Python Module Index

t


	t
	`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.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.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`

Python Module Index

Docs

Tutorials

Resources