- T (torch.Tensor 属性)
- t() (在模块 torch 中)
- t_() (torch.Tensor 方法)
- Tag (torch 中的类)
- take() (在模块 torch 中)
- take_along_dim() (在模块 torch 中)
- tan() (在模块 torch 中)
- tan_() (torch.Tensor 方法)
- tangent (torch.autograd.forward_ad.UnpackedDualTensor 属性)
- Tanh (torch.nn 中的类)
- tanh() (在模块 torch 中)
- tanh_() (torch.Tensor 方法)
- Tanhshrink (torch.nn 中的类)
- tanhshrink() (在模块 torch.nn.functional 中)
- TanhTransform (torch.distributions.transforms 中的类)
- TCPStore (torch.distributed 中的类)
- temperature (torch.distributions.relaxed_bernoulli.RelaxedBernoulli 属性)
- temperature() (在模块 torch.cuda 中)
- Tensor (torch 中的类)
- tensor() (在模块 torch 中)
- tensor_split() (在模块 torch 中)
- tensor_storage_size() (torch.distributed.checkpoint.planner.WriteItem 方法)
- tensorboard_trace_handler() (在模块 torch.profiler 中)
- TensorboardEventHandler (torch.monitor 中的类)
- TensorChunkSpec (torch.distributed.pipelining.microbatch 中的类)
- TensorDataset (torch.utils.data 中的类)
- tensordot() (在模块 torch 中)
- tensorinv() (在模块 torch.linalg 中)
- TensorPipeRpcBackendOptions (torch.distributed.rpc 中的类)
- tensorsolve() (在模块 torch.linalg 中)
- then() (torch.futures.Future 方法)
- threshold (torch.ao.nn.quantized.functional 中的类)
- Threshold (torch.nn 中的类)
- threshold() (在模块 torch.nn.functional 中)
- threshold_() (在模块 torch.nn.functional 中)
- tile() (在模块 torch 中)
- timeit() (torch.utils.benchmark.Timer 方法)
- Timer (torch.utils.benchmark 中的类)
- TimerClient (torch.distributed.elastic.timer 中的类)
- TimerRequest (torch.distributed.elastic.timer 中的类)
- TimerServer (torch.distributed.elastic.timer 中的类)
- timestamp (torch.monitor.Event 属性)
- to() (torch.jit.ScriptModule 方法)
- to_bool() (torch.fx.Tracer 方法)
- to_dense() (torch.Tensor 方法)
- to_dict() (torch.ao.quantization.backend_config.BackendConfig 方法)
- to_dlpack() (位于 torch.utils.dlpack 模块中)
- to_empty() (torch.jit.ScriptModule 方法)
- to_folder() (torch.fx.GraphModule 方法)
- to_here() (torch.distributed.rpc.PyRRef 方法)
- to_mkldnn() (torch.Tensor 方法)
- to_padded_tensor() (位于 torch.nested 模块中)
- to_sparse() (torch.Tensor 方法)
- to_sparse_bsc() (torch.Tensor 方法)
- to_sparse_bsr() (torch.Tensor 方法)
- to_sparse_coo() (torch.Tensor 方法)
- to_sparse_csc() (torch.Tensor 方法)
- to_sparse_csr() (torch.Tensor 方法)
- tolist() (torch.Tensor 方法)
- topk() (位于 torch 模块中)
- torch
- torch.__config__
- torch.__future__
- torch._logging
- torch.amp
- torch.amp.autocast_mode
- torch.amp.grad_scaler
- torch.ao
- torch.ao.nn
- torch.ao.nn.intrinsic
- torch.ao.nn.intrinsic.modules
- torch.ao.nn.intrinsic.modules.fused
- torch.ao.nn.intrinsic.qat
- torch.ao.nn.intrinsic.qat.modules
- torch.ao.nn.intrinsic.qat.modules.conv_fused
- torch.ao.nn.intrinsic.qat.modules.linear_fused
- torch.ao.nn.intrinsic.qat.modules.linear_relu
- torch.ao.nn.intrinsic.quantized
- torch.ao.nn.intrinsic.quantized.dynamic
- torch.ao.nn.intrinsic.quantized.dynamic.modules
- torch.ao.nn.intrinsic.quantized.dynamic.modules.linear_relu
- torch.ao.nn.intrinsic.quantized.modules
- torch.ao.nn.intrinsic.quantized.modules.bn_relu
- torch.ao.nn.intrinsic.quantized.modules.conv_add
- torch.ao.nn.intrinsic.quantized.modules.conv_relu
- torch.ao.nn.intrinsic.quantized.modules.linear_relu
- torch.ao.nn.qat
- torch.ao.nn.qat.dynamic
- torch.ao.nn.qat.dynamic.modules
- torch.ao.nn.qat.dynamic.modules.linear
- torch.ao.nn.qat.modules
- torch.ao.nn.qat.modules.conv
- torch.ao.nn.qat.modules.embedding_ops
- torch.ao.nn.qat.modules.linear
- torch.ao.nn.quantizable
- torch.ao.nn.quantizable.modules
- torch.ao.nn.quantizable.modules.activation
- torch.ao.nn.quantizable.modules.rnn
- torch.ao.nn.quantized
- torch.ao.nn.quantized.dynamic
- torch.ao.nn.quantized.dynamic.modules
- torch.ao.nn.quantized.dynamic.modules.conv
- torch.ao.nn.quantized.dynamic.modules.linear
- torch.ao.nn.quantized.dynamic.modules.rnn
