Index

_

_cache (nets.nn.modules.dnn.DNN attribute)

_parameters (nets.nn.modules.dnn.DNN attribute)

A

Activation (class in nets.nn.activation) activation_hidden (nets.nn.modules.dnn.DNN attribute) activation_output (nets.nn.modules.dnn.DNN attribute) Adagrad (class in nets.optim.adagrad) Adam (class in nets.optim.adam) add() (in module nets.autograd.ops) (nets.nn.modules.module.Module method)

append() (in module nets.autograd.numeric) (nets.tensor.Tensor method) append2dict() (in module nets.utils.functions) argmax() (in module nets.autograd.numeric) astype() (nets.tensor.Tensor method)

B

backward() (nets.nn.activation.Activation method) (nets.nn.activation.Softmax method) (nets.nn.loss.CrossEntropyLoss method) (nets.nn.loss.MSELoss method) (nets.nn.modules.conv.Conv2d method) (nets.nn.modules.dnn.DNN method) (nets.nn.modules.dropout.Dropout method) (nets.nn.modules.linear.Linear method) (nets.nn.modules.module.Module method) (nets.nn.modules.pool.MaxPool2d method) (nets.nn.modules.rnn.RNN method) (nets.nn.modules.sequential.Sequential method) (nets.optim.optimizer.Optimizer method) (nets.tensor.Tensor method)

BackwardCallError Batch (class in nets.data.batch)

C

cache() (nets.nn.modules.module.Module method) CIFAR10 (class in nets.datasets.cifar)

concatenate() (in module nets.autograd.numeric) Conv2d (class in nets.nn.modules.conv) CrossEntropyLoss (class in nets.nn.loss)

D

Dataset (class in nets.data.dataset) describe_stats() (in module nets.utils.display) detach() (nets.tensor.Tensor method) div() (in module nets.autograd.ops)

DNN (class in nets.nn.modules.dnn) dot() (in module nets.autograd.ops) download() (nets.data.dataset.Dataset class method) Dropout (class in nets.nn.modules.dropout) dropout() (in module nets.nn.functional)

E

eq() (in module nets.autograd.ops) eval() (nets.nn.modules.module.Module method)

evaluate() (nets.solver.solver.Solver method) Example (class in nets.data.example) exp() (in module nets.autograd.functions)

F

Field (class in nets.data.example) flatten() (in module nets.autograd.numeric) (nets.tensor.Tensor method) forward() (nets.nn.activation.Activation method) (nets.nn.activation.Softmax method) (nets.nn.loss.CrossEntropyLoss method) (nets.nn.loss.Loss method) (nets.nn.loss.MSELoss method) (nets.nn.modules.conv.Conv2d method) (nets.nn.modules.dnn.DNN method) (nets.nn.modules.dropout.Dropout method) (nets.nn.modules.linear.Linear method) (nets.nn.modules.module.Module method) (nets.nn.modules.pool.MaxPool2d method) (nets.nn.modules.rnn.RNN method) (nets.nn.modules.sequential.Sequential method)

fromlist() (nets.data.example.Example class method)

G

ge() (in module nets.autograd.ops) get_accuracy() (nets.solver.solver.Solver method) get_metrics() (in module nets.solver.solver)

get_name() (nets.nn.modules.module.Module method) get_time() (in module nets.utils.display) gradients() (nets.nn.modules.module.Module method) gt() (in module nets.autograd.ops)

H

hidden_dimensions (nets.nn.modules.dnn.DNN attribute)

Hook (class in nets.autograd.hook)

I

init_parameters() (nets.nn.modules.dnn.DNN method) init_params() (nets.nn.modules.linear.Linear method) inner_repr() (nets.nn.modules.conv.Conv2d method) (nets.nn.modules.linear.Linear method) (nets.nn.modules.module.Module method) (nets.nn.modules.pool.MaxPool2d method)

inverse() (in module nets.autograd.ops) item() (nets.tensor.Tensor method) Iterator (class in nets.data.iterator)

L

layer_dimensions (nets.nn.modules.dnn.DNN attribute) le() (in module nets.autograd.ops) leaky_relu() (in module nets.autograd.functions) leaky_relu_prime() (in module nets.autograd.functions) LeakyReLU (class in nets.nn.activation)

Linear (class in nets.nn.modules.linear) load_state() (nets.nn.modules.module.Module method) log() (in module nets.autograd.functions) Loss (class in nets.nn.loss) lt() (in module nets.autograd.ops)

M

max() (in module nets.autograd.numeric) maximum() (in module nets.autograd.functions) MaxPool2d (class in nets.nn.modules.pool) minimum() (in module nets.autograd.functions)

