torch0.13.0 package

Matrix_rank

Pdist

Randperm

Roll

Rot90

Round

Rrelu_

Rsqrt

Saves an object to a disk file.

Scalar tensor

Creates a tensor from a buffer of memory

Tensordot

Threshold_

Topk

Trace

Transpose

Trapz

Unique_consecutive

Unsafe_chunk

Unsafe_split

Unsqueeze

Vander

Add

Argmin

Argsort

Combinations

Complex

Conj

Conv_tbc

Det

Create a Device object

Diag

Divide

Dot

Dstack

Torch data types

Eig

In-place version of torch_index_put.

Index_select

A simple exported version of install_path Returns the torch installati...

Inverse

Is_complex

Is_floating_point

Verifies if torch is installed

Is_nonzero

Logaddexp

Logaddexp2

Logcumsumexp

Logdet

Logical_and

Logical_not

Logical_or

Logical_xor

Logit

Sets the seed for generating random numbers.

Masked_select

Matmul

Matrix_exp

Matrix_power

Empty cache

Returns the major and minor CUDA capability of device

Returns a bool indicating if CUDA is currently available.

Returns a dictionary of CUDA memory allocator statistics for a given d...

Returns the CUDA runtime version

Waits for all kernels in all streams on a CUDA device to complete.

Data loader. Combines a dataset and a sampler, and provides single- or...

Creates an iterator from a DataLoader

Get the next element of a dataloader iterator

Saves a script_function or script_module in bytecode form, to be l...

Adds the 'jit_scalar' class to the input

Trace a function and return an executable script_function.

Applies a 2D adaptive average pooling over an input signal composed of...

Applies a 3D adaptive average pooling over an input signal composed of...

AdaptiveLogSoftmaxWithLoss module

Applies a 1D adaptive max pooling over an input signal composed of sev...

Truncated normal initialization

Uniform initialization

Xavier normal initialization

Xavier uniform initialization

Zeros initialization

LogSigmoid module

LogSoftmax module

Threshold module

Adaptive_max_pool2d

Adaptive_max_pool3d

Affine_grid

Alpha_dropout

Avg_pool1d

Conv_tbc

Glu

Lp_pool2d

Margin_ranking_loss

Max_pool1d

Max_pool2d

Max_pool3d

Max_unpool1d

Max_unpool2d

Max_unpool3d

Mse_loss

One_hot

Smooth_l1_loss

Soft_margin_loss

Softmax

Softmin

Softplus

Softshrink

Softsign

Tanhshrink

Threshold

Acosh

Adaptive_avg_pool1d

MPS is available

OpenMP is available

Absolute

Greater

Greater_equal

Dataset wrapping tensors.

Acos

Dequantize

Log2

Negative

Unbind

Tanh module

Tanhshrink module

Adaptive_avg_pool3d

Saves a script_function to a path

BatchNorm2D

BatchNorm3D

Erfc

Erfinv

Exp

Exp2

Expm1

Converts to array

MKLDNN is available

Qr

Creates the corresponding Scheme object

Computes the sum of gradients of given tensors w.r.t. graph leaves.

Records operation history and defines formulas for differentiating ops...

Computes and returns the sum of gradients of outputs w.r.t. the inputs...

Set grad mode

Class representing the context.

CuDNN is available

CuDNN version

MKL is available

Given a list of values (possibly containing numbers), returns a list w...

Call a (Potentially Unexported) Torch Function

Clone a torch module.

Abstract base class for constraints.

Contrib sort vertices

Creates a gradient scaler

Returns the index of a currently selected device.

Returns the number of GPUs available.

Helper function to create an function that generates R6 instances of c...

Dataset Subset

Gets and sets the default floating point dtype.

Creates a Bernoulli distribution parameterized by probsor logits (...

Creates a categorical distribution parameterized by either probs or ...

Creates a Chi2 distribution parameterized by shape parameter df. Thi...