- torch.ao.nn.quantized.functional
- torch.ao.nn.quantized.modules
- torch.ao.nn.quantized.modules.activation
- torch.ao.nn.quantized.modules.batchnorm
- torch.ao.nn.quantized.modules.conv
- torch.ao.nn.quantized.modules.dropout
- torch.ao.nn.quantized.modules.embedding_ops
- torch.ao.nn.quantized.modules.functional_modules
- torch.ao.nn.quantized.modules.linear
- torch.ao.nn.quantized.modules.normalization
- torch.ao.nn.quantized.modules.rnn
- torch.ao.nn.quantized.modules.utils
- torch.ao.nn.quantized.reference
- torch.ao.nn.quantized.reference.modules
- torch.ao.nn.quantized.reference.modules.conv
- torch.ao.nn.quantized.reference.modules.linear
- torch.ao.nn.quantized.reference.modules.rnn
- torch.ao.nn.quantized.reference.modules.sparse
- torch.ao.nn.quantized.reference.modules.utils
- torch.ao.nn.sparse
- torch.ao.nn.sparse.quantized
- torch.ao.nn.sparse.quantized.dynamic
- torch.ao.nn.sparse.quantized.dynamic.linear
- torch.ao.nn.sparse.quantized.linear
- torch.ao.nn.sparse.quantized.utils
- torch.ao.ns
- torch.ao.ns._numeric_suite
- torch.ao.ns._numeric_suite_fx
- torch.ao.ns.fx
- torch.ao.ns.fx.graph_matcher
- torch.ao.ns.fx.graph_passes
- torch.ao.ns.fx.mappings
- torch.ao.ns.fx.n_shadows_utils
- torch.ao.ns.fx.ns_types
- torch.ao.ns.fx.pattern_utils
- torch.ao.ns.fx.qconfig_multi_mapping
- torch.ao.ns.fx.utils
- torch.ao.ns.fx.weight_utils
- torch.ao.pruning
- torch.ao.pruning.scheduler
- torch.ao.pruning.scheduler.base_scheduler
- torch.ao.pruning.scheduler.cubic_scheduler
- torch.ao.pruning.scheduler.lambda_scheduler
- torch.ao.pruning.sparsifier
- torch.ao.pruning.sparsifier.base_sparsifier
- torch.ao.pruning.sparsifier.nearly_diagonal_sparsifier
- torch.ao.pruning.sparsifier.utils
- torch.ao.pruning.sparsifier.weight_norm_sparsifier
- torch.ao.quantization
- torch.ao.quantization.backend_config
- torch.ao.quantization.backend_config.backend_config
- torch.ao.quantization.backend_config.executorch
- torch.ao.quantization.backend_config.fbgemm
- torch.ao.quantization.backend_config.native
- torch.ao.quantization.backend_config.observation_type
- torch.ao.quantization.backend_config.onednn
- torch.ao.quantization.backend_config.qnnpack
- torch.ao.quantization.backend_config.tensorrt
- torch.ao.quantization.backend_config.utils
- torch.ao.quantization.backend_config.x86
- torch.ao.quantization.fake_quantize
- torch.ao.quantization.fuse_modules
- torch.ao.quantization.fuser_method_mappings
- torch.ao.quantization.fx
- torch.ao.quantization.fx.convert
- torch.ao.quantization.fx.custom_config
- torch.ao.quantization.fx.fuse
- torch.ao.quantization.fx.fuse_handler
- torch.ao.quantization.fx.graph_module
- torch.ao.quantization.fx.lower_to_fbgemm
- torch.ao.quantization.fx.lower_to_qnnpack
- torch.ao.quantization.fx.lstm_utils
- torch.ao.quantization.fx.match_utils
- torch.ao.quantization.fx.pattern_utils
- torch.ao.quantization.fx.prepare
- torch.ao.quantization.fx.qconfig_mapping_utils
- torch.ao.quantization.fx.quantize_handler
- torch.ao.quantization.fx.tracer
- torch.ao.quantization.fx.utils
- torch.ao.quantization.observer
- torch.ao.quantization.pt2e
- torch.ao.quantization.pt2e.duplicate_dq_pass
- torch.ao.quantization.pt2e.export_utils
- torch.ao.quantization.pt2e.generate_numeric_debug_handle
- torch.ao.quantization.pt2e.graph_utils
- torch.ao.quantization.pt2e.port_metadata_pass
- torch.ao.quantization.pt2e.prepare
- torch.ao.quantization.pt2e.qat_utils
- torch.ao.quantization.pt2e.representation
- torch.ao.quantization.pt2e.representation.rewrite
- torch.ao.quantization.pt2e.utils
- torch.ao.quantization.qconfig
- torch.ao.quantization.qconfig_mapping
- torch.ao.quantization.quant_type
- torch.ao.quantization.quantization_mappings
- torch.ao.quantization.quantize_fx
- torch.ao.quantization.quantize_jit
