AutogradContext         Class representing the context.
Constraint              Abstract base class for constraints.
Distribution            Generic R6 class representing distributions
OptimizerIgnite         Abstract Base Class for LibTorch Optimizers
as_array                Converts to array
autograd_backward       Computes the sum of gradients of given tensors
                        w.r.t. graph leaves.
autograd_function       Records operation history and defines formulas
                        for differentiating ops.
autograd_grad           Computes and returns the sum of gradients of
                        outputs w.r.t. the inputs.
autograd_set_grad_mode
                        Set grad mode
backends_cudnn_is_available
                        CuDNN is available
backends_cudnn_version
                        CuDNN version
backends_mkl_is_available
                        MKL is available
backends_mkldnn_is_available
                        MKLDNN is available
backends_mps_is_available
                        MPS is available
backends_openmp_is_available
                        OpenMP is available
broadcast_all           Given a list of values (possibly containing
                        numbers), returns a list where each value is
                        broadcasted based on the following rules:
clone_module            Clone a torch module.
contrib_sort_vertices   Contrib sort vertices
cuda_amp_grad_scaler    Creates a gradient scaler
cuda_current_device     Returns the index of a currently selected
                        device.
cuda_device_count       Returns the number of GPUs available.
cuda_dump_memory_snapshot
                        Save CUDA Memory State Snapshot to File
cuda_empty_cache        Empty cache
cuda_get_device_capability
                        Returns the major and minor CUDA capability of
                        'device'
cuda_is_available       Returns a bool indicating if CUDA is currently
                        available.
cuda_memory_snapshot    Capture CUDA Memory State Snapshot
cuda_memory_stats       Returns a dictionary of CUDA memory allocator
                        statistics for a given device.
cuda_record_memory_history
                        Enable Recording of Memory Allocation Stack
                        Traces
cuda_runtime_version    Returns the CUDA runtime version
cuda_synchronize        Waits for all kernels in all streams on a CUDA
                        device to complete.
dataloader              Data loader. Combines a dataset and a sampler,
                        and provides single- or multi-process iterators
                        over the dataset.
dataloader_make_iter    Creates an iterator from a DataLoader
dataloader_next         Get the next element of a dataloader iterator
dataset                 Helper function to create an function that
                        generates R6 instances of class 'dataset'
dataset_subset          Dataset Subset
distr_bernoulli         Creates a Bernoulli distribution parameterized
                        by 'probs' or 'logits' (but not both). Samples
                        are binary (0 or 1). They take the value '1'
                        with probability 'p' and '0' with probability
                        '1 - p'.
distr_categorical       Creates a categorical distribution
                        parameterized by either 'probs' or 'logits'
                        (but not both).
distr_chi2              Creates a Chi2 distribution parameterized by
                        shape parameter 'df'. This is exactly
                        equivalent to 'distr_gamma(alpha=0.5*df,
                        beta=0.5)'
distr_gamma             Creates a Gamma distribution parameterized by
                        shape 'concentration' and 'rate'.
distr_mixture_same_family
                        Mixture of components in the same family
distr_multivariate_normal
                        Gaussian distribution
distr_normal            Creates a normal (also called Gaussian)
                        distribution parameterized by 'loc' and
                        'scale'.
distr_poisson           Creates a Poisson distribution parameterized by
                        'rate', the rate parameter.
enumerate               Enumerate an iterator
enumerate.dataloader    Enumerate an iterator
get_install_libs_url    Install Torch from files
install_torch           Install Torch
is_dataloader           Checks if the object is a dataloader
is_nn_buffer            Checks if the object is a nn_buffer
is_nn_module            Checks if the object is an nn_module
is_nn_parameter         Checks if an object is a nn_parameter
is_optimizer            Checks if the object is a torch optimizer
is_torch_device         Checks if object is a device
is_torch_dtype          Check if object is a torch data type
is_torch_layout         Check if an object is a torch layout.
is_torch_memory_format
                        Check if an object is a memory format
is_torch_qscheme        Checks if an object is a QScheme
is_undefined_tensor     Checks if a tensor is undefined
iterable_dataset        Creates an iterable dataset
jit_compile             Compile TorchScript code into a graph
jit_load                Loads a 'script_function' or 'script_module'
                        previously saved with 'jit_save'
jit_ops                 Enable idiomatic access to JIT operators from
                        R.
