Package: torch 0.17.0.9000

Tomasz Kalinowski

torch: Tensors and Neural Networks with 'GPU' Acceleration

Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <doi:10.48550/arXiv.1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.

Authors:Tomasz Kalinowski [ctb, cre], Daniel Falbel [aut, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], Hamada S. Badr [ctb], Sebastian Fischer [ctb], Maximilian Pichler [ctb], RStudio [cph]

torch_0.17.0.9000.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
torch/json (API)

# Install 'torch' in R:

install.packages('torch', repos = c('https://mlverse.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mlverse/torch/issues

Pkgdown/docs site:https://torch.mlverse.org

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

autograd deep-learning torch cpp

16.16 score 566 stars 50 packages 2.9k scripts 14k downloads 11 mentions 758 exports 23 dependencies

Last updated from:1a62fa648c. Checks:11 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	WARNING	640
linux-devel-x86_64	WARNING	643
source / vignettes	OK	848
linux-release-arm64	WARNING	629
linux-release-x86_64	WARNING	653
macos-release-arm64	WARNING	393
macos-release-x86_64	WARNING	985
macos-oldrel-arm64	WARNING	374
macos-oldrel-x86_64	WARNING	923
windows-devel	WARNING	699
windows-release	WARNING	983
windows-oldrel	WARNING	964
wasm-release	OK	292