- torch.ao.quantization.quantize_pt2e
- torch.ao.quantization.quantizer
- torch.ao.quantization.quantizer.composable_quantizer
- torch.ao.quantization.quantizer.embedding_quantizer
- torch.ao.quantization.quantizer.quantizer
- torch.ao.quantization.quantizer.utils
- torch.ao.quantization.quantizer.x86_inductor_quantizer
- torch.ao.quantization.quantizer.xnnpack_quantizer
- torch.ao.quantization.quantizer.xnnpack_quantizer_utils
- torch.ao.quantization.stubs
- torch.ao.quantization.utils
- torch.autograd
- torch.autograd.anomaly_mode
- torch.autograd.forward_ad
- torch.autograd.function
- torch.autograd.functional
- torch.autograd.grad_mode
- torch.autograd.gradcheck
- torch.autograd.graph
- torch.autograd.profiler
- torch.autograd.profiler_legacy
- torch.autograd.profiler_util
- torch.autograd.variable
- torch.backends
- torch.backends.cpu
- torch.backends.cuda
- torch.backends.cudnn
- torch.backends.cudnn.rnn
- torch.backends.mha
- torch.backends.mkl
- torch.backends.mkldnn
- torch.backends.mps
- torch.backends.nnpack
- torch.backends.openmp
- torch.backends.opt_einsum
- torch.backends.quantized
- torch.backends.xeon
- torch.backends.xeon.run_cpu
- torch.backends.xnnpack
- torch.compiler
- torch.contrib
- torch.cpu
- torch.cpu.amp
- torch.cpu.amp.autocast_mode
- torch.cpu.amp.grad_scaler
- torch.cuda
- torch.cuda._sanitizer
- torch.cuda.amp
- torch.cuda.amp.autocast_mode
- torch.cuda.amp.common
- torch.cuda.amp.grad_scaler
- torch.cuda.comm
- torch.cuda.error
- torch.cuda.graphs
- torch.cuda.jiterator
- torch.cuda.memory
- torch.cuda.nccl
- torch.cuda.nvtx
- torch.cuda.profiler
- torch.cuda.random
- torch.cuda.sparse
- torch.cuda.streams
- torch.cuda.tunable
- torch.distributed
- torch.distributed.algorithms
- torch.distributed.algorithms.ddp_comm_hooks
- torch.distributed.algorithms.ddp_comm_hooks.ddp_zero_hook
- torch.distributed.algorithms.ddp_comm_hooks.debugging_hooks
- torch.distributed.algorithms.ddp_comm_hooks.default_hooks
- torch.distributed.algorithms.ddp_comm_hooks.mixed_precision_hooks
- torch.distributed.algorithms.ddp_comm_hooks.optimizer_overlap_hooks
- torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook
- torch.distributed.algorithms.ddp_comm_hooks.powerSGD_hook
- torch.distributed.algorithms.ddp_comm_hooks.quantization_hooks
- torch.distributed.algorithms.join
- torch.distributed.algorithms.model_averaging
- torch.distributed.algorithms.model_averaging.averagers
- torch.distributed.algorithms.model_averaging.hierarchical_model_averager
- torch.distributed.algorithms.model_averaging.utils
- torch.distributed.argparse_util
- torch.distributed.autograd
- torch.distributed.c10d_logger
- torch.distributed.checkpoint
- torch.distributed.checkpoint.api
- torch.distributed.checkpoint.default_planner
- torch.distributed.checkpoint.filesystem
- torch.distributed.checkpoint.format_utils
- torch.distributed.checkpoint.logger
- torch.distributed.checkpoint.logging_handlers
- torch.distributed.checkpoint.metadata
- torch.distributed.checkpoint.optimizer
- torch.distributed.checkpoint.planner
- torch.distributed.checkpoint.planner_helpers
- torch.distributed.checkpoint.resharding
- torch.distributed.checkpoint.staging
- torch.distributed.checkpoint.state_dict
- torch.distributed.checkpoint.state_dict_loader
- torch.distributed.checkpoint.state_dict_saver
- torch.distributed.checkpoint.stateful
- torch.distributed.checkpoint.storage
- torch.distributed.checkpoint.utils
- torch.distributed.collective_utils
- torch.distributed.constants
- torch.distributed.device_mesh
- torch.distributed.distributed_c10d
- torch.distributed.elastic
- torch.distributed.elastic.agent
- torch.distributed.elastic.agent.server
- torch.distributed.elastic.agent.server.api
- torch.distributed.elastic.agent.server.health_check_server
