Index

_

__abs__() (tensornn.tensor.Tensor method) __add__() (tensornn.nn.NeuralNetwork method) (tensornn.tensor.Tensor method) __and__() (tensornn.tensor.Tensor method) __array__() (tensornn.tensor.Tensor method) __array_finalize__() (tensornn.tensor.Tensor method) __array_function__() (tensornn.tensor.Tensor method) __array_interface__ (tensornn.tensor.Tensor attribute) __array_namespace__() (tensornn.tensor.Tensor method) __array_priority__ (tensornn.tensor.Tensor attribute) __array_struct__ (tensornn.tensor.Tensor attribute) __array_ufunc__() (tensornn.tensor.Tensor method) __array_wrap__() (tensornn.tensor.Tensor method) __bool__() (tensornn.tensor.Tensor method) __buffer__() (tensornn.tensor.Tensor method) __class_getitem__() (tensornn.tensor.Tensor class method) __complex__() (tensornn.tensor.Tensor method) __contains__() (tensornn.tensor.Tensor method) __copy__() (tensornn.tensor.Tensor method) __deepcopy__() (tensornn.tensor.Tensor method) __delitem__() (tensornn.tensor.Tensor method) __divmod__() (tensornn.tensor.Tensor method) __dlpack__() (tensornn.tensor.Tensor method) __dlpack_device__() (tensornn.tensor.Tensor method) __eq__() (tensornn.tensor.Tensor method) __float__() (tensornn.tensor.Tensor method) __floordiv__() (tensornn.tensor.Tensor method) __format__() (tensornn.tensor.Tensor method) __ge__() (tensornn.tensor.Tensor method) __getitem__() (tensornn.tensor.Tensor method) __gt__() (tensornn.tensor.Tensor method) __hash__ (tensornn.tensor.Tensor attribute) __iadd__() (tensornn.tensor.Tensor method) __iand__() (tensornn.tensor.Tensor method) __ifloordiv__() (tensornn.tensor.Tensor method) __ilshift__() (tensornn.tensor.Tensor method) __imatmul__() (tensornn.tensor.Tensor method) __imod__() (tensornn.tensor.Tensor method) __imul__() (tensornn.tensor.Tensor method) __index__() (tensornn.tensor.Tensor method) __init__() (tensornn.activation.ELU method) (tensornn.activation.LeakyReLU method) (tensornn.activation.NewtonsSerpentine method) (tensornn.layers.Convolutional method) (tensornn.layers.Dense method) (tensornn.layers.Input method) (tensornn.layers.Layer method) (tensornn.nn.NeuralNetwork method) (tensornn.optimizers.Adam method) (tensornn.optimizers.Optimizer method) (tensornn.optimizers.RMSProp method) (tensornn.optimizers.SGD method) __int__() (tensornn.tensor.Tensor method) __invert__() (tensornn.tensor.Tensor method) __ior__() (tensornn.tensor.Tensor method) __ipow__() (tensornn.tensor.Tensor method) __irshift__() (tensornn.tensor.Tensor method) __isub__() (tensornn.tensor.Tensor method) __iter__() (tensornn.tensor.Tensor method) __itruediv__() (tensornn.tensor.Tensor method) __ixor__() (tensornn.tensor.Tensor method) __le__() (tensornn.tensor.Tensor method) __len__() (tensornn.tensor.Tensor method) __lshift__() (tensornn.tensor.Tensor method) __lt__() (tensornn.tensor.Tensor method)