jit_save                Saves a 'script_function' to a path
jit_save_for_mobile     Saves a 'script_function' or 'script_module' in
                        bytecode form, to be loaded on a mobile device
jit_scalar              Adds the 'jit_scalar' class to the input
jit_serialize           Serialize a Script Module
jit_trace               Trace a function and return an executable
                        'script_function'.
jit_trace_module        Trace a module
jit_tuple               Adds the 'jit_tuple' class to the input
jit_unserialize         Unserialize a Script Module
linalg_cholesky         Computes the Cholesky decomposition of a
                        complex Hermitian or real symmetric
                        positive-definite matrix.
linalg_cholesky_ex      Computes the Cholesky decomposition of a
                        complex Hermitian or real symmetric
                        positive-definite matrix.
linalg_cond             Computes the condition number of a matrix with
                        respect to a matrix norm.
linalg_det              Computes the determinant of a square matrix.
linalg_eig              Computes the eigenvalue decomposition of a
                        square matrix if it exists.
linalg_eigh             Computes the eigenvalue decomposition of a
                        complex Hermitian or real symmetric matrix.
linalg_eigvals          Computes the eigenvalues of a square matrix.
linalg_eigvalsh         Computes the eigenvalues of a complex Hermitian
                        or real symmetric matrix.
linalg_householder_product
                        Computes the first 'n' columns of a product of
                        Householder matrices.
linalg_inv              Computes the inverse of a square matrix if it
                        exists.
linalg_inv_ex           Computes the inverse of a square matrix if it
                        is invertible.
linalg_lstsq            Computes a solution to the least squares
                        problem of a system of linear equations.
linalg_matrix_norm      Computes a matrix norm.
linalg_matrix_power     Computes the 'n'-th power of a square matrix
                        for an integer 'n'.
linalg_matrix_rank      Computes the numerical rank of a matrix.
linalg_multi_dot        Efficiently multiplies two or more matrices
linalg_norm             Computes a vector or matrix norm.
linalg_pinv             Computes the pseudoinverse (Moore-Penrose
                        inverse) of a matrix.
linalg_qr               Computes the QR decomposition of a matrix.
linalg_slogdet          Computes the sign and natural logarithm of the
                        absolute value of the determinant of a square
                        matrix.
linalg_solve            Computes the solution of a square system of
                        linear equations with a unique solution.
linalg_solve_triangular
                        Triangular solve
linalg_svd              Computes the singular value decomposition (SVD)
                        of a matrix.
linalg_svdvals          Computes the singular values of a matrix.
linalg_tensorinv        Computes the multiplicative inverse of
                        'torch_tensordot()'
linalg_tensorsolve      Computes the solution 'X' to the system
                        'torch_tensordot(A, X) = B'.
linalg_vector_norm      Computes a vector norm.
load_state_dict         Load a state dict file
local_autocast          Autocast context manager
local_device            Device contexts
lr_cosine_annealing     Set the learning rate of each parameter group
                        using a cosine annealing schedule
lr_lambda               Sets the learning rate of each parameter group
                        to the initial lr times a given function. When
                        last_epoch=-1, sets initial lr as lr.
lr_multiplicative       Multiply the learning rate of each parameter
                        group by the factor given in the specified
                        function. When last_epoch=-1, sets initial lr
                        as lr.
lr_one_cycle            Once cycle learning rate
lr_reduce_on_plateau    Reduce learning rate on plateau
lr_scheduler            Creates learning rate schedulers
lr_step                 Step learning rate decay
nn_adaptive_avg_pool1d
                        Applies a 1D adaptive average pooling over an
                        input signal composed of several input planes.
nn_adaptive_avg_pool2d
                        Applies a 2D adaptive average pooling over an
                        input signal composed of several input planes.
nn_adaptive_avg_pool3d
                        Applies a 3D adaptive average pooling over an
                        input signal composed of several input planes.
nn_adaptive_log_softmax_with_loss
                        AdaptiveLogSoftmaxWithLoss module
nn_adaptive_max_pool1d
                        Applies a 1D adaptive max pooling over an input
                        signal composed of several input planes.