- torch.distributed.elastic.agent.server.local_elastic_agent
- torch.distributed.elastic.control_plane
- torch.distributed.elastic.events
- torch.distributed.elastic.events.api
- torch.distributed.elastic.events.handlers
- torch.distributed.elastic.metrics
- torch.distributed.elastic.metrics.api
- torch.distributed.elastic.multiprocessing
- torch.distributed.elastic.multiprocessing.api
- torch.distributed.elastic.multiprocessing.errors
- torch.distributed.elastic.multiprocessing.errors.error_handler
- torch.distributed.elastic.multiprocessing.errors.handlers
- torch.distributed.elastic.multiprocessing.redirects
- torch.distributed.elastic.multiprocessing.subprocess_handler
- torch.distributed.elastic.multiprocessing.subprocess_handler.handlers
- torch.distributed.elastic.multiprocessing.subprocess_handler.subprocess_handler
- torch.distributed.elastic.multiprocessing.tail_log
- torch.distributed.elastic.rendezvous
- torch.distributed.elastic.rendezvous.api
- torch.distributed.elastic.rendezvous.c10d_rendezvous_backend
- torch.distributed.elastic.rendezvous.dynamic_rendezvous
- torch.distributed.elastic.rendezvous.etcd_rendezvous
- torch.distributed.elastic.rendezvous.etcd_rendezvous_backend
- torch.distributed.elastic.rendezvous.etcd_server
- torch.distributed.elastic.rendezvous.etcd_store
- torch.distributed.elastic.rendezvous.registry
- torch.distributed.elastic.rendezvous.static_tcp_rendezvous
- torch.distributed.elastic.rendezvous.utils
- torch.distributed.elastic.timer
- torch.distributed.elastic.timer.api
- torch.distributed.elastic.timer.debug_info_logging
- torch.distributed.elastic.timer.file_based_local_timer
- torch.distributed.elastic.timer.local_timer
- torch.distributed.elastic.utils
- torch.distributed.elastic.utils.api
- torch.distributed.elastic.utils.data
- torch.distributed.elastic.utils.data.cycling_iterator
- torch.distributed.elastic.utils.data.elastic_distributed_sampler
- torch.distributed.elastic.utils.distributed
- torch.distributed.elastic.utils.log_level
- torch.distributed.elastic.utils.logging
- torch.distributed.elastic.utils.store
- torch.distributed.fsdp
- torch.distributed.fsdp.api
- torch.distributed.fsdp.fully_sharded_data_parallel
- torch.distributed.fsdp.sharded_grad_scaler
- torch.distributed.fsdp.wrap
- torch.distributed.launch
- torch.distributed.launcher
- torch.distributed.launcher.api
- torch.distributed.logging_handlers
- torch.distributed.nn
- torch.distributed.nn.api
- torch.distributed.nn.api.remote_module
- torch.distributed.nn.functional
- torch.distributed.nn.jit
- torch.distributed.nn.jit.instantiator
- torch.distributed.nn.jit.templates
- torch.distributed.nn.jit.templates.remote_module_template
- torch.distributed.optim
- torch.distributed.optim.apply_optimizer_in_backward
- torch.distributed.optim.functional_adadelta
- torch.distributed.optim.functional_adagrad
- torch.distributed.optim.functional_adam
- torch.distributed.optim.functional_adamax
- torch.distributed.optim.functional_adamw
- torch.distributed.optim.functional_rmsprop
- torch.distributed.optim.functional_rprop
- torch.distributed.optim.functional_sgd
- torch.distributed.optim.named_optimizer
- torch.distributed.optim.optimizer
- torch.distributed.optim.post_localSGD_optimizer
- torch.distributed.optim.utils
- torch.distributed.optim.zero_redundancy_optimizer
- torch.distributed.pipelining
- torch.distributed.pipelining.microbatch
- torch.distributed.pipelining.schedules
- torch.distributed.pipelining.stage
- torch.distributed.remote_device
- torch.distributed.rendezvous
- torch.distributed.rpc
- torch.distributed.rpc.api
- torch.distributed.rpc.backend_registry
- torch.distributed.rpc.constants
- torch.distributed.rpc.functions
- torch.distributed.rpc.internal
- torch.distributed.rpc.options