__matmul__() (tensornn.tensor.Tensor method) __mod__() (tensornn.tensor.Tensor method) __mul__() (tensornn.tensor.Tensor method) __ne__() (tensornn.tensor.Tensor method) __neg__() (tensornn.tensor.Tensor method) __new__() (tensornn.tensor.Tensor static method) __or__() (tensornn.tensor.Tensor method) __pos__() (tensornn.tensor.Tensor method) __pow__() (tensornn.tensor.Tensor method) __radd__() (tensornn.tensor.Tensor method) __rand__() (tensornn.tensor.Tensor method) __rdivmod__() (tensornn.tensor.Tensor method) __reduce__() (tensornn.tensor.Tensor method) __reduce_ex__() (tensornn.tensor.Tensor method) __repr__() (tensornn.activation.Activation method) (tensornn.activation.ELU method) (tensornn.activation.LeakyReLU method) (tensornn.activation.LecunTanh method) (tensornn.activation.NewtonsSerpentine method) (tensornn.activation.NoActivation method) (tensornn.activation.ReLU method) (tensornn.activation.Sigmoid method) (tensornn.activation.Softmax method) (tensornn.activation.Swish method) (tensornn.activation.Tanh method) (tensornn.layers.Convolutional method) (tensornn.layers.Dense method) (tensornn.layers.Input method) (tensornn.layers.Layer method) (tensornn.loss.BinaryCrossEntropy method) (tensornn.loss.CategoricalCrossEntropy method) (tensornn.loss.Loss method) (tensornn.loss.MeanAbsoluteError method) (tensornn.loss.MeanSquaredError method) (tensornn.loss.MeanSquaredLogarithmicError method) (tensornn.loss.Poisson method) (tensornn.loss.ResidualSumOfSquares method) (tensornn.loss.RootMeanSquaredError method) (tensornn.loss.SquaredHinge method) (tensornn.nn.NeuralNetwork method) (tensornn.optimizers.Adam method) (tensornn.optimizers.Optimizer method) (tensornn.optimizers.RMSProp method) (tensornn.optimizers.SGD method) (tensornn.tensor.Tensor method) (tensornn.utils.TensorNNObject method) __rfloordiv__() (tensornn.tensor.Tensor method) __rlshift__() (tensornn.tensor.Tensor method) __rmatmul__() (tensornn.tensor.Tensor method) __rmod__() (tensornn.tensor.Tensor method) __rmul__() (tensornn.tensor.Tensor method) __ror__() (tensornn.tensor.Tensor method) __rpow__() (tensornn.tensor.Tensor method) __rrshift__() (tensornn.tensor.Tensor method) __rshift__() (tensornn.tensor.Tensor method) __rsub__() (tensornn.tensor.Tensor method) __rtruediv__() (tensornn.tensor.Tensor method) __rxor__() (tensornn.tensor.Tensor method) __setitem__() (tensornn.tensor.Tensor method) __setstate__() (tensornn.tensor.Tensor method) __sizeof__() (tensornn.tensor.Tensor method) __str__() (tensornn.tensor.Tensor method) __sub__() (tensornn.tensor.Tensor method) __truediv__() (tensornn.tensor.Tensor method) __xor__() (tensornn.tensor.Tensor method)

A

Activation (class in tensornn.activation), [1] activation (tensornn.layers.Layer attribute) Adam (class in tensornn.optimizers), [1] add() (tensornn.nn.NeuralNetwork method), [1] all() (tensornn.tensor.Tensor method) any() (tensornn.tensor.Tensor method)

argmax() (tensornn.tensor.Tensor method) argmin() (tensornn.tensor.Tensor method) argpartition() (tensornn.tensor.Tensor method) argsort() (tensornn.tensor.Tensor method) astype() (tensornn.tensor.Tensor method) atleast_2d() (in module tensornn.utils)

B

b_init (tensornn.layers.Dense attribute) backward() (tensornn.layers.Convolutional method) (tensornn.layers.Dense method), [1] (tensornn.layers.Input method), [1] (tensornn.layers.Layer method), [1] (tensornn.nn.NeuralNetwork method), [1]

base (tensornn.tensor.Tensor attribute) BCE (in module tensornn.loss) biases (tensornn.layers.Layer attribute) BinaryCrossEntropy (class in tensornn.loss) byteswap() (tensornn.tensor.Tensor method)

C

calculate() (tensornn.loss.BinaryCrossEntropy method) (tensornn.loss.CategoricalCrossEntropy method), [1] (tensornn.loss.Loss method), [1] (tensornn.loss.MeanAbsoluteError method) (tensornn.loss.MeanSquaredError method) (tensornn.loss.MeanSquaredLogarithmicError method) (tensornn.loss.Poisson method), [1] (tensornn.loss.ResidualSumOfSquares method) (tensornn.loss.RootMeanSquaredError method) (tensornn.loss.SquaredHinge method), [1] calculated (tensornn.layers.Dense attribute)

CategoricalCrossEntropy (class in tensornn.loss), [1] CCE (in module tensornn.loss) choose() (tensornn.tensor.Tensor method) clip() (tensornn.tensor.Tensor method) compress() (tensornn.tensor.Tensor method) conj() (tensornn.tensor.Tensor method) conjugate() (tensornn.tensor.Tensor method) Convolutional (class in tensornn.layers) copy() (tensornn.tensor.Tensor method) ctypes (tensornn.tensor.Tensor attribute) cumprod() (tensornn.tensor.Tensor method) cumsum() (tensornn.tensor.Tensor method)