Exports:%>%as_array as_iterator autograd_backward autograd_function autograd_grad autograd_set_grad_mode backends_cudnn_is_available backends_cudnn_version backends_mkl_is_available backends_mkldnn_is_available backends_mps_is_available backends_mps_synchronize backends_openmp_is_available buffer_from_torch_tensor call_torch_function clone_module contrib_sort_vertices cpu_cache_flush cuda_amp_grad_scaler cuda_current_device cuda_device_count cuda_dump_memory_snapshot cuda_empty_cache cuda_get_device_capability cuda_get_rng_state cuda_is_available cuda_memory_snapshot cuda_memory_stats cuda_memory_summary cuda_record_memory_history cuda_runtime_version cuda_set_rng_state cuda_synchronize dataloader dataloader_make_iter dataloader_next dataset dataset_subset distr_bernoulli distr_categorical distr_chi2 distr_gamma distr_mixture_same_family distr_multivariate_normal distr_normal distr_poisson enumerate get_install_libs_url install_torch install_torch_from_file install_torch_sitrep is_dataloader is_nn_buffer is_nn_module is_nn_parameter is_optimizer is_torch_device is_torch_dtype is_torch_layout is_torch_memory_format is_torch_qscheme is_undefined_tensor iterable_dataset jit_compile jit_load jit_ops jit_save jit_save_for_mobile jit_scalar jit_serialize jit_trace jit_trace_module jit_tuple jit_unserialize linalg_cholesky linalg_cholesky_ex linalg_cond linalg_det linalg_eig linalg_eigh linalg_eigvals linalg_eigvalsh linalg_householder_product linalg_inv linalg_inv_ex linalg_lstsq linalg_matrix_norm linalg_matrix_power linalg_matrix_rank linalg_multi_dot linalg_norm linalg_pinv linalg_qr linalg_slogdet linalg_solve linalg_solve_triangular linalg_svd linalg_svdvals linalg_tensorinv linalg_tensorsolve linalg_vector_norm load_state_dict local_autocast local_device local_enable_grad local_no_grad local_torch_manual_seed loop lr_cosine_annealing lr_lambda lr_multiplicative lr_one_cycle lr_reduce_on_plateau lr_scheduler lr_step nn_adaptive_avg_pool1d nn_adaptive_avg_pool2d nn_adaptive_avg_pool3d nn_adaptive_log_softmax_with_loss nn_adaptive_max_pool1d nn_adaptive_max_pool2d nn_adaptive_max_pool3d nn_aum_loss nn_avg_pool1d nn_avg_pool2d nn_avg_pool3d nn_batch_norm1d nn_batch_norm2d nn_batch_norm3d nn_bce_loss nn_bce_with_logits_loss nn_bilinear nn_buffer nn_celu nn_contrib_sparsemax nn_conv_transpose1d nn_conv_transpose2d nn_conv_transpose3d nn_conv1d nn_conv2d nn_conv3d nn_cosine_embedding_loss nn_cross_entropy_loss nn_ctc_loss nn_dropout nn_dropout2d nn_dropout3d nn_elu nn_embedding nn_embedding_bag nn_flatten nn_fractional_max_pool2d nn_fractional_max_pool3d nn_gelu nn_glu nn_group_norm nn_gru nn_hardshrink nn_hardsigmoid nn_hardswish nn_hardtanh nn_hinge_embedding_loss nn_identity nn_init_calculate_gain nn_init_constant_nn_init_dirac_nn_init_eye_nn_init_kaiming_normal_nn_init_kaiming_uniform_nn_init_normal_nn_init_ones_nn_init_orthogonal_nn_init_sparse_nn_init_trunc_normal_nn_init_uniform_nn_init_xavier_normal_nn_init_xavier_uniform_nn_init_zeros_nn_kl_div_loss nn_l1_loss nn_layer_norm nn_leaky_relu nn_linear nn_log_sigmoid nn_log_softmax nn_lp_pool1d nn_lp_pool2d nn_lstm nn_margin_ranking_loss nn_max_pool1d nn_max_pool2d nn_max_pool3d nn_max_unpool1d nn_max_unpool2d nn_max_unpool3d nn_module nn_module_dict nn_module_list nn_mse_loss nn_multi_margin_loss nn_multihead_attention nn_multilabel_margin_loss nn_multilabel_soft_margin_loss nn_nll_loss nn_pairwise_distance nn_parameter nn_poisson_nll_loss nn_prelu nn_prune_head nn_relu nn_relu6 nn_rnn nn_rrelu nn_selu nn_sequential nn_sigmoid nn_silu nn_smooth_l1_loss nn_soft_margin_loss nn_softmax nn_softmax2d nn_softmin nn_softplus nn_softshrink nn_softsign nn_tanh nn_tanhshrink nn_threshold nn_transformer_encoder nn_transformer_encoder_layer nn_triplet_margin_loss nn_triplet_margin_with_distance_loss nn_unflatten nn_upsample nn_utils_clip_grad_norm_nn_utils_clip_grad_value_nn_utils_rnn_pack_padded_sequence nn_utils_rnn_pack_sequence nn_utils_rnn_pad_packed_sequence nn_utils_rnn_pad_sequence nn_utils_weight_norm nnf_adaptive_avg_pool1d nnf_adaptive_avg_pool2d nnf_adaptive_avg_pool3d nnf_adaptive_max_pool1d nnf_adaptive_max_pool2d nnf_adaptive_max_pool3d nnf_affine_grid nnf_alpha_dropout nnf_area_under_min_fpr_fnr nnf_avg_pool1d nnf_avg_pool2d nnf_avg_pool3d nnf_batch_norm nnf_bilinear nnf_binary_cross_entropy nnf_binary_cross_entropy_with_logits nnf_celu nnf_celu_nnf_contrib_sparsemax nnf_conv_tbc nnf_conv_transpose1d nnf_conv_transpose2d nnf_conv_transpose3d nnf_conv1d nnf_conv2d nnf_conv3d nnf_cosine_embedding_loss nnf_cosine_similarity nnf_cross_entropy nnf_ctc_loss nnf_dropout nnf_dropout2d nnf_dropout3d nnf_elu nnf_elu_nnf_embedding nnf_embedding_bag nnf_fold nnf_fractional_max_pool2d nnf_fractional_max_pool3d nnf_gelu nnf_glu nnf_grid_sample nnf_group_norm nnf_gumbel_softmax nnf_hardshrink nnf_hardsigmoid nnf_hardswish nnf_hardtanh nnf_hardtanh_nnf_hinge_embedding_loss nnf_instance_norm nnf_interpolate nnf_kl_div nnf_l1_loss nnf_layer_norm nnf_leaky_relu nnf_linear nnf_local_response_norm nnf_log_softmax nnf_logsigmoid nnf_lp_pool1d nnf_lp_pool2d nnf_margin_ranking_loss nnf_max_pool1d nnf_max_pool2d nnf_max_pool3d nnf_max_unpool1d nnf_max_unpool2d nnf_max_unpool3d nnf_mse_loss nnf_multi_head_attention_forward nnf_multi_margin_loss nnf_multilabel_margin_loss nnf_multilabel_soft_margin_loss nnf_nll_loss nnf_normalize nnf_one_hot nnf_pad nnf_pairwise_distance nnf_pdist nnf_pixel_shuffle nnf_poisson_nll_loss nnf_prelu nnf_relu nnf_relu_nnf_relu6 nnf_rrelu nnf_rrelu_nnf_selu nnf_selu_nnf_sigmoid nnf_silu nnf_smooth_l1_loss nnf_soft_margin_loss nnf_softmax nnf_softmin nnf_softplus nnf_softshrink nnf_softsign nnf_tanhshrink nnf_threshold nnf_threshold_nnf_triplet_margin_loss nnf_triplet_margin_with_distance_loss nnf_unfold optim_adadelta optim_adagrad optim_adam optim_adamw optim_asgd optim_ignite_adagrad optim_ignite_adam optim_ignite_adamw