nn_adaptive_max_pool2d
                        Applies a 2D adaptive max pooling over an input
                        signal composed of several input planes.
nn_adaptive_max_pool3d
                        Applies a 3D adaptive max pooling over an input
                        signal composed of several input planes.
nn_aum_loss             AUM loss
nn_avg_pool1d           Applies a 1D average pooling over an input
                        signal composed of several input planes.
nn_avg_pool2d           Applies a 2D average pooling over an input
                        signal composed of several input planes.
nn_avg_pool3d           Applies a 3D average pooling over an input
                        signal composed of several input planes.
nn_batch_norm1d         BatchNorm1D module
nn_batch_norm2d         BatchNorm2D
nn_batch_norm3d         BatchNorm3D
nn_bce_loss             Binary cross entropy loss
nn_bce_with_logits_loss
                        BCE with logits loss
nn_bilinear             Bilinear module
nn_buffer               Creates a nn_buffer
nn_celu                 CELU module
nn_contrib_sparsemax    Sparsemax activation
nn_conv1d               Conv1D module
nn_conv2d               Conv2D module
nn_conv3d               Conv3D module
nn_conv_transpose1d     ConvTranspose1D
nn_conv_transpose2d     ConvTranpose2D module
nn_conv_transpose3d     ConvTranpose3D module
nn_cosine_embedding_loss
                        Cosine embedding loss
nn_cross_entropy_loss   CrossEntropyLoss module
nn_ctc_loss             The Connectionist Temporal Classification loss.
nn_dropout              Dropout module
nn_dropout2d            Dropout2D module
nn_dropout3d            Dropout3D module
nn_elu                  ELU module
nn_embedding            Embedding module
nn_embedding_bag        Embedding bag module
nn_flatten              Flattens a contiguous range of dims into a
                        tensor.
nn_fractional_max_pool2d
                        Applies a 2D fractional max pooling over an
                        input signal composed of several input planes.
nn_fractional_max_pool3d
                        Applies a 3D fractional max pooling over an
                        input signal composed of several input planes.
nn_gelu                 GELU module
nn_glu                  GLU module
nn_group_norm           Group normalization
nn_gru                  Applies a multi-layer gated recurrent unit
                        (GRU) RNN to an input sequence.
nn_hardshrink           Hardshwink module
nn_hardsigmoid          Hardsigmoid module
nn_hardswish            Hardswish module
nn_hardtanh             Hardtanh module
nn_hinge_embedding_loss
                        Hinge embedding loss
nn_identity             Identity module
nn_init_calculate_gain
                        Calculate gain
nn_init_constant_       Constant initialization
nn_init_dirac_          Dirac initialization
nn_init_eye_            Eye initialization
nn_init_kaiming_normal_
                        Kaiming normal initialization
nn_init_kaiming_uniform_
                        Kaiming uniform initialization
nn_init_normal_         Normal initialization
nn_init_ones_           Ones initialization
nn_init_orthogonal_     Orthogonal initialization
nn_init_sparse_         Sparse initialization
nn_init_trunc_normal_   Truncated normal initialization
nn_init_uniform_        Uniform initialization
nn_init_xavier_normal_
                        Xavier normal initialization
nn_init_xavier_uniform_
                        Xavier uniform initialization
nn_init_zeros_          Zeros initialization
nn_kl_div_loss          Kullback-Leibler divergence loss
nn_l1_loss              L1 loss
nn_layer_norm           Layer normalization
nn_leaky_relu           LeakyReLU module
nn_linear               Linear module
nn_log_sigmoid          LogSigmoid module
nn_log_softmax          LogSoftmax module
nn_lp_pool1d            Applies a 1D power-average pooling over an
                        input signal composed of several input planes.
nn_lp_pool2d            Applies a 2D power-average pooling over an
                        input signal composed of several input planes.
nn_lstm                 Applies a multi-layer long short-term memory
                        (LSTM) RNN to an input sequence.
nn_margin_ranking_loss
                        Margin ranking loss
nn_max_pool1d           MaxPool1D module
nn_max_pool2d           MaxPool2D module
nn_max_pool3d           Applies a 3D max pooling over an input signal
                        composed of several input planes.