D

data (tensornn.tensor.Tensor attribute) Dense (class in tensornn.layers), [1] derivative() (tensornn.activation.Activation method), [1] (tensornn.activation.ELU method), [1] (tensornn.activation.LeakyReLU method), [1] (tensornn.activation.LecunTanh method), [1] (tensornn.activation.NewtonsSerpentine method), [1] (tensornn.activation.NoActivation method), [1] (tensornn.activation.ReLU method), [1] (tensornn.activation.Sigmoid method), [1] (tensornn.activation.Softmax method), [1] (tensornn.activation.Swish method), [1] (tensornn.activation.Tanh method), [1] (tensornn.loss.BinaryCrossEntropy method) (tensornn.loss.CategoricalCrossEntropy method), [1] (tensornn.loss.Loss method), [1] (tensornn.loss.MeanAbsoluteError method) (tensornn.loss.MeanSquaredError method) (tensornn.loss.MeanSquaredLogarithmicError method) (tensornn.loss.Poisson method) (tensornn.loss.ResidualSumOfSquares method) (tensornn.loss.RootMeanSquaredError method) (tensornn.loss.SquaredHinge method)

diagonal() (tensornn.tensor.Tensor method) dot() (tensornn.tensor.Tensor method) dtype (tensornn.tensor.Tensor attribute) dump() (tensornn.tensor.Tensor method) dumps() (tensornn.tensor.Tensor method)

E

ELU (class in tensornn.activation), [1]

F

fill() (tensornn.tensor.Tensor method) flags (tensornn.tensor.Tensor attribute) flat (tensornn.tensor.Tensor attribute) flatten() (in module tensornn.utils), [1] (tensornn.tensor.Tensor method) forward() (tensornn.activation.Activation method), [1] (tensornn.activation.ELU method), [1] (tensornn.activation.LeakyReLU method), [1] (tensornn.activation.LecunTanh method), [1] (tensornn.activation.NewtonsSerpentine method), [1] (tensornn.activation.NoActivation method), [1] (tensornn.activation.ReLU method), [1] (tensornn.activation.Sigmoid method), [1] (tensornn.activation.Softmax method), [1] (tensornn.activation.Swish method), [1] (tensornn.activation.Tanh method), [1] (tensornn.layers.Convolutional method) (tensornn.layers.Dense method), [1] (tensornn.layers.Input method), [1] (tensornn.layers.Layer method), [1] (tensornn.nn.NeuralNetwork method), [1]

G

get_loss() (tensornn.nn.NeuralNetwork method), [1] get_minibatches() (tensornn.nn.NeuralNetwork method), [1] getfield() (tensornn.tensor.Tensor method) grad_biases (tensornn.layers.Dense attribute) (tensornn.layers.Layer attribute)

grad_weights (tensornn.layers.Dense attribute) (tensornn.layers.Layer attribute) gradients (tensornn.layers.Layer attribute)

I

imag (tensornn.tensor.Tensor attribute) InitializationError, [1] Input (class in tensornn.layers), [1]

InputDimError, [1] inputs (tensornn.layers.Dense attribute) item() (tensornn.tensor.Tensor method) itemsize (tensornn.tensor.Tensor attribute)

L

Layer (class in tensornn.layers), [1] LeakyReLU (class in tensornn.activation), [1] learning_rate (tensornn.optimizers.Optimizer attribute)

LecunTanh (class in tensornn.activation), [1] load() (tensornn.nn.NeuralNetwork class method), [1] Loss (class in tensornn.loss), [1]

M

MAE (in module tensornn.loss), [1] max() (tensornn.tensor.Tensor method) mean() (tensornn.tensor.Tensor method) MeanAbsoluteError (class in tensornn.loss) MeanSquaredError (class in tensornn.loss) MeanSquaredLogarithmicError (class in tensornn.loss) min() (tensornn.tensor.Tensor method) model (tensornn.optimizers.Optimizer attribute) module tensornn.activation tensornn.debug tensornn.errors tensornn.layers tensornn.loss tensornn.nn tensornn.optimizers tensornn.tensor tensornn.utils

momentum (tensornn.optimizers.SGD attribute) MSE (in module tensornn.loss), [1] MSLE (in module tensornn.loss), [1] mT (tensornn.tensor.Tensor attribute)

N

nbytes (tensornn.tensor.Tensor attribute) ndim (tensornn.tensor.Tensor attribute) NeuralNetwork (class in tensornn.nn), [1] neurons (tensornn.layers.Layer attribute)

NewtonsSerpentine (class in tensornn.activation), [1] NoActivation (class in tensornn.activation), [1] nonzero() (tensornn.tensor.Tensor method) normalize() (in module tensornn.utils), [1] NotRegisteredError, [1]

O

one_hot() (in module tensornn.utils), [1]

Optimizer (class in tensornn.optimizers), [1]