optim_ignite_rmsprop optim_ignite_sgd optim_lbfgs optim_required optim_rmsprop optim_rprop optim_sgd optimizer optimizer_ignite OptimizerIgnite sampler set_autocast set_cpu_allocator_config slc tensor_dataset torch_abs torch_absolute torch_acos torch_acosh torch_adaptive_avg_pool1d torch_add torch_addbmm torch_addcdiv torch_addcmul torch_addmm torch_addmv torch_addr torch_allclose torch_amax torch_amin torch_angle torch_arange torch_arccos torch_arccosh torch_arcsin torch_arcsinh torch_arctan torch_arctanh torch_argmax torch_argmin torch_argsort torch_as_strided torch_asin torch_asinh torch_atan torch_atan2 torch_atanh torch_atleast_1d torch_atleast_2d torch_atleast_3d torch_avg_pool1d torch_baddbmm torch_bartlett_window torch_bernoulli torch_bfloat16 torch_bincount torch_bitwise_and torch_bitwise_not torch_bitwise_or torch_bitwise_xor torch_blackman_window torch_block_diag torch_bmm torch_bool torch_broadcast_tensors torch_bucketize torch_can_cast torch_cartesian_prod torch_cat torch_cdist torch_cdouble torch_ceil torch_celu torch_celu_torch_cfloat torch_cfloat128 torch_cfloat32 torch_cfloat64 torch_chain_matmul torch_chalf torch_channel_shuffle torch_channels_last_format torch_cholesky torch_cholesky_inverse torch_cholesky_solve torch_chunk torch_clamp torch_clip torch_clone torch_combinations torch_complex torch_conj torch_contiguous_format torch_conv_tbc torch_conv_transpose1d torch_conv_transpose2d torch_conv_transpose3d torch_conv1d torch_conv2d torch_conv3d torch_cos torch_cosh torch_cosine_similarity torch_count_nonzero torch_cross torch_cummax torch_cummin torch_cumprod torch_cumsum torch_deg2rad torch_dequantize torch_det torch_device torch_diag torch_diag_embed torch_diagflat torch_diagonal torch_diff torch_digamma torch_dist torch_div torch_divide torch_dot torch_double torch_dstack torch_einsum torch_empty torch_empty_like torch_empty_strided torch_eq torch_equal torch_erf torch_erfc torch_erfinv torch_exp torch_exp2 torch_expm1 torch_eye torch_fft_fft torch_fft_fftfreq torch_fft_ifft torch_fft_irfft torch_fft_rfft torch_finfo torch_fix torch_flatten torch_flip torch_fliplr torch_flipud torch_float torch_float16 torch_float32 torch_float64 torch_float8_e4m3fn torch_float8_e5m2 torch_floor torch_floor_divide torch_fmod torch_frac torch_full torch_full_like torch_gather torch_gcd torch_ge torch_generator torch_geqrf torch_ger torch_get_default_dtype torch_get_num_interop_threads torch_get_num_threads torch_get_rng_state torch_greater torch_greater_equal torch_gt torch_half torch_hamming_window torch_hann_window torch_heaviside torch_histc torch_hstack torch_hypot torch_i0 torch_iinfo torch_imag torch_index torch_index_put torch_index_put_torch_index_select torch_install_path torch_int torch_int16 torch_int32 torch_int64 torch_int8 torch_inverse torch_is_complex torch_is_floating_point torch_is_installed torch_is_nonzero torch_isclose torch_isfinite torch_isinf torch_isnan torch_isneginf torch_isposinf torch_isreal torch_istft torch_kaiser_window torch_kron torch_kthvalue torch_lcm torch_ldexp torch_le torch_lerp torch_less torch_less_equal torch_lgamma torch_linspace torch_load torch_log torch_log10 torch_log1p torch_log2 torch_logaddexp torch_logaddexp2 torch_logcumsumexp torch_logdet torch_logical_and torch_logical_not torch_logical_or torch_logical_xor torch_logit torch_logspace torch_logsumexp torch_long torch_lt torch_lu torch_lu_solve torch_lu_unpack torch_manual_seed torch_masked_select torch_matmul torch_matrix_exp torch_matrix_power torch_max torch_maximum torch_mean torch_median torch_meshgrid torch_min torch_minimum torch_mm torch_mode torch_movedim torch_mul torch_multinomial torch_multiply torch_mv torch_mvlgamma torch_nanquantile torch_nansum torch_narrow torch_ne torch_neg torch_negative torch_nextafter torch_nonzero torch_norm torch_normal torch_not_equal torch_ones torch_ones_like torch_orgqr torch_ormqr torch_outer torch_pdist torch_per_channel_affine torch_per_channel_symmetric torch_per_tensor_affine torch_per_tensor_symmetric torch_pinverse torch_pixel_shuffle torch_poisson torch_polar torch_polygamma torch_pow torch_preserve_format torch_prod torch_promote_types torch_qint32 torch_qint8 torch_qr torch_quantile torch_quantize_per_channel torch_quantize_per_tensor torch_quint8 torch_rad2deg torch_rand torch_rand_like torch_randint torch_randint_like torch_randn torch_randn_like torch_randperm torch_range torch_real torch_reciprocal torch_reduction_mean torch_reduction_none torch_reduction_sum torch_relu torch_relu_torch_remainder torch_renorm torch_repeat_interleave torch_reshape torch_result_type torch_roll torch_rot90 torch_round torch_rrelu_torch_rsqrt torch_save torch_scalar_tensor torch_scaled_dot_product_attention torch_searchsorted torch_selu torch_selu_torch_serialize torch_set_default_dtype torch_set_num_interop_threads torch_set_num_threads torch_set_rng_state torch_sgn torch_short torch_sigmoid torch_sign torch_signbit torch_sin torch_sinh torch_slogdet torch_sort torch_sparse_coo torch_sparse_coo_tensor torch_sparse_sampled_addmm torch_split torch_sqrt torch_square torch_squeeze torch_stack torch_std torch_std_mean torch_stft torch_strided torch_sub torch_subtract torch_sum torch_svd torch_t torch_take torch_take_along_dim torch_tan torch_tanh torch_tensor torch_tensor_from_buffer torch_tensordot torch_threshold_torch_topk torch_trace torch_transpose torch_trapz torch_triangular_solve torch_tril torch_tril_indices torch_triu torch_triu_indices torch_true_divide torch_trunc torch_uint8 torch_unbind torch_unique_consecutive torch_unsafe_chunk torch_unsafe_split torch_unsqueeze torch_vander torch_var torch_var_mean torch_vdot torch_view_as_complex torch_view_as_real torch_vstack torch_where torch_zeros torch_zeros_like unset_autocast with_autocast with_detect_anomaly with_device with_enable_grad with_no_grad with_torch_manual_seed yield