- torch.distributed.rpc.rref_proxy
- torch.distributed.rpc.server_process_global_profiler
- torch.distributed.run
- torch.distributed.tensor
- torch.distributed.tensor.parallel
- torch.distributed.tensor.parallel.api
- torch.distributed.tensor.parallel.ddp
- torch.distributed.tensor.parallel.fsdp
- torch.distributed.tensor.parallel.input_reshard
- torch.distributed.tensor.parallel.loss
- torch.distributed.tensor.parallel.style
- torch.distributed.utils
- torch.distributions
- 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.inverse_gamma
- torch.distributions.kl
- torch.distributions.kumaraswamy
- torch.distributions.laplace
- torch.distributions.lkj_cholesky
- torch.distributions.log_normal
- torch.distributions.logistic_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.utils
- torch.distributions.von_mises
- torch.distributions.weibull
- torch.distributions.wishart
- torch.export
- torch.export.custom_obj
- torch.export.dynamic_shapes
- torch.export.exported_program
- torch.export.graph_signature
|
- torch.export.unflatten
- torch.fft
- torch.finfo (torch 中的类)
- torch.func
- torch.functional
- torch.futures
- torch.fx
- torch.fx.annotate
- torch.fx.config
- torch.fx.experimental
- torch.fx.experimental.accelerator_partitioner
- torch.fx.experimental.const_fold
- torch.fx.experimental.debug
- torch.fx.experimental.graph_gradual_typechecker
- torch.fx.experimental.merge_matmul
- torch.fx.experimental.meta_tracer
- torch.fx.experimental.migrate_gradual_types
- torch.fx.experimental.migrate_gradual_types.constraint
- torch.fx.experimental.migrate_gradual_types.constraint_generator
- torch.fx.experimental.migrate_gradual_types.constraint_transformation
- torch.fx.experimental.migrate_gradual_types.operation
- torch.fx.experimental.migrate_gradual_types.transform_to_z3
- torch.fx.experimental.migrate_gradual_types.util
- torch.fx.experimental.migrate_gradual_types.z3_types
- torch.fx.experimental.normalize
- torch.fx.experimental.optimization
- torch.fx.experimental.partitioner_utils
- torch.fx.experimental.proxy_tensor
- torch.fx.experimental.recording
- torch.fx.experimental.refinement_types
- torch.fx.experimental.rewriter
- torch.fx.experimental.schema_type_annotation
- torch.fx.experimental.sym_node
- torch.fx.experimental.symbolic_shapes
- torch.fx.experimental.unification
- torch.fx.experimental.unification.core
- torch.fx.experimental.unification.dispatch
- torch.fx.experimental.unification.match
- torch.fx.experimental.unification.more
- torch.fx.experimental.unification.multipledispatch
- torch.fx.experimental.unification.multipledispatch.conflict
- torch.fx.experimental.unification.multipledispatch.core
- torch.fx.experimental.unification.multipledispatch.dispatcher
- torch.fx.experimental.unification.multipledispatch.utils
- torch.fx.experimental.unification.multipledispatch.variadic
- torch.fx.experimental.unification.unification_tools
- torch.fx.experimental.unification.utils
- torch.fx.experimental.unification.variable
- torch.fx.experimental.unify_refinements
- torch.fx.experimental.validator
- torch.fx.graph
- torch.fx.graph_module
- torch.fx.immutable_collections
- torch.fx.interpreter
- torch.fx.node
- torch.fx.operator_schemas
- torch.fx.passes
- torch.fx.passes.annotate_getitem_nodes
- torch.fx.passes.backends
- torch.fx.passes.backends.cudagraphs
- torch.fx.passes.dialect
- torch.fx.passes.dialect.common
- torch.fx.passes.dialect.common.cse_pass
- torch.fx.passes.fake_tensor_prop
- torch.fx.passes.graph_drawer
- torch.fx.passes.graph_manipulation
- torch.fx.passes.graph_transform_observer
- torch.fx.passes.infra
- torch.fx.passes.infra.partitioner
- torch.fx.passes.infra.pass_base
- torch.fx.passes.infra.pass_manager
- torch.fx.passes.net_min_base
- torch.fx.passes.operator_support