nn_max_unpool1d         Computes a partial inverse of 'MaxPool1d'.
nn_max_unpool2d         Computes a partial inverse of 'MaxPool2d'.
nn_max_unpool3d         Computes a partial inverse of 'MaxPool3d'.
nn_module               Base class for all neural network modules.
nn_module_dict          Container that allows named values
nn_module_list          Holds submodules in a list.
nn_mse_loss             MSE loss
nn_multi_margin_loss    Multi margin loss
nn_multihead_attention
                        MultiHead attention
nn_multilabel_margin_loss
                        Multilabel margin loss
nn_multilabel_soft_margin_loss
                        Multi label soft margin loss
nn_nll_loss             Nll loss
nn_pairwise_distance    Pairwise distance
nn_parameter            Creates an 'nn_parameter'
nn_poisson_nll_loss     Poisson NLL loss
nn_prelu                PReLU module
nn_prune_head           Prune top layer(s) of a network
nn_relu                 ReLU module
nn_relu6                ReLu6 module
nn_rnn                  RNN module
nn_rrelu                RReLU module
nn_selu                 SELU module
nn_sequential           A sequential container
nn_sigmoid              Sigmoid module
nn_silu                 Applies the Sigmoid Linear Unit (SiLU)
                        function, element-wise. The SiLU function is
                        also known as the swish function.
nn_smooth_l1_loss       Smooth L1 loss
nn_soft_margin_loss     Soft margin loss
nn_softmax              Softmax module
nn_softmax2d            Softmax2d module
nn_softmin              Softmin
nn_softplus             Softplus module
nn_softshrink           Softshrink module
nn_softsign             Softsign module
nn_tanh                 Tanh module
nn_tanhshrink           Tanhshrink module
nn_threshold            Threshold module
nn_transformer_encoder
                        Transformer Encoder Module (R torch)
nn_transformer_encoder_layer
                        Transformer Encoder Layer Module (R torch)
nn_triplet_margin_loss
                        Triplet margin loss
nn_triplet_margin_with_distance_loss
                        Triplet margin with distance loss
nn_unflatten            Unflattens a tensor dim expanding it to a
                        desired shape. For use with [nn_sequential.
nn_upsample             Upsample module
nn_utils_clip_grad_norm_
                        Clips gradient norm of an iterable of
                        parameters.
nn_utils_clip_grad_value_
                        Clips gradient of an iterable of parameters at
                        specified value.
nn_utils_rnn_pack_padded_sequence
                        Packs a Tensor containing padded sequences of
                        variable length.
nn_utils_rnn_pack_sequence
                        Packs a list of variable length Tensors
nn_utils_rnn_pad_packed_sequence
                        Pads a packed batch of variable length
                        sequences.
nn_utils_rnn_pad_sequence
                        Pad a list of variable length Tensors with
                        'padding_value'
nn_utils_weight_norm    nn_utils_weight_norm
nnf_adaptive_avg_pool1d
                        Adaptive_avg_pool1d
nnf_adaptive_avg_pool2d
                        Adaptive_avg_pool2d
nnf_adaptive_avg_pool3d
                        Adaptive_avg_pool3d
nnf_adaptive_max_pool1d
                        Adaptive_max_pool1d
nnf_adaptive_max_pool2d
                        Adaptive_max_pool2d
nnf_adaptive_max_pool3d
                        Adaptive_max_pool3d
nnf_affine_grid         Affine_grid
nnf_alpha_dropout       Alpha_dropout
nnf_area_under_min_fpr_fnr
                        Area under the Min(FPR, FNR) (AUM)
nnf_avg_pool1d          Avg_pool1d
nnf_avg_pool2d          Avg_pool2d
nnf_avg_pool3d          Avg_pool3d