Dependencies:bit bit64 callr cli coro desc farver glue jsonlite labeling lifecycle magrittr otel processx ps R6 RColorBrewer Rcpp rlang safetensors scales viridisLite withr

Installation

Rendered frominstallation.Rmdusingknitr::rmarkdown

Last update: 2026-04-11
Started: 2020-10-08

Help page	Topics
Converts to array	as_array
Computes the sum of gradients of given tensors w.r.t. graph leaves.	autograd_backward
Records operation history and defines formulas for differentiating ops.	autograd_function
Computes and returns the sum of gradients of outputs w.r.t. the inputs.	autograd_grad
Set grad mode	autograd_set_grad_mode
Class representing the context.	AutogradContext
CuDNN is available	backends_cudnn_is_available
CuDNN version	backends_cudnn_version
MKL is available	backends_mkl_is_available
MKLDNN is available	backends_mkldnn_is_available
MPS is available	backends_mps_is_available
OpenMP is available	backends_openmp_is_available
Given a list of values (possibly containing numbers), returns a list where each value is broadcasted based on the following rules:	broadcast_all
Clone a torch module.	clone_module
Abstract base class for constraints.	Constraint
Contrib sort vertices	contrib_sort_vertices
Flush the CPU memory cache	cpu_cache_flush
Creates a gradient scaler	cuda_amp_grad_scaler
Returns the index of a currently selected device.	cuda_current_device
Returns the number of GPUs available.	cuda_device_count
Save CUDA Memory State Snapshot to File	cuda_dump_memory_snapshot
Empty cache	cuda_empty_cache
Returns the major and minor CUDA capability of 'device'	cuda_get_device_capability
Returns a bool indicating if CUDA is currently available.	cuda_is_available
Capture CUDA Memory State Snapshot	cuda_memory_snapshot
Returns a dictionary of CUDA memory allocator statistics for a given device.	cuda_memory_stats cuda_memory_summary
Enable Recording of Memory Allocation Stack Traces	cuda_record_memory_history
Returns the CUDA runtime version	cuda_runtime_version
Waits for all kernels in all streams on a CUDA device to complete.	cuda_synchronize
Data loader. Combines a dataset and a sampler, and provides single- or multi-process iterators over the dataset.	dataloader
Creates an iterator from a DataLoader	dataloader_make_iter
Get the next element of a dataloader iterator	dataloader_next
Helper function to create an function that generates R6 instances of class 'dataset'	dataset
Dataset Subset	dataset_subset
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_bernoulli
Creates a categorical distribution parameterized by either 'probs' or 'logits' (but not both).	distr_categorical
Creates a Chi2 distribution parameterized by shape parameter 'df'. This is exactly equivalent to 'distr_gamma(alpha=0.5*df, beta=0.5)'	distr_chi2
Creates a Gamma distribution parameterized by shape 'concentration' and 'rate'.	distr_gamma
Mixture of components in the same family	distr_mixture_same_family
Gaussian distribution	distr_multivariate_normal
Creates a normal (also called Gaussian) distribution parameterized by 'loc' and 'scale'.	distr_normal
Creates a Poisson distribution parameterized by 'rate', the rate parameter.	distr_poisson
Generic R6 class representing distributions	Distribution
Enumerate an iterator	enumerate
Enumerate an iterator	enumerate.dataloader
Install Torch from files	get_install_libs_url install_torch_from_file
Install Torch	install_torch
Torch Installation Situation Report	install_torch_sitrep
Checks if the object is a dataloader	is_dataloader
Checks if the object is a nn_buffer	is_nn_buffer
Checks if the object is an nn_module	is_nn_module
Checks if an object is a nn_parameter	is_nn_parameter
Checks if the object is a torch optimizer	is_optimizer
Checks if object is a device	is_torch_device
Check if object is a torch data type	is_torch_dtype
Check if an object is a torch layout.	is_torch_layout
Check if an object is a memory format	is_torch_memory_format
Checks if an object is a QScheme	is_torch_qscheme
Checks if a tensor is undefined	is_undefined_tensor
Creates an iterable dataset	iterable_dataset
Compile TorchScript code into a graph	jit_compile
Loads a 'script_function' or 'script_module' previously saved with 'jit_save'	jit_load
Enable idiomatic access to JIT operators from R.	jit_ops
Saves a 'script_function' to a path	jit_save
Saves a 'script_function' or 'script_module' in bytecode form, to be loaded on a mobile device	jit_save_for_mobile
Adds the 'jit_scalar' class to the input	jit_scalar
Serialize a Script Module	jit_serialize
Trace a function and return an executable 'script_function'.	jit_trace
Trace a module	jit_trace_module
Adds the 'jit_tuple' class to the input	jit_tuple
Unserialize a Script Module	jit_unserialize
Computes the Cholesky decomposition of a complex Hermitian or real symmetric positive-definite matrix.	linalg_cholesky
Computes the Cholesky decomposition of a complex Hermitian or real symmetric positive-definite matrix.	linalg_cholesky_ex
Computes the condition number of a matrix with respect to a matrix norm.	linalg_cond
Computes the determinant of a square matrix.	linalg_det
Computes the eigenvalue decomposition of a square matrix if it exists.	linalg_eig
Computes the eigenvalue decomposition of a complex Hermitian or real symmetric matrix.	linalg_eigh
Computes the eigenvalues of a square matrix.	linalg_eigvals
Computes the eigenvalues of a complex Hermitian or real symmetric matrix.	linalg_eigvalsh