- torch.fx.passes.param_fetch
- torch.fx.passes.pass_manager
- torch.fx.passes.reinplace
- torch.fx.passes.runtime_assert
- torch.fx.passes.shape_prop
- torch.fx.passes.split_module
- torch.fx.passes.split_utils
- torch.fx.passes.splitter_base
- torch.fx.passes.tests
- torch.fx.passes.tests.test_pass_manager
- torch.fx.passes.tools_common
- torch.fx.passes.utils
- torch.fx.passes.utils.common
- torch.fx.passes.utils.fuser_utils
- torch.fx.passes.utils.matcher_utils
- torch.fx.passes.utils.matcher_with_name_node_map_utils
- torch.fx.passes.utils.source_matcher_utils
- torch.fx.proxy
- torch.fx.subgraph_rewriter
- torch.fx.tensor_type
- torch.fx.traceback
- torch.hub
- torch.iinfo (torch 中的类)
- torch.jit
- torch.jit.annotations
- torch.jit.frontend
- torch.jit.generate_bytecode
- torch.jit.mobile
- torch.jit.quantized
- torch.jit.supported_ops
- torch.jit.unsupported_tensor_ops
- torch.library
- torch.linalg
- torch.masked
- torch.masked.maskedtensor
- torch.masked.maskedtensor.binary
- torch.masked.maskedtensor.core
- torch.masked.maskedtensor.creation
- torch.masked.maskedtensor.passthrough
- torch.masked.maskedtensor.reductions
- torch.masked.maskedtensor.unary
- torch.monitor
- torch.mps
- torch.mps.event
- torch.mps.profiler
- torch.mtia
- torch.multiprocessing
- torch.multiprocessing.pool
- torch.multiprocessing.queue
- torch.multiprocessing.reductions
- torch.multiprocessing.spawn
- torch.nested
- torch.nn
- torch.nn.attention
- torch.nn.attention.bias
- torch.nn.backends
- torch.nn.backends.thnn
- torch.nn.common_types
- torch.nn.cpp
- torch.nn.functional
- torch.nn.grad
- torch.nn.init
- torch.nn.intrinsic
- torch.nn.intrinsic.modules
- torch.nn.intrinsic.modules.fused
- torch.nn.intrinsic.qat
- torch.nn.intrinsic.qat.modules
- torch.nn.intrinsic.qat.modules.conv_fused
- torch.nn.intrinsic.qat.modules.linear_fused
- torch.nn.intrinsic.qat.modules.linear_relu
- torch.nn.intrinsic.quantized
- torch.nn.intrinsic.quantized.dynamic
- torch.nn.intrinsic.quantized.dynamic.modules
- torch.nn.intrinsic.quantized.dynamic.modules.linear_relu
- torch.nn.intrinsic.quantized.modules
- torch.nn.intrinsic.quantized.modules.bn_relu
- torch.nn.intrinsic.quantized.modules.conv_relu
- torch.nn.intrinsic.quantized.modules.linear_relu
- torch.nn.modules
- 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.modules.utils
- torch.nn.parallel
- torch.nn.parallel.comm
- torch.nn.parallel.distributed
- torch.nn.parallel.parallel_apply
- torch.nn.parallel.replicate
- torch.nn.parallel.scatter_gather
- torch.nn.parameter
- torch.nn.qat
- torch.nn.qat.dynamic
- torch.nn.qat.dynamic.modules
- torch.nn.qat.dynamic.modules.linear
- torch.nn.qat.modules
- torch.nn.qat.modules.conv
- torch.nn.qat.modules.embedding_ops
- torch.nn.qat.modules.linear
- torch.nn.quantizable
- torch.nn.quantizable.modules
- torch.nn.quantizable.modules.activation
- torch.nn.quantizable.modules.rnn
- torch.nn.quantized
- torch.nn.quantized.dynamic
- torch.nn.quantized.dynamic.modules
- torch.nn.quantized.dynamic.modules.conv
- 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.dropout
- torch.nn.quantized.modules.embedding_ops
- torch.nn.quantized.modules.functional_modules
- torch.nn.quantized.modules.linear
- torch.nn.quantized.modules.normalization
- torch.nn.quantized.modules.rnn
- torch.nn.quantized.modules.utils
- torch.nn.utils
- torch.nn.utils.clip_grad
- torch.nn.utils.convert_parameters
- torch.nn.utils.fusion
- torch.nn.utils.init
- torch.nn.utils.memory_format
- torch.nn.utils.parametrizations
- torch.nn.utils.parametrize
- torch.nn.utils.prune
- torch.nn.utils.rnn
- torch.nn.utils.stateless
- torch.onnx
- torch.onnx.errors
- torch.onnx.operators
- torch.onnx.symbolic_caffe2
- torch.onnx.symbolic_helper
- torch.onnx.symbolic_opset10
- torch.onnx.symbolic_opset11