nnf_batch_norm          Batch_norm
nnf_bilinear            Bilinear
nnf_binary_cross_entropy
                        Binary_cross_entropy
nnf_binary_cross_entropy_with_logits
                        Binary_cross_entropy_with_logits
nnf_celu                Celu
nnf_contrib_sparsemax   Sparsemax
nnf_conv1d              Conv1d
nnf_conv2d              Conv2d
nnf_conv3d              Conv3d
nnf_conv_tbc            Conv_tbc
nnf_conv_transpose1d    Conv_transpose1d
nnf_conv_transpose2d    Conv_transpose2d
nnf_conv_transpose3d    Conv_transpose3d
nnf_cosine_embedding_loss
                        Cosine_embedding_loss
nnf_cosine_similarity   Cosine_similarity
nnf_cross_entropy       Cross_entropy
nnf_ctc_loss            Ctc_loss
nnf_dropout             Dropout
nnf_dropout2d           Dropout2d
nnf_dropout3d           Dropout3d
nnf_elu                 Elu
nnf_embedding           Embedding
nnf_embedding_bag       Embedding_bag
nnf_fold                Fold
nnf_fractional_max_pool2d
                        Fractional_max_pool2d
nnf_fractional_max_pool3d
                        Fractional_max_pool3d
nnf_gelu                Gelu
nnf_glu                 Glu
nnf_grid_sample         Grid_sample
nnf_group_norm          Group_norm
nnf_gumbel_softmax      Gumbel_softmax
nnf_hardshrink          Hardshrink
nnf_hardsigmoid         Hardsigmoid
nnf_hardswish           Hardswish
nnf_hardtanh            Hardtanh
nnf_hinge_embedding_loss
                        Hinge_embedding_loss
nnf_instance_norm       Instance_norm
nnf_interpolate         Interpolate
nnf_kl_div              Kl_div
nnf_l1_loss             L1_loss
nnf_layer_norm          Layer_norm
nnf_leaky_relu          Leaky_relu
nnf_linear              Linear
nnf_local_response_norm
                        Local_response_norm
nnf_log_softmax         Log_softmax
nnf_logsigmoid          Logsigmoid
nnf_lp_pool1d           Lp_pool1d
nnf_lp_pool2d           Lp_pool2d
nnf_margin_ranking_loss
                        Margin_ranking_loss
nnf_max_pool1d          Max_pool1d
nnf_max_pool2d          Max_pool2d
nnf_max_pool3d          Max_pool3d
nnf_max_unpool1d        Max_unpool1d
nnf_max_unpool2d        Max_unpool2d
nnf_max_unpool3d        Max_unpool3d
nnf_mse_loss            Mse_loss
nnf_multi_head_attention_forward
                        Multi head attention forward
nnf_multi_margin_loss   Multi_margin_loss
nnf_multilabel_margin_loss
                        Multilabel_margin_loss
nnf_multilabel_soft_margin_loss
                        Multilabel_soft_margin_loss
nnf_nll_loss            Nll_loss
nnf_normalize           Normalize
nnf_one_hot             One_hot
nnf_pad                 Pad
nnf_pairwise_distance   Pairwise_distance
nnf_pdist               Pdist
nnf_pixel_shuffle       Pixel_shuffle
nnf_poisson_nll_loss    Poisson_nll_loss
nnf_prelu               Prelu
nnf_relu                Relu
nnf_relu6               Relu6
nnf_rrelu               Rrelu
nnf_selu                Selu
nnf_sigmoid             Sigmoid
nnf_silu                Applies the Sigmoid Linear Unit (SiLU)
                        function, element-wise. See 'nn_silu()' for
                        more information.
nnf_smooth_l1_loss      Smooth_l1_loss
nnf_soft_margin_loss    Soft_margin_loss
nnf_softmax             Softmax
nnf_softmin             Softmin
nnf_softplus            Softplus
nnf_softshrink          Softshrink
nnf_softsign            Softsign
nnf_tanhshrink          Tanhshrink
nnf_threshold           Threshold
nnf_triplet_margin_loss
                        Triplet_margin_loss
nnf_triplet_margin_with_distance_loss
                        Triplet margin with distance loss
nnf_unfold              Unfold
optim_adadelta          Adadelta optimizer
optim_adagrad           Adagrad optimizer
optim_adam              Implements Adam algorithm.