Computes the first 'n' columns of a product of Householder matrices.	linalg_householder_product
Computes the inverse of a square matrix if it exists.	linalg_inv
Computes the inverse of a square matrix if it is invertible.	linalg_inv_ex
Computes a solution to the least squares problem of a system of linear equations.	linalg_lstsq
Computes a matrix norm.	linalg_matrix_norm
Computes the 'n'-th power of a square matrix for an integer 'n'.	linalg_matrix_power
Computes the numerical rank of a matrix.	linalg_matrix_rank
Efficiently multiplies two or more matrices	linalg_multi_dot
Computes a vector or matrix norm.	linalg_norm
Computes the pseudoinverse (Moore-Penrose inverse) of a matrix.	linalg_pinv
Computes the QR decomposition of a matrix.	linalg_qr
Computes the sign and natural logarithm of the absolute value of the determinant of a square matrix.	linalg_slogdet
Computes the solution of a square system of linear equations with a unique solution.	linalg_solve
Triangular solve	linalg_solve_triangular
Computes the singular value decomposition (SVD) of a matrix.	linalg_svd
Computes the singular values of a matrix.	linalg_svdvals
Computes the multiplicative inverse of 'torch_tensordot()'	linalg_tensorinv
Computes the solution 'X' to the system 'torch_tensordot(A, X) = B'.	linalg_tensorsolve
Computes a vector norm.	linalg_vector_norm
Load a state dict file	load_state_dict
Autocast context manager	local_autocast set_autocast unset_autocast with_autocast
Device contexts	local_device with_device
Set the learning rate of each parameter group using a cosine annealing schedule	lr_cosine_annealing
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_lambda
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_multiplicative
Once cycle learning rate	lr_one_cycle
Reduce learning rate on plateau	lr_reduce_on_plateau
Creates learning rate schedulers	lr_scheduler
Step learning rate decay	lr_step
Applies a 1D adaptive average pooling over an input signal composed of several input planes.	nn_adaptive_avg_pool1d
Applies a 2D adaptive average pooling over an input signal composed of several input planes.	nn_adaptive_avg_pool2d
Applies a 3D adaptive average pooling over an input signal composed of several input planes.	nn_adaptive_avg_pool3d
AdaptiveLogSoftmaxWithLoss module	nn_adaptive_log_softmax_with_loss
Applies a 1D adaptive max pooling over an input signal composed of several input planes.	nn_adaptive_max_pool1d
Applies a 2D adaptive max pooling over an input signal composed of several input planes.	nn_adaptive_max_pool2d
Applies a 3D adaptive max pooling over an input signal composed of several input planes.	nn_adaptive_max_pool3d
AUM loss	nn_aum_loss
Applies a 1D average pooling over an input signal composed of several input planes.	nn_avg_pool1d
Applies a 2D average pooling over an input signal composed of several input planes.	nn_avg_pool2d
Applies a 3D average pooling over an input signal composed of several input planes.	nn_avg_pool3d
BatchNorm1D module	nn_batch_norm1d
BatchNorm2D	nn_batch_norm2d
BatchNorm3D	nn_batch_norm3d
Binary cross entropy loss	nn_bce_loss
BCE with logits loss	nn_bce_with_logits_loss
Bilinear module	nn_bilinear
Creates a nn_buffer	nn_buffer
CELU module	nn_celu
Sparsemax activation	nn_contrib_sparsemax
ConvTranspose1D	nn_conv_transpose1d
ConvTranpose2D module	nn_conv_transpose2d
ConvTranpose3D module	nn_conv_transpose3d
Conv1D module	nn_conv1d
Conv2D module	nn_conv2d
Conv3D module	nn_conv3d
Cosine embedding loss	nn_cosine_embedding_loss
CrossEntropyLoss module	nn_cross_entropy_loss
The Connectionist Temporal Classification loss.	nn_ctc_loss
Dropout module	nn_dropout
Dropout2D module	nn_dropout2d
Dropout3D module	nn_dropout3d
ELU module	nn_elu
Embedding module	nn_embedding
Embedding bag module	nn_embedding_bag
Flattens a contiguous range of dims into a tensor.	nn_flatten
Applies a 2D fractional max pooling over an input signal composed of several input planes.	nn_fractional_max_pool2d
Applies a 3D fractional max pooling over an input signal composed of several input planes.	nn_fractional_max_pool3d
GELU module	nn_gelu
GLU module	nn_glu
Group normalization	nn_group_norm
Applies a multi-layer gated recurrent unit (GRU) RNN to an input sequence.	nn_gru
Hardshwink module	nn_hardshrink
Hardsigmoid module	nn_hardsigmoid
Hardswish module	nn_hardswish
Hardtanh module	nn_hardtanh
Hinge embedding loss	nn_hinge_embedding_loss
Identity module	nn_identity
Calculate gain	nn_init_calculate_gain
Constant initialization	nn_init_constant_
Dirac initialization	nn_init_dirac_
Eye initialization	nn_init_eye_
Kaiming normal initialization	nn_init_kaiming_normal_
Kaiming uniform initialization	nn_init_kaiming_uniform_
Normal initialization	nn_init_normal_
Ones initialization	nn_init_ones_
Orthogonal initialization	nn_init_orthogonal_
Sparse initialization	nn_init_sparse_
Truncated normal initialization	nn_init_trunc_normal_
Uniform initialization	nn_init_uniform_
Xavier normal initialization	nn_init_xavier_normal_
Xavier uniform initialization	nn_init_xavier_uniform_
Zeros initialization	nn_init_zeros_
Kullback-Leibler divergence loss	nn_kl_div_loss
L1 loss	nn_l1_loss
Layer normalization	nn_layer_norm
LeakyReLU module	nn_leaky_relu
Linear module	nn_linear
LogSigmoid module	nn_log_sigmoid
LogSoftmax module	nn_log_softmax
Applies a 1D power-average pooling over an input signal composed of several input planes.	nn_lp_pool1d