- torch.onnx.symbolic_opset12
- torch.onnx.symbolic_opset13
- torch.onnx.symbolic_opset14
- torch.onnx.symbolic_opset15
- torch.onnx.symbolic_opset16
- torch.onnx.symbolic_opset17
- torch.onnx.symbolic_opset18
- torch.onnx.symbolic_opset19
- torch.onnx.symbolic_opset20
- torch.onnx.symbolic_opset7
- torch.onnx.symbolic_opset8
- torch.onnx.symbolic_opset9
- torch.onnx.utils
- torch.onnx.verification
- torch.optim
- 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.nadam
- torch.optim.optimizer
- torch.optim.radam
- torch.optim.rmsprop
- torch.optim.rprop
- torch.optim.sgd
- torch.optim.sparse_adam
- torch.optim.swa_utils
- torch.overrides
- torch.package
- torch.package.analyze
- torch.package.analyze.find_first_use_of_broken_modules
- torch.package.analyze.is_from_package
- torch.package.analyze.trace_dependencies
- torch.package.file_structure_representation
- torch.package.find_file_dependencies
- torch.package.glob_group
- torch.package.importer
- torch.package.package_exporter
- torch.package.package_importer
- torch.profiler
- torch.profiler.itt
- torch.profiler.profiler
- torch.profiler.python_tracer
- torch.quantization
- torch.quantization.fake_quantize
- torch.quantization.fuse_modules
- torch.quantization.fuser_method_mappings
- torch.quantization.fx
- torch.quantization.fx.convert
- torch.quantization.fx.fuse
- torch.quantization.fx.fusion_patterns
- torch.quantization.fx.graph_module
- torch.quantization.fx.match_utils
- torch.quantization.fx.pattern_utils
- torch.quantization.fx.prepare
- torch.quantization.fx.quantization_patterns
- torch.quantization.fx.quantization_types
- torch.quantization.fx.utils
- torch.quantization.observer
- torch.quantization.qconfig
- torch.quantization.quant_type
- torch.quantization.quantization_mappings
- torch.quantization.quantize
- torch.quantization.quantize_fx
- torch.quantization.quantize_jit
- torch.quantization.stubs
- torch.quantization.utils
- torch.quasirandom
- torch.random
- torch.return_types
- torch.serialization
- torch.signal
- torch.signal.windows
- torch.signal.windows.windows
- torch.sparse
- torch.sparse.semi_structured
- torch.special
- torch.storage
- torch.testing
- torch.torch_version
- torch.types
- torch.utils
- torch.utils.backcompat
- torch.utils.backend_registration
- torch.utils.benchmark
- torch.utils.benchmark.examples
- torch.utils.benchmark.examples.blas_compare_setup
- torch.utils.benchmark.examples.compare
- torch.utils.benchmark.examples.fuzzer
- torch.utils.benchmark.examples.op_benchmark
- torch.utils.benchmark.examples.simple_timeit
- torch.utils.benchmark.examples.spectral_ops_fuzz_test
- torch.utils.benchmark.op_fuzzers
- torch.utils.benchmark.op_fuzzers.binary
- torch.utils.benchmark.op_fuzzers.sparse_binary
- torch.utils.benchmark.op_fuzzers.sparse_unary
- torch.utils.benchmark.op_fuzzers.spectral
- torch.utils.benchmark.op_fuzzers.unary
- torch.utils.benchmark.utils
- torch.utils.benchmark.utils.common
- torch.utils.benchmark.utils.compare
- torch.utils.benchmark.utils.compile
- torch.utils.benchmark.utils.cpp_jit
- torch.utils.benchmark.utils.fuzzer
- torch.utils.benchmark.utils.sparse_fuzzer
- torch.utils.benchmark.utils.timer
- torch.utils.benchmark.utils.valgrind_wrapper
- torch.utils.benchmark.utils.valgrind_wrapper.timer_interface
- torch.utils.bottleneck
- torch.utils.bundled_inputs
- torch.utils.checkpoint
- torch.utils.collect_env
- torch.utils.cpp_backtrace
- torch.utils.cpp_extension
- torch.utils.data
- torch.utils.data.backward_compatibility
- torch.utils.data.dataloader
- torch.utils.data.datapipes
- torch.utils.data.datapipes.dataframe
- torch.utils.data.datapipes.dataframe.dataframe_wrapper
- torch.utils.data.datapipes.dataframe.dataframes
- torch.utils.data.datapipes.dataframe.datapipes
