StochasticReducePrecision.StochasticReducePrecision attribute) Precision (class in analogvnn.nn.precision.Precision) precision_width (analogvnn.nn.precision.ReducePrecision.ReducePrecision property) (analogvnn.nn.precision.StochasticReducePrecision.StochasticReducePrecision property) PReLU (class in analogvnn.nn.activation.ReLU) PseudoParameter (class in analogvnn.parameter.PseudoParameter) R rate_factor (analogvnn.nn.noise.PoissonNoise.PoissonNoise property) ready_for_backward() (analogvnn.graph.ModelGraphState.ModelGraphState method) ready_for_forward() (analogvnn.graph.ModelGraphState.ModelGraphState method) reduce_precision() (in module analogvnn.fn.reduce_precision) ReducePrecision (class in analogvnn.nn.precision.ReducePrecision) register_testing() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) register_training() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) registered_children() (analogvnn.nn.module.Layer.Layer method) ReLU (class in analogvnn.nn.activation.ReLU) render() (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph method) reset_parameters() (analogvnn.nn.Linear.Linear method) reset_params() (analogvnn.utils.render_autograd_graph.AutoGradDot method) right_inverse (analogvnn.parameter.PseudoParameter.PseudoParameter attribute) S save (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) save_autograd_graph_from_module() (in module analogvnn.utils.render_autograd_graph) save_autograd_graph_from_outputs() (in module analogvnn.utils.render_autograd_graph) save_autograd_graph_from_trace() (in module analogvnn.utils.render_autograd_graph) scale (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise attribute) (analogvnn.nn.noise.PoissonNoise.PoissonNoise attribute) scale_factor (analogvnn.nn.activation.ELU.SELU attribute) SELU (class in analogvnn.nn.activation.ELU) Sequential (class in analogvnn.nn.module.Sequential) set_backward_function() (analogvnn.backward.BackwardFunction.BackwardFunction method) (analogvnn.nn.module.Layer.Layer method) set_device() (analogvnn.utils.is_cpu_cuda.CPUCuda method) set_grad_of() (analogvnn.backward.BackwardModule.BackwardModule static method) set_layer() (analogvnn.backward.BackwardModule.BackwardModule method) set_log_dir() (analogvnn.utils.TensorboardModelLog.TensorboardModelLog method) set_loss() (analogvnn.graph.ModelGraphState.ModelGraphState method) set_original_data() (analogvnn.parameter.PseudoParameter.PseudoParameter method) set_transformation() (analogvnn.parameter.PseudoParameter.PseudoParameter method) show_attrs (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) show_saved (analogvnn.utils.render_autograd_graph.AutoGradDot attribute) Sigmoid (class in analogvnn.nn.activation.Sigmoid) SiLU (class in analogvnn.nn.activation.SiLU) size_to_str() (in module analogvnn.utils.render_autograd_graph) static_cdf() (analogvnn.nn.noise.GaussianNoise.GaussianNoise static method) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise static method) (analogvnn.nn.noise.PoissonNoise.PoissonNoise static method) staticmethod_leakage() (analogvnn.nn.noise.PoissonNoise.PoissonNoise static method) std (analogvnn.nn.noise.GaussianNoise.GaussianNoise attribute) stddev (analogvnn.nn.noise.GaussianNoise.GaussianNoise property) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise property) (analogvnn.nn.noise.UniformNoise.UniformNoise property) stochastic_reduce_precision() (in module analogvnn.fn.reduce_precision) StochasticReducePrecision (class in analogvnn.nn.precision.StochasticReducePrecision) STOP (analogvnn.graph.AcyclicDirectedGraph.AcyclicDirectedGraph attribute) (analogvnn.graph.GraphEnum.GraphEnum attribute) (analogvnn.graph.ModelGraphState.ModelGraphState attribute) subscribe_tensorboard() (analogvnn.nn.module.Model.Model method) substitute_member() (analogvnn.parameter.PseudoParameter.PseudoParameter static method) T Tanh (class in analogvnn.nn.activation.Tanh) TENSOR_CALLABLE (in module analogvnn.utils.common_types) TENSOR_OPERABLE (in module analogvnn.utils.common_types) tensorboard (analogvnn.nn.module.Model.Model attribute) (analogvnn.utils.TensorboardModelLog.TensorboardModelLog attribute) TensorboardModelLog (class in analogvnn.utils.TensorboardModelLog) TENSORS (in module analogvnn.utils.common_types) test() (in module analogvnn.fn.test) test_on() (analogvnn.nn.module.Model.Model method) to_args_kwargs_object() (analogvnn.graph.ArgsKwargs.ArgsKwargs class method) to_float_tensor() (in module analogvnn.utils.to_tensor_parameter) to_graphviz_digraph() (in module analogvnn.graph.to_graph_viz_digraph) to_matrix() (in module analogvnn.fn.to_matrix) to_nongrad_parameter() (in module analogvnn.utils.to_tensor_parameter) train() (in module analogvnn.fn.train) train_on() (analogvnn.nn.module.Model.Model method) transformation (analogvnn.parameter.PseudoParameter.PseudoParameter property) U UniformNoise (class in analogvnn.nn.noise.UniformNoise) use_autograd_graph (analogvnn.graph.ModelGraphState.ModelGraphState attribute) (analogvnn.nn.module.Layer.Layer property) (analogvnn.nn.module.Model.Model property) use_cpu() (analogvnn.utils.is_cpu_cuda.CPUCuda method) use_cuda_if_available() (analogvnn.utils.is_cpu_cuda.CPUCuda method) V variance (analogvnn.nn.noise.GaussianNoise.GaussianNoise property) (analogvnn.nn.noise.LaplacianNoise.LaplacianNoise property) (analogvnn.nn.noise.UniformNoise.UniformNoise property) W weight (analogvnn.nn.Linear.Linear attribute)