Applies a 2D power-average pooling over an input signal composed of several input planes.	nn_lp_pool2d
Applies a multi-layer long short-term memory (LSTM) RNN to an input sequence.	nn_lstm
Margin ranking loss	nn_margin_ranking_loss
MaxPool1D module	nn_max_pool1d
MaxPool2D module	nn_max_pool2d
Applies a 3D max pooling over an input signal composed of several input planes.	nn_max_pool3d
Computes a partial inverse of 'MaxPool1d'.	nn_max_unpool1d
Computes a partial inverse of 'MaxPool2d'.	nn_max_unpool2d
Computes a partial inverse of 'MaxPool3d'.	nn_max_unpool3d
Base class for all neural network modules.	nn_module
Container that allows named values	nn_module_dict
Holds submodules in a list.	nn_module_list
MSE loss	nn_mse_loss
Multi margin loss	nn_multi_margin_loss
MultiHead attention	nn_multihead_attention
Multilabel margin loss	nn_multilabel_margin_loss
Multi label soft margin loss	nn_multilabel_soft_margin_loss
Nll loss	nn_nll_loss
Pairwise distance	nn_pairwise_distance
Creates an 'nn_parameter'	nn_parameter
Poisson NLL loss	nn_poisson_nll_loss
PReLU module	nn_prelu
Prune top layer(s) of a network	nn_prune_head
ReLU module	nn_relu
ReLu6 module	nn_relu6
RNN module	nn_rnn
RReLU module	nn_rrelu
SELU module	nn_selu
A sequential container	nn_sequential
Sigmoid module	nn_sigmoid
Applies the Sigmoid Linear Unit (SiLU) function, element-wise. The SiLU function is also known as the swish function.	nn_silu
Smooth L1 loss	nn_smooth_l1_loss
Soft margin loss	nn_soft_margin_loss
Softmax module	nn_softmax
Softmax2d module	nn_softmax2d
Softmin	nn_softmin
Softplus module	nn_softplus
Softshrink module	nn_softshrink
Softsign module	nn_softsign
Tanh module	nn_tanh
Tanhshrink module	nn_tanhshrink
Threshold module	nn_threshold
Transformer Encoder Module (R torch)	nn_transformer_encoder
Transformer Encoder Layer Module (R torch)	nn_transformer_encoder_layer
Triplet margin loss	nn_triplet_margin_loss
Triplet margin with distance loss	nn_triplet_margin_with_distance_loss
Unflattens a tensor dim expanding it to a desired shape. For use with [nn_sequential.	nn_unflatten
Upsample module	nn_upsample
Clips gradient norm of an iterable of parameters.	nn_utils_clip_grad_norm_
Clips gradient of an iterable of parameters at specified value.	nn_utils_clip_grad_value_
Packs a Tensor containing padded sequences of variable length.	nn_utils_rnn_pack_padded_sequence
Packs a list of variable length Tensors	nn_utils_rnn_pack_sequence
Pads a packed batch of variable length sequences.	nn_utils_rnn_pad_packed_sequence
Pad a list of variable length Tensors with 'padding_value'	nn_utils_rnn_pad_sequence
nn_utils_weight_norm	nn_utils_weight_norm
Adaptive_avg_pool1d	nnf_adaptive_avg_pool1d
Adaptive_avg_pool2d	nnf_adaptive_avg_pool2d
Adaptive_avg_pool3d	nnf_adaptive_avg_pool3d
Adaptive_max_pool1d	nnf_adaptive_max_pool1d
Adaptive_max_pool2d	nnf_adaptive_max_pool2d
Adaptive_max_pool3d	nnf_adaptive_max_pool3d
Affine_grid	nnf_affine_grid
Alpha_dropout	nnf_alpha_dropout
Area under the Min(FPR, FNR) (AUM)	nnf_area_under_min_fpr_fnr
Avg_pool1d	nnf_avg_pool1d
Avg_pool2d	nnf_avg_pool2d
Avg_pool3d	nnf_avg_pool3d
Batch_norm	nnf_batch_norm
Bilinear	nnf_bilinear
Binary_cross_entropy	nnf_binary_cross_entropy
Binary_cross_entropy_with_logits	nnf_binary_cross_entropy_with_logits
Celu	nnf_celu nnf_celu_
Sparsemax	nnf_contrib_sparsemax
Conv_tbc	nnf_conv_tbc
Conv_transpose1d	nnf_conv_transpose1d
Conv_transpose2d	nnf_conv_transpose2d
Conv_transpose3d	nnf_conv_transpose3d
Conv1d	nnf_conv1d
Conv2d	nnf_conv2d
Conv3d	nnf_conv3d
Cosine_embedding_loss	nnf_cosine_embedding_loss
Cosine_similarity	nnf_cosine_similarity
Cross_entropy	nnf_cross_entropy
Ctc_loss	nnf_ctc_loss
Dropout	nnf_dropout
Dropout2d	nnf_dropout2d
Dropout3d	nnf_dropout3d
Elu	nnf_elu nnf_elu_
Embedding	nnf_embedding
Embedding_bag	nnf_embedding_bag
Fold	nnf_fold
Fractional_max_pool2d	nnf_fractional_max_pool2d
Fractional_max_pool3d	nnf_fractional_max_pool3d
Gelu	nnf_gelu
Glu	nnf_glu
Grid_sample	nnf_grid_sample
Group_norm	nnf_group_norm
Gumbel_softmax	nnf_gumbel_softmax
Hardshrink	nnf_hardshrink
Hardsigmoid	nnf_hardsigmoid
Hardswish	nnf_hardswish
Hardtanh	nnf_hardtanh nnf_hardtanh_
Hinge_embedding_loss	nnf_hinge_embedding_loss
Instance_norm	nnf_instance_norm
Interpolate	nnf_interpolate
Kl_div	nnf_kl_div
L1_loss	nnf_l1_loss
Layer_norm	nnf_layer_norm
Leaky_relu	nnf_leaky_relu
Linear	nnf_linear
Local_response_norm	nnf_local_response_norm
Log_softmax	nnf_log_softmax
Logsigmoid	nnf_logsigmoid
Lp_pool1d	nnf_lp_pool1d
Lp_pool2d	nnf_lp_pool2d
Margin_ranking_loss	nnf_margin_ranking_loss
Max_pool1d	nnf_max_pool1d
Max_pool2d	nnf_max_pool2d
Max_pool3d	nnf_max_pool3d
Max_unpool1d	nnf_max_unpool1d
Max_unpool2d	nnf_max_unpool2d
Max_unpool3d	nnf_max_unpool3d
Mse_loss	nnf_mse_loss
Multi head attention forward	nnf_multi_head_attention_forward
Multi_margin_loss	nnf_multi_margin_loss
Multilabel_margin_loss	nnf_multilabel_margin_loss
Multilabel_soft_margin_loss	nnf_multilabel_soft_margin_loss
Nll_loss	nnf_nll_loss
Normalize	nnf_normalize
One_hot	nnf_one_hot
Pad	nnf_pad
Pairwise_distance	nnf_pairwise_distance
Pdist	nnf_pdist
Pixel_shuffle	nnf_pixel_shuffle
Poisson_nll_loss	nnf_poisson_nll_loss
Prelu	nnf_prelu
Relu	nnf_relu nnf_relu_
Relu6	nnf_relu6
Rrelu	nnf_rrelu nnf_rrelu_
Selu	nnf_selu nnf_selu_
Sigmoid	nnf_sigmoid
Applies the Sigmoid Linear Unit (SiLU) function, element-wise. See 'nn_silu()' for more information.	nnf_silu
Smooth_l1_loss	nnf_smooth_l1_loss
Soft_margin_loss	nnf_soft_margin_loss
Softmax	nnf_softmax