Creates a Gamma distribution parameterized by shape concentration an...

Mixture of components in the same family

Gaussian distribution

Creates a normal (also called Gaussian) distribution parameterized by ...

Creates a Poisson distribution parameterized by rate, the rate param...

Generic R6 class representing distributions

Enumerate an iterator

Enumerate an iterator

Install Torch

Install Torch from files

Checks if the object is a dataloader

Checks if the object is a nn_buffer

Checks if the object is an nn_module

Checks if an object is a nn_parameter

Checks if the object is a torch optimizer

Checks if object is a device

Check if object is a torch data type

Check if an object is a torch layout.

Check if an object is a memory format

Checks if an object is a QScheme

Checks if a tensor is undefined

Creates an iterable dataset

Compile TorchScript code into a graph

Loads a script_function or script_module previously saved with `ji...

Enable idiomatic access to JIT operators from R.

Trace a module

Adds the 'jit_tuple' class to the input

Computes the Cholesky decomposition of a complex Hermitian or real sym...

Computes the Cholesky decomposition of a complex Hermitian or real sym...

Computes the condition number of a matrix with respect to a matrix nor...

Computes the determinant of a square matrix.

Computes the eigenvalue decomposition of a square matrix if it exists.

Computes the eigenvalue decomposition of a complex Hermitian or real s...

Computes the eigenvalues of a square matrix.

Computes the eigenvalues of a complex Hermitian or real symmetric matr...

Computes the first n columns of a product of Householder matrices.

Hardsigmoid module

Computes the inverse of a square matrix if it exists.

Computes the inverse of a square matrix if it is invertible.

Computes a solution to the least squares problem of a system of linear...

Computes a matrix norm.

Computes the n-th power of a square matrix for an integer n.

Hardswish module

Computes the numerical rank of a matrix.

Efficiently multiplies two or more matrices

Computes a vector or matrix norm.

Computes the pseudoinverse (Moore-Penrose inverse) of a matrix.

Computes the QR decomposition of a matrix.

Hardtanh module

Computes the sign and natural logarithm of the absolute value of the d...

Computes the solution of a square system of linear equations with a un...

Triangular solve

Computes the singular value decomposition (SVD) of a matrix.

Computes the singular values of a matrix.

Computes the multiplicative inverse of torch_tensordot()

Computes the solution X to the system torch_tensordot(A, X) = B.

Computes a vector norm.

Load a state dict file

Autocast context manager

Device contexts

Set the learning rate of each parameter group using a cosine annealing...

Ones initialization

Sets the learning rate of each parameter group to the initial lr times...

Multiply the learning rate of each parameter group by the factor given...

Once cycle learning rate

Reduce learning rate on plateau

Creates learning rate schedulers

Step learning rate decay

Applies a 1D adaptive average pooling over an input signal composed of...

Applies a 2D adaptive max pooling over an input signal composed of sev...

Applies a 3D adaptive max pooling over an input signal composed of sev...

Applies a 1D average pooling over an input signal composed of several ...

Applies a 2D average pooling over an input signal composed of several ...

Applies a 3D average pooling over an input signal composed of several ...

BatchNorm1D module

Binary cross entropy loss

BCE with logits loss

Bilinear module

Creates a nn_buffer

CELU module

Sparsemax activation

ConvTranspose1D

ConvTranpose2D module

ConvTranpose3D module

Conv1D module

Conv2D module

Conv3D module

Adaptive_max_pool1d

Cosine embedding loss

CrossEntropyLoss module

The Connectionist Temporal Classification loss.

Dropout module

Dropout2D module

Orthogonal initialization

Dropout3D module

ELU module

Embedding module

Embedding bag module

Flattens a contiguous range of dims into a tensor.

Sparse initialization

Applies a 2D fractional max pooling over an input signal composed of s...

Applies a 3D fractional max pooling over an input signal composed of s...