- torch.utils.data.datapipes.dataframe.structures
- torch.utils.data.datapipes.datapipe
- torch.utils.data.datapipes.gen_pyi
- torch.utils.data.datapipes.iter
- torch.utils.data.datapipes.iter.callable
- torch.utils.data.datapipes.iter.combinatorics
- torch.utils.data.datapipes.iter.combining
- torch.utils.data.datapipes.iter.filelister
- torch.utils.data.datapipes.iter.fileopener
- torch.utils.data.datapipes.iter.grouping
- torch.utils.data.datapipes.iter.routeddecoder
- torch.utils.data.datapipes.iter.selecting
- torch.utils.data.datapipes.iter.sharding
- torch.utils.data.datapipes.iter.streamreader
- torch.utils.data.datapipes.iter.utils
- torch.utils.data.datapipes.map
- torch.utils.data.datapipes.map.callable
- torch.utils.data.datapipes.map.combinatorics
- torch.utils.data.datapipes.map.combining
- torch.utils.data.datapipes.map.grouping
- torch.utils.data.datapipes.map.utils
- torch.utils.data.datapipes.utils
- torch.utils.data.datapipes.utils.common
- torch.utils.data.datapipes.utils.decoder
- torch.utils.data.datapipes.utils.snapshot
- torch.utils.data.dataset
- torch.utils.data.distributed
- torch.utils.data.graph
- torch.utils.data.graph_settings
- torch.utils.data.sampler
- torch.utils.deterministic
- torch.utils.dlpack
- torch.utils.file_baton
- torch.utils.flop_counter
- torch.utils.hipify
- torch.utils.hipify.constants
- torch.utils.hipify.cuda_to_hip_mappings
- torch.utils.hipify.hipify_python
- torch.utils.hipify.version
- torch.utils.hooks
- torch.utils.jit
- torch.utils.jit.log_extract
- torch.utils.mkldnn
- torch.utils.mobile_optimizer
- torch.utils.model_dump
- torch.utils.model_zoo
- torch.utils.module_tracker
- torch.utils.show_pickle
- torch.utils.tensorboard
- torch.utils.tensorboard.summary
- torch.utils.tensorboard.writer
- torch.utils.throughput_benchmark
- torch.utils.viz
- torch.utils.weak
- torch.version
- torch.xpu
- torch.xpu.random
- torch.xpu.streams
- torch_name() (torch.onnx.JitScalarType 方法)
- torch_save_to_dcp() (位于 torch.distributed.checkpoint.format_utils 模块中)
- total_average() (torch.autograd.profiler.profile 方法)
- total_count (torch.distributions.multinomial.Multinomial 属性)
- trace() (位于 torch 模块中)
- trace_module() (位于 torch.jit 模块中)
- Tracer (torch.fx 中的类)
- train() (torch.jit.ScriptModule 方法)
- Transform (torch.distributions.transforms 中的类)
- transform() (torch.fx.Transformer 方法)
- transform_object() (torch.distributed.checkpoint.DefaultSavePlanner 方法)
- transform_tensor() (torch.distributed.checkpoint.DefaultLoadPlanner 方法)
- TransformedDistribution (torch.distributions.transformed_distribution 中的类)
- Transformer (torch.fx 中的类)
- TransformerDecoder (torch.nn 中的类)
- TransformerDecoderLayer (torch.nn 中的类)
- TransformerEncoder (torch.nn 中的类)
- TransformerEncoderLayer (torch.nn 中的类)
- transpose() (位于 torch 模块中)
- transpose_() (torch.Tensor 方法)
- trapezoid() (位于 torch 模块中)
- trapz() (位于 torch 模块中)
- triangular_solve() (位于 torch 模块中)
- tril() (位于 torch 模块中)
- tril_() (torch.Tensor 方法)
- tril_indices() (位于 torch 模块中)
- trim_significant_figures() (torch.utils.benchmark.Compare 方法)
- triplet_margin_loss() (位于 torch.nn.functional 模块中)
- triplet_margin_with_distance_loss() (位于 torch.nn.functional 模块中)
- TripletMarginLoss (torch.nn 中的类)
- TripletMarginWithDistanceLoss (torch.nn 中的类)
- triu() (位于 torch 模块中)
- triu_() (torch.Tensor 方法)
- triu_indices() (位于 torch 模块中)
- true_divide() (位于 torch 模块中)
- true_divide_() (torch.Tensor 方法)
- trunc() (位于 torch 模块中)
- trunc_() (torch.Tensor 方法)
- trunc_normal_() (位于 torch.nn.init 模块中)
- tuning_enable() (位于 torch.cuda.tunable 模块中)
- tuning_is_enabled() (位于 torch.cuda.tunable 模块中)
- type (torch.jit.Attribute 属性)
- type() (torch.jit.ScriptModule 方法)
- type_as() (torch.Tensor 方法)
- TypedStorage (torch 中的类)
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