Softmin	nnf_softmin
Softplus	nnf_softplus
Softshrink	nnf_softshrink
Softsign	nnf_softsign
Tanhshrink	nnf_tanhshrink
Threshold	nnf_threshold nnf_threshold_
Triplet_margin_loss	nnf_triplet_margin_loss
Triplet margin with distance loss	nnf_triplet_margin_with_distance_loss
Unfold	nnf_unfold
Adadelta optimizer	optim_adadelta
Adagrad optimizer	optim_adagrad
Implements Adam algorithm.	optim_adam
Implements AdamW algorithm	optim_adamw
Averaged Stochastic Gradient Descent optimizer	optim_asgd
LibTorch implementation of Adagrad	optim_ignite_adagrad
LibTorch implementation of Adam	optim_ignite_adam
LibTorch implementation of AdamW	optim_ignite_adamw
LibTorch implementation of RMSprop	optim_ignite_rmsprop
LibTorch implementation of SGD	optim_ignite_sgd
LBFGS optimizer	optim_lbfgs
Dummy value indicating a required value.	optim_required
RMSprop optimizer	optim_rmsprop
Implements the resilient backpropagation algorithm.	optim_rprop
SGD optimizer	optim_sgd
Creates a custom optimizer	optimizer
Abstract Base Class for LibTorch Optimizers	optimizer_ignite
Abstract Base Class for LibTorch Optimizers	OptimizerIgnite
Creates a new Sampler	sampler
Configure the CPU memory allocator	set_cpu_allocator_config
Dataset wrapping tensors.	tensor_dataset
Number of threads	threads torch_get_num_interop_threads torch_get_num_threads torch_set_num_interop_threads torch_set_num_threads
Abs	torch_abs
Absolute	torch_absolute
Acos	torch_acos
Acosh	torch_acosh
Adaptive_avg_pool1d	torch_adaptive_avg_pool1d
Add	torch_add
Addbmm	torch_addbmm
Addcdiv	torch_addcdiv
Addcmul	torch_addcmul
Addmm	torch_addmm
Addmv	torch_addmv
Addr	torch_addr
Allclose	torch_allclose
Amax	torch_amax
Amin	torch_amin
Angle	torch_angle
Arange	torch_arange
Arccos	torch_arccos
Arccosh	torch_arccosh
Arcsin	torch_arcsin
Arcsinh	torch_arcsinh
Arctan	torch_arctan
Arctanh	torch_arctanh
Argmax	torch_argmax
Argmin	torch_argmin
Argsort	torch_argsort
As_strided	torch_as_strided
Asin	torch_asin
Asinh	torch_asinh
Atan	torch_atan
Atan2	torch_atan2
Atanh	torch_atanh
Atleast_1d	torch_atleast_1d
Atleast_2d	torch_atleast_2d
Atleast_3d	torch_atleast_3d
Avg_pool1d	torch_avg_pool1d
Baddbmm	torch_baddbmm
Bartlett_window	torch_bartlett_window
Bernoulli	torch_bernoulli
Bincount	torch_bincount
Bitwise_and	torch_bitwise_and
Bitwise_not	torch_bitwise_not
Bitwise_or	torch_bitwise_or
Bitwise_xor	torch_bitwise_xor
Blackman_window	torch_blackman_window
Block_diag	torch_block_diag
Bmm	torch_bmm
Broadcast_tensors	torch_broadcast_tensors
Bucketize	torch_bucketize
Can_cast	torch_can_cast
Cartesian_prod	torch_cartesian_prod
Cat	torch_cat
Cdist	torch_cdist
Ceil	torch_ceil
Celu	torch_celu
Celu_	torch_celu_
Chain_matmul	torch_chain_matmul
Channel_shuffle	torch_channel_shuffle
Cholesky	torch_cholesky
Cholesky_inverse	torch_cholesky_inverse
Cholesky_solve	torch_cholesky_solve
Chunk	torch_chunk
Clamp	torch_clamp
Clip	torch_clip
Clone	torch_clone
Combinations	torch_combinations
Complex	torch_complex
Conj	torch_conj
Conv_tbc	torch_conv_tbc
Conv_transpose1d	torch_conv_transpose1d
Conv_transpose2d	torch_conv_transpose2d
Conv_transpose3d	torch_conv_transpose3d
Conv1d	torch_conv1d
Conv2d	torch_conv2d
Conv3d	torch_conv3d
Cos	torch_cos
Cosh	torch_cosh
Cosine_similarity	torch_cosine_similarity
Count_nonzero	torch_count_nonzero
Cross	torch_cross
Cummax	torch_cummax
Cummin	torch_cummin
Cumprod	torch_cumprod
Cumsum	torch_cumsum
Deg2rad	torch_deg2rad
Dequantize	torch_dequantize
Det	torch_det
Create a Device object	torch_device
Diag	torch_diag
Diag_embed	torch_diag_embed
Diagflat	torch_diagflat
Diagonal	torch_diagonal
Computes the n-th forward difference along the given dimension.	torch_diff
Digamma	torch_digamma
Dist	torch_dist
Div	torch_div
Divide	torch_divide
Dot	torch_dot
Dstack	torch_dstack
Torch data types	torch_bfloat16 torch_bool torch_cdouble torch_cfloat torch_cfloat128 torch_cfloat32 torch_cfloat64 torch_chalf torch_double torch_dtype torch_float torch_float16 torch_float32 torch_float64 torch_float8_e4m3fn torch_float8_e5m2 torch_half torch_int torch_int16 torch_int32 torch_int64 torch_int8 torch_long torch_qint32 torch_qint8 torch_quint8 torch_short torch_uint8
Eig	torch_eig
Einsum	torch_einsum
Empty	torch_empty
Empty_like	torch_empty_like
Empty_strided	torch_empty_strided
Eq	torch_eq
Equal	torch_equal
Erf	torch_erf
Erfc	torch_erfc
Erfinv	torch_erfinv
Exp	torch_exp
Exp2	torch_exp2
Expm1	torch_expm1
Eye	torch_eye
Fft	torch_fft_fft
fftfreq	torch_fft_fftfreq
Ifft	torch_fft_ifft
Irfft	torch_fft_irfft
Rfft	torch_fft_rfft
Floating point type info	torch_finfo
Fix	torch_fix
Flatten	torch_flatten
Flip	torch_flip
Fliplr	torch_fliplr
Flipud	torch_flipud
Floor	torch_floor
Floor_divide	torch_floor_divide
Fmod	torch_fmod
Frac	torch_frac
Full	torch_full
Full_like	torch_full_like
Gather	torch_gather
Gcd	torch_gcd
Ge	torch_ge
Create a Generator object	torch_generator
Geqrf	torch_geqrf
Ger	torch_ger
RNG state management	cuda_get_rng_state cuda_set_rng_state torch_get_rng_state torch_set_rng_state
Greater	torch_greater
Greater_equal	torch_greater_equal
Gt	torch_gt
Hamming_window	torch_hamming_window
Hann_window	torch_hann_window
Heaviside	torch_heaviside
Histc	torch_histc
Hstack	torch_hstack
Hypot	torch_hypot
I0	torch_i0
Integer type info	torch_iinfo
Imag	torch_imag
Index torch tensors	torch_index
Modify values selected by 'indices'.	torch_index_put
In-place version of 'torch_index_put'.	torch_index_put_
Index_select	torch_index_select