GELU module

GLU module

Group normalization

Applies a multi-layer gated recurrent unit (GRU) RNN to an input seque...

Hardshwink module

Hinge embedding loss

Identity module

Calculate gain

Constant initialization

Dirac initialization

Eye initialization

Kaiming normal initialization

Kaiming uniform initialization

Normal initialization

Kullback-Leibler divergence loss

L1 loss

Layer normalization

LeakyReLU module

Linear module

Ceil

Applies a 1D power-average pooling over an input signal composed of se...

Applies a 2D power-average pooling over an input signal composed of se...

Applies a multi-layer long short-term memory (LSTM) RNN to an input se...

Margin ranking loss

MaxPool1D module

Softsign module

MaxPool2D module

Applies a 3D max pooling over an input signal composed of several inpu...

Computes a partial inverse of MaxPool1d.

Computes a partial inverse of MaxPool2d.

Computes a partial inverse of MaxPool3d.

Base class for all neural network modules.

Container that allows named values

Holds submodules in a list.

MSE loss

Multi margin loss

Applies the Sigmoid Linear Unit (SiLU) function, element-wise. The SiL...

Celu

MultiHead attention

Multilabel margin loss

Multi label soft margin loss

Nll loss

Pairwise distance

Creates an nn_parameter

Poisson NLL loss

PReLU module

Prune top layer(s) of a network

ReLU module

ReLu6 module

RNN module

RReLU module

SELU module

A sequential container

Sigmoid module

Celu_

Smooth L1 loss

Soft margin loss

Softmax module

Softmax2d module

Softmin

Softplus module

Softshrink module

Triplet margin loss

Triplet margin with distance loss

Unflattens a tensor dim expanding it to a desired shape. For use with ...

Upsample module

Clips gradient norm of an iterable of parameters.

Clips gradient of an iterable of parameters at specified value.

Packs a Tensor containing padded sequences of variable length.

Packs a list of variable length Tensors

Pads a packed batch of variable length sequences.

Pad a list of variable length Tensors with padding_value

nn_utils_weight_norm

Adaptive_avg_pool1d

Adaptive_avg_pool2d

Avg_pool2d

Avg_pool3d

Batch_norm

Bilinear

Binary_cross_entropy

Binary_cross_entropy_with_logits

Celu

Sparsemax

Conv_transpose1d

Conv_transpose2d

Conv_transpose3d

Conv1d

Conv2d

Conv3d

Elu

Cosine_embedding_loss

Cosine_similarity

Cross_entropy

Ctc_loss

Dropout

Dropout2d

Dropout3d

Sigmoid

Embedding

Embedding_bag

Fold

Fractional_max_pool2d

Fractional_max_pool3d

Gelu

Outer

Grid_sample

Group_norm

Gumbel_softmax

Hardshrink

Hardsigmoid

Hardswish

Hardtanh

Hinge_embedding_loss

Instance_norm

Applies the Sigmoid Linear Unit (SiLU) function, element-wise. See `nn...

Interpolate

Kl_div

L1_loss

Layer_norm

Leaky_relu

Linear

Local_response_norm

Log_softmax

Logsigmoid

Lp_pool1d

Multi head attention forward

Multi_margin_loss

Multilabel_margin_loss

Multilabel_soft_margin_loss

Nll_loss

Normalize

Number of threads

Pad

Pairwise_distance

Pdist

Pixel_shuffle

Poisson_nll_loss

Prelu

Relu

Relu6

Rrelu

Selu

Triplet_margin_loss

Triplet margin with distance loss

Unfold

Adadelta optimizer

Adagrad optimizer

Abs

Implements Adam algorithm.

Implements AdamW algorithm

Averaged Stochastic Gradient Descent optimizer

LBFGS optimizer

Dummy value indicating a required value.

Creates a new Sampler

RMSprop optimizer

Implements the resilient backpropagation algorithm.