optim_adamw             Implements AdamW algorithm
optim_asgd              Averaged Stochastic Gradient Descent optimizer
optim_ignite_adagrad    LibTorch implementation of Adagrad
optim_ignite_adam       LibTorch implementation of Adam
optim_ignite_adamw      LibTorch implementation of AdamW
optim_ignite_rmsprop    LibTorch implementation of RMSprop
optim_ignite_sgd        LibTorch implementation of SGD
optim_lbfgs             LBFGS optimizer
optim_required          Dummy value indicating a required value.
optim_rmsprop           RMSprop optimizer
optim_rprop             Implements the resilient backpropagation
                        algorithm.
optim_sgd               SGD optimizer
optimizer               Creates a custom optimizer
optimizer_ignite        Abstract Base Class for LibTorch Optimizers
sampler                 Creates a new Sampler
tensor_dataset          Dataset wrapping tensors.
threads                 Number of threads
torch_abs               Abs
torch_absolute          Absolute
torch_acos              Acos
torch_acosh             Acosh
torch_adaptive_avg_pool1d
                        Adaptive_avg_pool1d
torch_add               Add
torch_addbmm            Addbmm
torch_addcdiv           Addcdiv
torch_addcmul           Addcmul
torch_addmm             Addmm
torch_addmv             Addmv
torch_addr              Addr
torch_allclose          Allclose
torch_amax              Amax
torch_amin              Amin
torch_angle             Angle
torch_arange            Arange
torch_arccos            Arccos
torch_arccosh           Arccosh
torch_arcsin            Arcsin
torch_arcsinh           Arcsinh
torch_arctan            Arctan
torch_arctanh           Arctanh
torch_argmax            Argmax
torch_argmin            Argmin
torch_argsort           Argsort
torch_as_strided        As_strided
torch_asin              Asin
torch_asinh             Asinh
torch_atan              Atan
torch_atan2             Atan2
torch_atanh             Atanh
torch_atleast_1d        Atleast_1d
torch_atleast_2d        Atleast_2d
torch_atleast_3d        Atleast_3d
torch_avg_pool1d        Avg_pool1d
torch_baddbmm           Baddbmm
torch_bartlett_window   Bartlett_window
torch_bernoulli         Bernoulli
torch_bincount          Bincount
torch_bitwise_and       Bitwise_and
torch_bitwise_not       Bitwise_not
torch_bitwise_or        Bitwise_or
torch_bitwise_xor       Bitwise_xor
torch_blackman_window   Blackman_window
torch_block_diag        Block_diag
torch_bmm               Bmm
torch_broadcast_tensors
                        Broadcast_tensors
torch_bucketize         Bucketize
torch_can_cast          Can_cast
torch_cartesian_prod    Cartesian_prod
torch_cat               Cat
torch_cdist             Cdist
torch_ceil              Ceil
torch_celu              Celu
torch_celu_             Celu_
torch_chain_matmul      Chain_matmul
torch_channel_shuffle   Channel_shuffle
torch_cholesky          Cholesky
torch_cholesky_inverse
                        Cholesky_inverse
torch_cholesky_solve    Cholesky_solve
torch_chunk             Chunk
torch_clamp             Clamp
torch_clip              Clip
torch_clone             Clone
torch_combinations      Combinations
torch_complex           Complex
torch_conj              Conj
torch_conv1d            Conv1d
torch_conv2d            Conv2d
torch_conv3d            Conv3d
torch_conv_tbc          Conv_tbc
torch_conv_transpose1d
                        Conv_transpose1d
torch_conv_transpose2d
                        Conv_transpose2d
torch_conv_transpose3d
                        Conv_transpose3d
torch_cos               Cos
torch_cosh              Cosh
torch_cosine_similarity
                        Cosine_similarity
torch_count_nonzero     Count_nonzero
torch_cross             Cross
torch_cummax            Cummax
torch_cummin            Cummin
torch_cumprod           Cumprod
torch_cumsum            Cumsum
torch_deg2rad           Deg2rad
torch_dequantize        Dequantize
torch_det               Det
torch_device            Create a Device object
torch_diag              Diag
torch_diag_embed        Diag_embed
torch_diagflat          Diagflat
torch_diagonal          Diagonal
torch_diff              Computes the n-th forward difference along the
                        given dimension.