P

partition() (tensornn.tensor.Tensor method) Poisson (class in tensornn.loss), [1] predict() (tensornn.nn.NeuralNetwork method), [1]

prod() (tensornn.tensor.Tensor method) put() (tensornn.tensor.Tensor method) Python Enhancement Proposals PEP 585

R

ravel() (tensornn.tensor.Tensor method) real (tensornn.tensor.Tensor attribute) register() (tensornn.layers.Convolutional method) (tensornn.layers.Dense method), [1] (tensornn.layers.Input method), [1] (tensornn.layers.Layer method), [1] (tensornn.nn.NeuralNetwork method), [1] (tensornn.optimizers.Adam method), [1] (tensornn.optimizers.Optimizer method), [1] (tensornn.optimizers.RMSProp method), [1] (tensornn.optimizers.SGD method), [1] ReLU (class in tensornn.activation), [1] repeat() (tensornn.tensor.Tensor method) reset() (tensornn.optimizers.Adam method) (tensornn.optimizers.Optimizer method), [1] (tensornn.optimizers.RMSProp method) (tensornn.optimizers.SGD method)

reset_gradients() (tensornn.layers.Convolutional method) (tensornn.layers.Dense method) (tensornn.layers.Input method) (tensornn.layers.Layer method), [1] (tensornn.nn.NeuralNetwork method), [1] reshape() (tensornn.tensor.Tensor method) ResidualSumOfSquares (class in tensornn.loss) resize() (tensornn.tensor.Tensor method) RMSE (in module tensornn.loss), [1] RMSProp (class in tensornn.optimizers), [1] RootMeanSquaredError (class in tensornn.loss) round() (tensornn.tensor.Tensor method) RSS (in module tensornn.loss), [1]

S

save() (tensornn.nn.NeuralNetwork method), [1] searchsorted() (tensornn.tensor.Tensor method) set_lr() (tensornn.optimizers.Adam method) (tensornn.optimizers.Optimizer method), [1] (tensornn.optimizers.RMSProp method) (tensornn.optimizers.SGD method) set_seed() (in module tensornn.utils), [1] setfield() (tensornn.tensor.Tensor method) setflags() (tensornn.tensor.Tensor method) SGD (class in tensornn.optimizers), [1] shape (tensornn.tensor.Tensor attribute) SHL (in module tensornn.loss) Sigmoid (class in tensornn.activation), [1] simple() (tensornn.nn.NeuralNetwork class method), [1] size (tensornn.tensor.Tensor attribute) Softmax (class in tensornn.activation), [1]

sort() (tensornn.tensor.Tensor method) source() (in module tensornn.utils), [1] SquaredHinge (class in tensornn.loss), [1] squeeze() (tensornn.tensor.Tensor method) std() (tensornn.tensor.Tensor method) step() (tensornn.layers.Convolutional method) (tensornn.layers.Dense method), [1] (tensornn.layers.Input method), [1] (tensornn.layers.Layer method), [1] (tensornn.optimizers.Adam method), [1] (tensornn.optimizers.Optimizer method), [1] (tensornn.optimizers.RMSProp method), [1] (tensornn.optimizers.SGD method), [1] strides (tensornn.tensor.Tensor attribute) sum() (tensornn.tensor.Tensor method) swapaxes() (tensornn.tensor.Tensor method) Swish (class in tensornn.activation), [1]

T

T (tensornn.tensor.Tensor attribute) take() (tensornn.tensor.Tensor method) Tanh (class in tensornn.activation), [1] Tensor (class in tensornn.tensor), [1] tensornn.activation module tensornn.debug module tensornn.errors module tensornn.layers module tensornn.loss module tensornn.nn module

tensornn.optimizers module tensornn.tensor module tensornn.utils module TensorNNObject (class in tensornn.utils) tmp_str() (tensornn.tensor.Tensor method), [1] to_device() (tensornn.tensor.Tensor method) tobytes() (tensornn.tensor.Tensor method) tofile() (tensornn.tensor.Tensor method) tolist() (tensornn.tensor.Tensor method) trace() (tensornn.tensor.Tensor method) train() (tensornn.nn.NeuralNetwork method), [1] transpose() (tensornn.tensor.Tensor method)

U

update_log() (tensornn.nn.NeuralNetwork method), [1]

V

var() (tensornn.tensor.Tensor method) velocities_b (tensornn.optimizers.SGD attribute)

velocities_w (tensornn.optimizers.SGD attribute) view() (tensornn.tensor.Tensor method)

W

w_init (tensornn.layers.Dense attribute)

weights (tensornn.layers.Layer attribute)