SGD optimizer

Creates a custom optimizer

Pipe operator

Re-exporting the as_iterator function.

Creates a slice

Addbmm

Addcdiv

Addcmul

Addmm

Addmv

Addr

Allclose

Amax

Amin

Angle

Arange

Arccos

Arccosh

Arcsin

Arcsinh

Arctan

Arctanh

Argmax

As_strided

Asin

Asinh

Atan

Atan2

Atanh

Atleast_1d

Atleast_2d

Atleast_3d

Avg_pool1d

Chain_matmul

Baddbmm

Bartlett_window

Bernoulli

Bincount

Bitwise_and

Bitwise_not

Bitwise_or

Bitwise_xor

Channel_shuffle

Blackman_window

Block_diag

Bmm

Broadcast_tensors

Bucketize

Can_cast

Cartesian_prod

Cat

Cdist

Cholesky

Cholesky_inverse

Cholesky_solve

Chunk

Clamp

Clip

Clone

Deg2rad

Conv_transpose1d

Conv_transpose2d

Conv_transpose3d

Conv1d

Conv2d

Conv3d

Cos

Cosh

Cosine_similarity

Count_nonzero

Cross

Cummax

Cummin

Cumprod

Cumsum

Diag_embed

Diagflat

Diagonal

Computes the n-th forward difference along the given dimension.

Digamma

Dist

Div

Einsum

Empty

Empty_like

Empty_strided

Eq

Equal

Erf

Eye

Fft

fftfreq

Ifft

Irfft

Gt

Rfft

Floating point type info

Fix

Flatten

Flip

Fliplr

Flipud

Floor

Floor_divide

Fmod

Frac

RNG state management

Full

Full_like

Gather

Gcd

Ge

Create a Generator object

Geqrf

Ger

Hamming_window

Hann_window

Heaviside

Histc

Hstack

Hypot

I0

Integer type info

Imag

Index torch tensors

Modify values selected by indices.

Isclose

Isfinite

Isinf

Isnan

Isneginf

Isposinf

Isreal

Istft

Kaiser_window

Kronecker product

Log1p

Kthvalue

Creates the corresponding layout

Lcm

Le

Lerp

Less

Less_equal

Lgamma

Linspace

Loads a saved object

Log

Log10

Logspace

Logsumexp

Lstsq

Lt

LU

Lu_solve

Lu_unpack

Max

Maximum

Mean

Median

Memory format

Meshgrid

Nextafter

Result_type

Min

Minimum

Mm

Mode

Movedim

Mul

Nonzero

Multinomial

Multiply

Mv

Mvlgamma

Nanquantile

Nansum

Narrow

Ne

Neg

Norm

Normal

Not_equal

Ones

Ones_like

Orgqr

Ormqr

Tanh

Pinverse

Pixel_shuffle

Poisson

Polar

Polygamma

Pow

Prod

Promote_types

Quantile

Quantize_per_channel

Quantize_per_tensor

Rad2deg

Rand

Rand_like

Randint

Randint_like

Randn

Randn_like

Range

Real

Reciprocal

Creates the reduction objet

Relu

Relu_

Remainder

Renorm

Repeat_interleave

Reshape

Searchsorted

Selu

Selu_

Serialize a torch object returning a raw object

Sgn

Sigmoid

Sign

Signbit

Sin

Sinh

Slogdet

Sort

Converts R objects to a torch tensor

Sparse_coo_tensor

Split

Sqrt

Square

Squeeze

Stack

Std

Std_mean

Stft

Sub

Subtract

Sum

Svd

T

Take

Tan

Triangular_solve

Tril

Tril_indices

Triu

Triu_indices

TRUE_divide

Trunc

Var

Var_mean

Vdot

View_as_complex

View_as_real

Vstack

Where

Zeros

Zeros_like

Context-manager that enable anomaly detection for the autograd engine.

Enable grad

Temporarily modify gradient recording.