torch_digamma           Digamma
torch_dist              Dist
torch_div               Div
torch_divide            Divide
torch_dot               Dot
torch_dstack            Dstack
torch_dtype             Torch data types
torch_eig               Eig
torch_einsum            Einsum
torch_empty             Empty
torch_empty_like        Empty_like
torch_empty_strided     Empty_strided
torch_eq                Eq
torch_equal             Equal
torch_erf               Erf
torch_erfc              Erfc
torch_erfinv            Erfinv
torch_exp               Exp
torch_exp2              Exp2
torch_expm1             Expm1
torch_eye               Eye
torch_fft_fft           Fft
torch_fft_fftfreq       fftfreq
torch_fft_ifft          Ifft
torch_fft_irfft         Irfft
torch_fft_rfft          Rfft
torch_finfo             Floating point type info
torch_fix               Fix
torch_flatten           Flatten
torch_flip              Flip
torch_fliplr            Fliplr
torch_flipud            Flipud
torch_floor             Floor
torch_floor_divide      Floor_divide
torch_fmod              Fmod
torch_frac              Frac
torch_full              Full
torch_full_like         Full_like
torch_gather            Gather
torch_gcd               Gcd
torch_ge                Ge
torch_generator         Create a Generator object
torch_geqrf             Geqrf
torch_ger               Ger
torch_get_rng_state     RNG state management
torch_greater           Greater
torch_greater_equal     Greater_equal
torch_gt                Gt
torch_hamming_window    Hamming_window
torch_hann_window       Hann_window
torch_heaviside         Heaviside
torch_histc             Histc
torch_hstack            Hstack
torch_hypot             Hypot
torch_i0                I0
torch_iinfo             Integer type info
torch_imag              Imag
torch_index             Index torch tensors
torch_index_put         Modify values selected by 'indices'.
torch_index_put_        In-place version of 'torch_index_put'.
torch_index_select      Index_select
torch_install_path      A simple exported version of install_path
                        Returns the torch installation path.
torch_inverse           Inverse
torch_is_complex        Is_complex
torch_is_floating_point
                        Is_floating_point
torch_is_installed      Verifies if torch is installed
torch_is_nonzero        Is_nonzero
torch_isclose           Isclose
torch_isfinite          Isfinite
torch_isinf             Isinf
torch_isnan             Isnan
torch_isneginf          Isneginf
torch_isposinf          Isposinf
torch_isreal            Isreal
torch_istft             Istft
torch_kaiser_window     Kaiser_window
torch_kron              Kronecker product
torch_kthvalue          Kthvalue
torch_layout            Creates the corresponding layout
torch_lcm               Lcm
torch_le                Le
torch_lerp              Lerp
torch_less              Less
torch_less_equal        Less_equal
torch_lgamma            Lgamma
torch_linspace          Linspace
torch_load              Loads a saved object
torch_log               Log
torch_log10             Log10
torch_log1p             Log1p
torch_log2              Log2
torch_logaddexp         Logaddexp
torch_logaddexp2        Logaddexp2
torch_logcumsumexp      Logcumsumexp
torch_logdet            Logdet
torch_logical_and       Logical_and
torch_logical_not       Logical_not
torch_logical_or        Logical_or
torch_logical_xor       Logical_xor
torch_logit             Logit
torch_logspace          Logspace
torch_logsumexp         Logsumexp
torch_lstsq             Lstsq
torch_lt                Lt
torch_lu                LU
torch_lu_solve          Lu_solve
torch_lu_unpack         Lu_unpack
torch_manual_seed       Sets the seed for generating random numbers.