A simple exported version of install_path Returns the torch installation path.	torch_install_path
Inverse	torch_inverse
Is_complex	torch_is_complex
Is_floating_point	torch_is_floating_point
Verifies if torch is installed	torch_is_installed
Is_nonzero	torch_is_nonzero
Isclose	torch_isclose
Isfinite	torch_isfinite
Isinf	torch_isinf
Isnan	torch_isnan
Isneginf	torch_isneginf
Isposinf	torch_isposinf
Isreal	torch_isreal
Istft	torch_istft
Kaiser_window	torch_kaiser_window
Kronecker product	torch_kron
Kthvalue	torch_kthvalue
Creates the corresponding layout	torch_layout torch_sparse_coo torch_strided
Lcm	torch_lcm
Ldexp	torch_ldexp
Le	torch_le
Lerp	torch_lerp
Less	torch_less
Less_equal	torch_less_equal
Lgamma	torch_lgamma
Linspace	torch_linspace
Loads a saved object	torch_load
Log	torch_log
Log10	torch_log10
Log1p	torch_log1p
Log2	torch_log2
Logaddexp	torch_logaddexp
Logaddexp2	torch_logaddexp2
Logcumsumexp	torch_logcumsumexp
Logdet	torch_logdet
Logical_and	torch_logical_and
Logical_not	torch_logical_not
Logical_or	torch_logical_or
Logical_xor	torch_logical_xor
Logit	torch_logit
Logspace	torch_logspace
Logsumexp	torch_logsumexp
Lstsq	torch_lstsq
Lt	torch_lt
LU	torch_lu
Lu_solve	torch_lu_solve
Lu_unpack	torch_lu_unpack
Sets the seed for generating random numbers.	local_torch_manual_seed torch_manual_seed with_torch_manual_seed
Masked_select	torch_masked_select
Matmul	torch_matmul
Matrix_exp	torch_matrix_exp
Matrix_power	torch_matrix_power
Matrix_rank	torch_matrix_rank
Max	torch_max
Maximum	torch_maximum
Mean	torch_mean
Median	torch_median
Memory format	torch_channels_last_format torch_contiguous_format torch_memory_format torch_preserve_format
Meshgrid	torch_meshgrid
Min	torch_min
Minimum	torch_minimum
Mm	torch_mm
Mode	torch_mode
Movedim	torch_movedim
Mul	torch_mul
Multinomial	torch_multinomial
Multiply	torch_multiply
Mv	torch_mv
Mvlgamma	torch_mvlgamma
Nanquantile	torch_nanquantile
Nansum	torch_nansum
Narrow	torch_narrow
Ne	torch_ne
Neg	torch_neg
Negative	torch_negative
Nextafter	torch_nextafter
Nonzero	torch_nonzero
Norm	torch_norm
Normal	torch_normal
Not_equal	torch_not_equal
Ones	torch_ones
Ones_like	torch_ones_like
Orgqr	torch_orgqr
Ormqr	torch_ormqr
Outer	torch_outer
Pdist	torch_pdist
Pinverse	torch_pinverse
Pixel_shuffle	torch_pixel_shuffle
Poisson	torch_poisson
Polar	torch_polar
Polygamma	torch_polygamma
Pow	torch_pow
Prod	torch_prod
Promote_types	torch_promote_types
Qr	torch_qr
Creates the corresponding Scheme object	torch_per_channel_affine torch_per_channel_symmetric torch_per_tensor_affine torch_per_tensor_symmetric torch_qscheme
Quantile	torch_quantile
Quantize_per_channel	torch_quantize_per_channel
Quantize_per_tensor	torch_quantize_per_tensor
Rad2deg	torch_rad2deg
Rand	torch_rand
Rand_like	torch_rand_like
Randint	torch_randint
Randint_like	torch_randint_like
Randn	torch_randn
Randn_like	torch_randn_like
Randperm	torch_randperm
Range	torch_range
Real	torch_real
Reciprocal	torch_reciprocal
Creates the reduction objet	torch_reduction torch_reduction_mean torch_reduction_none torch_reduction_sum
Relu	torch_relu
Relu_	torch_relu_
Remainder	torch_remainder
Renorm	torch_renorm
Repeat_interleave	torch_repeat_interleave
Reshape	torch_reshape
Result_type	torch_result_type
Roll	torch_roll
Rot90	torch_rot90
Round	torch_round
Rrelu_	torch_rrelu_
Rsqrt	torch_rsqrt
Saves an object to a disk file.	torch_save
Scalar tensor	torch_scalar_tensor
Scaled Dot Product Attention	torch_scaled_dot_product_attention
Searchsorted	torch_searchsorted
Selu	torch_selu
Selu_	torch_selu_
Serialize a torch object returning a raw object	torch_serialize
Gets and sets the default floating point dtype.	torch_get_default_dtype torch_set_default_dtype
Sgn	torch_sgn
Sigmoid	torch_sigmoid
Sign	torch_sign
Signbit	torch_signbit
Sin	torch_sin
Sinh	torch_sinh
Slogdet	torch_slogdet
Sort	torch_sort
Sparse_coo_tensor	torch_sparse_coo_tensor
Sparse_sampled_addmm	torch_sparse_sampled_addmm
Split	torch_split
Sqrt	torch_sqrt
Square	torch_square
Squeeze	torch_squeeze
Stack	torch_stack
Std	torch_std
Std_mean	torch_std_mean
Stft	torch_stft
Sub	torch_sub
Subtract	torch_subtract
Sum	torch_sum
Svd	torch_svd
T	torch_t
Take	torch_take
Selects values from input at the 1-dimensional indices from indices along the given dim.	torch_take_along_dim
Tan	torch_tan
Tanh	torch_tanh
Converts R objects to a torch tensor	torch_tensor
Creates a tensor from a buffer of memory	buffer_from_torch_tensor torch_tensor_from_buffer
Tensordot	torch_tensordot
Threshold_	torch_threshold_
Topk	torch_topk
Trace	torch_trace
Transpose	torch_transpose
Trapz	torch_trapz
Triangular_solve	torch_triangular_solve
Tril	torch_tril
Tril_indices	torch_tril_indices
Triu	torch_triu
Triu_indices	torch_triu_indices
TRUE_divide	torch_true_divide
Trunc	torch_trunc
Unbind	torch_unbind
Unique_consecutive	torch_unique_consecutive
Unsafe_chunk	torch_unsafe_chunk
Unsafe_split	torch_unsafe_split
Unsqueeze	torch_unsqueeze
Vander	torch_vander
Var	torch_var
Var_mean	torch_var_mean
Vdot	torch_vdot
View_as_complex	torch_view_as_complex
View_as_real	torch_view_as_real
Vstack	torch_vstack
Where	torch_where
Zeros	torch_zeros
Zeros_like	torch_zeros_like
Context-manager that enable anomaly detection for the autograd engine.	with_detect_anomaly
Enable grad	local_enable_grad with_enable_grad
Temporarily modify gradient recording.	local_no_grad with_no_grad

Package: torch 0.17.0.9000

torch: Tensors and Neural Networks with 'GPU' Acceleration

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