MNIST (class in nets.datasets.mnist) Module (class in nets.nn.modules.module) modules() (nets.nn.modules.module.Module method) MSELoss (class in nets.nn.loss) multiply() (in module nets.autograd.ops)

N

ne() (in module nets.autograd.ops) neg() (in module nets.autograd.ops) nets.autograd.functions (module) nets.autograd.hook (module) nets.autograd.numeric (module) nets.autograd.ops (module) nets.autograd.parameter (module) nets.data.batch (module) nets.data.dataset (module) nets.data.example (module) nets.data.iterator (module) nets.datasets.cifar (module) nets.datasets.mnist (module) nets.datasets.svhn (module) nets.functional (module) nets.nn.activation (module) nets.nn.functional (module) nets.nn.loss (module) nets.nn.modules.conv (module) nets.nn.modules.dnn (module)

nets.nn.modules.dropout (module) nets.nn.modules.linear (module) nets.nn.modules.module (module) nets.nn.modules.pool (module) nets.nn.modules.rnn (module) nets.nn.modules.rnnbase (module) nets.nn.modules.sequential (module) nets.nn.utils (module) nets.numeric (module) nets.optim.adagrad (module) nets.optim.adam (module) nets.optim.optimizer (module) nets.optim.rmsprop (module) nets.optim.sgd (module) nets.solver.solver (module) nets.tensor (module) nets.utils.display (module) nets.utils.errors (module) nets.utils.functions (module) normal() (nets.autograd.parameter.Parameter class method) numpy() (nets.tensor.Tensor method)

O

one_hot() (in module nets.nn.utils)

Optimizer (class in nets.optim.optimizer) orthogonal() (nets.autograd.parameter.Parameter class method)

P

pad() (in module nets.autograd.numeric) Parameter (class in nets.autograd.parameter) parameters() (nets.nn.modules.module.Module method)

pow() (in module nets.autograd.functions) process() (nets.data.example.Field method) progress_bar() (in module nets.utils.display)

R

register_hook() (nets.tensor.Tensor method) ReLU (class in nets.nn.activation) relu() (in module nets.autograd.functions) relu_prime() (in module nets.autograd.functions) reset() (nets.solver.solver.Solver method)

reshape() (in module nets.autograd.numeric) (nets.tensor.Tensor method) RMSprop (class in nets.optim.rmsprop) RNN (class in nets.nn.modules.rnn) RNNBase (class in nets.nn.modules.rnnbase) run() (nets.solver.solver.Solver method)

S

save() (nets.nn.modules.module.Module method) (nets.solver.solver.Solver method) save_dict() (nets.nn.modules.module.Module method) scaled_weight() (nets.autograd.parameter.Parameter class method) Sequential (class in nets.nn.modules.sequential) set_hidden_0() (nets.nn.modules.rnn.RNN method) SGD (class in nets.optim.sgd) Sigmoid (class in nets.nn.activation) sigmoid() (in module nets.autograd.functions) sigmoid_prime() (in module nets.autograd.functions) slice() (in module nets.autograd.ops) Softmax (class in nets.nn.activation) softmax() (in module nets.autograd.functions)

Solver (class in nets.solver.solver) splits() (nets.datasets.cifar.CIFAR10 class method) (nets.datasets.mnist.MNIST class method) sqrt() (in module nets.autograd.functions) state_dict() (nets.nn.modules.module.Module method) step() (nets.optim.adagrad.Adagrad method) (nets.optim.adam.Adam method) (nets.optim.optimizer.Optimizer method) (nets.optim.rmsprop.RMSprop method) (nets.optim.sgd.SGD method) sub() (in module nets.autograd.ops) sum() (in module nets.autograd.ops) (nets.tensor.Tensor method)

T

Tanh (class in nets.nn.activation) tanh() (in module nets.autograd.functions) tanh_prime() (in module nets.autograd.functions) Tensor (class in nets.tensor) to_array() (in module nets.tensor) to_tensor() (in module nets.tensor)

tolist() (nets.tensor.Tensor method) train() (nets.nn.modules.module.Module method) (nets.solver.solver.Solver method) training (nets.nn.modules.dnn.DNN attribute) transpose() (in module nets.autograd.numeric) (nets.tensor.Tensor method)

U

uniform() (nets.autograd.parameter.Parameter class method)

W

where() (in module nets.autograd.functions)

Z

zero_grad() (nets.nn.modules.module.Module method) (nets.optim.optimizer.Optimizer method) (nets.tensor.Tensor method)

zeros() (nets.autograd.parameter.Parameter class method)