torch_masked_select     Masked_select
torch_matmul            Matmul
torch_matrix_exp        Matrix_exp
torch_matrix_power      Matrix_power
torch_matrix_rank       Matrix_rank
torch_max               Max
torch_maximum           Maximum
torch_mean              Mean
torch_median            Median
torch_memory_format     Memory format
torch_meshgrid          Meshgrid
torch_min               Min
torch_minimum           Minimum
torch_mm                Mm
torch_mode              Mode
torch_movedim           Movedim
torch_mul               Mul
torch_multinomial       Multinomial
torch_multiply          Multiply
torch_mv                Mv
torch_mvlgamma          Mvlgamma
torch_nanquantile       Nanquantile
torch_nansum            Nansum
torch_narrow            Narrow
torch_ne                Ne
torch_neg               Neg
torch_negative          Negative
torch_nextafter         Nextafter
torch_nonzero           Nonzero
torch_norm              Norm
torch_normal            Normal
torch_not_equal         Not_equal
torch_ones              Ones
torch_ones_like         Ones_like
torch_orgqr             Orgqr
torch_ormqr             Ormqr
torch_outer             Outer
torch_pdist             Pdist
torch_pinverse          Pinverse
torch_pixel_shuffle     Pixel_shuffle
torch_poisson           Poisson
torch_polar             Polar
torch_polygamma         Polygamma
torch_pow               Pow
torch_prod              Prod
torch_promote_types     Promote_types
torch_qr                Qr
torch_qscheme           Creates the corresponding Scheme object
torch_quantile          Quantile
torch_quantize_per_channel
                        Quantize_per_channel
torch_quantize_per_tensor
                        Quantize_per_tensor
torch_rad2deg           Rad2deg
torch_rand              Rand
torch_rand_like         Rand_like
torch_randint           Randint
torch_randint_like      Randint_like
torch_randn             Randn
torch_randn_like        Randn_like
torch_randperm          Randperm
torch_range             Range
torch_real              Real
torch_reciprocal        Reciprocal
torch_reduction         Creates the reduction objet
torch_relu              Relu
torch_relu_             Relu_
torch_remainder         Remainder
torch_renorm            Renorm
torch_repeat_interleave
                        Repeat_interleave
torch_reshape           Reshape
torch_result_type       Result_type
torch_roll              Roll
torch_rot90             Rot90
torch_round             Round
torch_rrelu_            Rrelu_
torch_rsqrt             Rsqrt
torch_save              Saves an object to a disk file.
torch_scalar_tensor     Scalar tensor
torch_searchsorted      Searchsorted
torch_selu              Selu
torch_selu_             Selu_
torch_serialize         Serialize a torch object returning a raw object
torch_set_default_dtype
                        Gets and sets the default floating point dtype.
torch_sgn               Sgn
torch_sigmoid           Sigmoid
torch_sign              Sign
torch_signbit           Signbit
torch_sin               Sin
torch_sinh              Sinh
torch_slogdet           Slogdet
torch_sort              Sort
torch_sparse_coo_tensor
                        Sparse_coo_tensor
torch_split             Split
torch_sqrt              Sqrt
torch_square            Square
torch_squeeze           Squeeze
torch_stack             Stack
torch_std               Std
torch_std_mean          Std_mean
torch_stft              Stft
torch_sub               Sub
torch_subtract          Subtract
torch_sum               Sum
torch_svd               Svd
torch_t                 T
torch_take              Take
torch_take_along_dim    Selects values from input at the 1-dimensional
                        indices from indices along the given dim.
torch_tan               Tan
torch_tanh              Tanh
torch_tensor            Converts R objects to a torch tensor
torch_tensor_from_buffer
                        Creates a tensor from a buffer of memory
torch_tensordot         Tensordot
torch_threshold_        Threshold_
torch_topk              Topk
torch_trace             Trace
torch_transpose         Transpose
torch_trapz             Trapz
torch_triangular_solve
                        Triangular_solve
torch_tril              Tril
torch_tril_indices      Tril_indices
torch_triu              Triu
torch_triu_indices      Triu_indices
torch_true_divide       TRUE_divide
torch_trunc             Trunc
torch_unbind            Unbind
torch_unique_consecutive
                        Unique_consecutive
torch_unsafe_chunk      Unsafe_chunk
torch_unsafe_split      Unsafe_split
torch_unsqueeze         Unsqueeze
torch_vander            Vander
torch_var               Var
torch_var_mean          Var_mean
torch_vdot              Vdot
torch_view_as_complex   View_as_complex
torch_view_as_real      View_as_real
torch_vstack            Vstack
torch_where             Where
torch_zeros             Zeros
torch_zeros_like        Zeros_like
with_detect_anomaly     Context-manager that enable anomaly detection
                        for the autograd engine.
with_enable_grad        Enable grad
with_no_grad            Temporarily modify gradient recording.
