All modules for which code is available
- torch
- torch._C
- torch._C._distributed_autograd
- torch._C._distributed_c10d
- torch._C._distributed_rpc
- torch._C._fft
- torch._C._linalg
- torch._C._nn
- torch.__config__
- torch._jit_internal
- torch._lobpcg
- torch._lowrank
- torch._tensor_str
- torch._utils
- torch.autograd
- torch.autograd.anomaly_mode
- torch.autograd.function
- torch.autograd.functional
- torch.autograd.grad_mode
- torch.autograd.gradcheck
- torch.autograd.profiler
- torch.backends.cuda
- torch.backends.cudnn
- torch.backends.mkl
- torch.backends.mkldnn
- torch.backends.openmp
- torch.cuda
- torch.cuda.amp.autocast_mode
- torch.cuda.amp.grad_scaler
- torch.cuda.memory
- torch.cuda.nvtx
- torch.cuda.random
- torch.cuda.streams
- torch.distributed
- torch.distributed.algorithms.ddp_comm_hooks.default_hooks
- torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook
- torch.distributed.autograd
- torch.distributed.distributed_c10d
- torch.distributed.optim.optimizer
- torch.distributed.pipeline.sync.pipe
- torch.distributed.pipeline.sync.skip.skippable
- torch.distributed.rpc
- torch.distributions.bernoulli
- torch.distributions.beta
- torch.distributions.binomial
- torch.distributions.categorical
- torch.distributions.cauchy
- torch.distributions.chi2
- torch.distributions.constraint_registry
- torch.distributions.constraints
- torch.distributions.continuous_bernoulli
- torch.distributions.dirichlet
- torch.distributions.distribution
- torch.distributions.exp_family
- torch.distributions.exponential
- torch.distributions.fishersnedecor
- torch.distributions.gamma
- torch.distributions.geometric
- torch.distributions.gumbel
- torch.distributions.half_cauchy
- torch.distributions.half_normal
- torch.distributions.independent
- torch.distributions.kl
- torch.distributions.kumaraswamy
- torch.distributions.laplace
- torch.distributions.lkj_cholesky
- torch.distributions.log_normal
- torch.distributions.lowrank_multivariate_normal
- torch.distributions.mixture_same_family
- torch.distributions.multinomial
- torch.distributions.multivariate_normal
- torch.distributions.negative_binomial
- torch.distributions.normal
- torch.distributions.one_hot_categorical
- torch.distributions.pareto
- torch.distributions.poisson
- torch.distributions.relaxed_bernoulli
- torch.distributions.relaxed_categorical
- torch.distributions.studentT
- torch.distributions.transformed_distribution
- torch.distributions.transforms
- torch.distributions.uniform
- torch.distributions.von_mises
- torch.distributions.weibull
- torch.functional
- torch.futures
- torch.fx.graph
- torch.fx.graph_module
- torch.fx.interpreter
- torch.fx.node
- torch.fx.proxy
- torch.fx.subgraph_rewriter
- torch.fx.symbolic_trace
- torch.hub
- torch.jit
- torch.multiprocessing
- torch.nn.functional
- torch.nn.init
- torch.nn.intrinsic.modules.fused
- torch.nn.intrinsic.qat.modules.conv_fused
- torch.nn.intrinsic.qat.modules.linear_relu
- torch.nn.intrinsic.quantized.modules.conv_relu
- torch.nn.intrinsic.quantized.modules.linear_relu
- torch.nn.modules.activation
- torch.nn.modules.adaptive
- torch.nn.modules.batchnorm
- torch.nn.modules.channelshuffle
- torch.nn.modules.container
- torch.nn.modules.conv
- torch.nn.modules.distance
- torch.nn.modules.dropout
- torch.nn.modules.flatten
- torch.nn.modules.fold
- torch.nn.modules.instancenorm
- torch.nn.modules.lazy
- torch.nn.modules.linear
- torch.nn.modules.loss
- torch.nn.modules.module
- torch.nn.modules.normalization
- torch.nn.modules.padding
- torch.nn.modules.pixelshuffle
- torch.nn.modules.pooling
- torch.nn.modules.rnn
- torch.nn.modules.sparse
- torch.nn.modules.transformer
- torch.nn.modules.upsampling
- torch.nn.parallel.comm
- torch.nn.parallel.data_parallel
- torch.nn.parallel.distributed
- torch.nn.parameter
- torch.nn.qat.modules.conv
- torch.nn.qat.modules.linear
- torch.nn.quantized.dynamic.modules.linear
- torch.nn.quantized.dynamic.modules.rnn
- torch.nn.quantized.functional
- torch.nn.quantized.modules
- torch.nn.quantized.modules.activation
- torch.nn.quantized.modules.batchnorm
- torch.nn.quantized.modules.conv
- torch.nn.quantized.modules.embedding_ops
- torch.nn.quantized.modules.functional_modules
- torch.nn.quantized.modules.linear
- torch.nn.quantized.modules.normalization
- torch.nn.utils.clip_grad
- torch.nn.utils.convert_parameters
- torch.nn.utils.prune
- torch.nn.utils.rnn
- torch.nn.utils.spectral_norm
- torch.nn.utils.weight_norm
- torch.onnx
- torch.optim.adadelta
- torch.optim.adagrad
- torch.optim.adam
- torch.optim.adamax
- torch.optim.adamw
- torch.optim.asgd
- torch.optim.lbfgs
- torch.optim.lr_scheduler
- torch.optim.optimizer
- torch.optim.rmsprop
- torch.optim.rprop
- torch.optim.sgd
- torch.optim.sparse_adam
- torch.overrides
- torch.profiler.profiler
- torch.quantization
- torch.quantization.fake_quantize
- torch.quantization.fuse_modules
- torch.quantization.observer
- torch.quantization.qconfig
- torch.quantization.quantize
- torch.quantization.stubs
- torch.quasirandom
- torch.random
- torch.serialization
- torch.sparse
- torch.storage
- torch.tensor
- torch.utils.benchmark.utils.common
- torch.utils.benchmark.utils.timer
- torch.utils.benchmark.utils.valgrind_wrapper.timer_interface
- torch.utils.checkpoint
- torch.utils.cpp_extension
- torch.utils.data._utils.worker
- torch.utils.data.dataloader
- torch.utils.data.dataset
- torch.utils.data.distributed
- torch.utils.data.sampler
- torch.utils.mobile_optimizer
- torch.utils.tensorboard.writer
- typing
