Caffe2 - Python API
A deep learning, cross platform ML framework
Class Index
A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | Y | Z | _
  A  
DropoutCell (caffe2.python.rnn_cell)   MarginRankingLoss (torch.nn.modules.loss)   RNNBase (torch.nn.modules.rnn)   TextFileReader (caffe2.python.text_file_reader)   
DropoutDescriptor (torch.backends.cudnn)   MarginRankLoss (caffe2.python.layers.margin_rank_loss)   RNNCell (torch.nn.modules.rnn)   THNNBackendBase (torch._thnn.utils)   
AbsTransform (torch.distributions.transforms)   
  E  
Markdown (caffe2.python.docs.formatter)   RNNCell (caffe2.python.rnn_cell)   THNNCudaBackendStateMixin (torch._thnn)   
Adadelta (torch.optim.adadelta)   MaxNorm (caffe2.python.regularizer)   RNNCellBase (torch.nn.modules.rnn)   THNNFunctionBackend (torch.nn.backends.thnn)   
AdadeltaOptimizer (caffe2.python.optimizer)   EditHistory (expecttest)   MaxPool1d (torch.nn.modules.pooling)   RNNDescriptor (torch.backends.cudnn)   Threshold (torch.nn.modules.activation)   
Adagrad (torch.optim.adagrad)   ELU (torch.nn.modules.activation)   MaxPool2d (torch.nn.modules.pooling)   RNNModel (model_defs.word_language_model)   TopLevelTracedModule (torch.jit)   
AdagradOptimizer (caffe2.python.optimizer)   Embedding (torch.nn.modules.sparse)   MaxPool3d (torch.nn.modules.pooling)   RnnModelWithPackedSequence (model_defs.rnn_model_with_packed_sequence)   TracedModule (torch.jit)   
Adam (torch.optim.adam)   EmbeddingBag (torch.nn._functions.thnn.sparse)   MaxUnpool1d (torch.nn.modules.pooling)   Rprop (torch.optim.rprop)   TracerWarning (torch.jit)   
Adamax (torch.optim.adamax)   EmbeddingBag (torch.nn.modules.sparse)   MaxUnpool2d (torch.nn.modules.pooling)   RReLU (torch.nn.modules.activation)   TracingCheckError (torch.jit)   
AdamOptimizer (caffe2.python.optimizer)   EnforceUnique (torch.autograd.profiler)   MaxUnpool3d (torch.nn.modules.pooling)   
  S  
Transform (torch.distributions.transforms)   
AdaptiveAvgPool1d (torch.nn.modules.pooling)   ErrorDataset (test_dataloader)   MergeIdLists (caffe2.python.layers.merge_id_lists)   TransformedDistribution (torch.distributions.transformed_distribution)   
AdaptiveAvgPool2d (torch.nn.modules.pooling)   Errors (verify)   Metadata (caffe2.python.schema)   Sampler (torch.utils.data.sampler)   Transformer (caffe2.python.transformations)   
AdaptiveAvgPool3d (torch.nn.modules.pooling)   ErrorTrackingProcess (test_dataloader)   Metrics (caffe2.python.parallel_workers)   SamplingTrain (caffe2.python.layers.sampling_train)   TranslatorRegistry (caffe2.python.caffe_translator)   
AdaptiveLogSoftmaxWithLoss (torch.nn.modules.adaptive)   Event (torch.cuda.streams)   MILSTMCell (caffe2.python.rnn_cell)   SamplingTrainableMixin (caffe2.python.layers.sampling_trainable_mixin)   Trie (caffe2.python.binarysize)   
AdaptiveMaxPool1d (torch.nn.modules.pooling)   EventList (torch.autograd.profiler)   MILSTMWithAttentionCell (caffe2.python.rnn_cell)   Scalar (caffe2.python.schema)   Trie (pyHIPIFY.hipify_python)   
AdaptiveMaxPool2d (torch.nn.modules.pooling)   ExceptionWrapper (torch.utils.data._utils)   MNIST (model_defs.mnist)   Scatter (torch.nn.parallel._functions)   TripletMarginLoss (torch.nn.modules.loss)   
AdaptiveMaxPool3d (torch.nn.modules.pooling)   ExecutionStep (caffe2.python.core)   MnistNet (test_jit)   SchedulerTestNet (test_optim)   TupleCls (torch._jit_internal)   
AdaptiveWeight (caffe2.python.layers.adaptive_weight)   ExecutorTestBase (caffe2.python.test.executor_test_util)   Model (test_cuda)   ScriptMeta (torch.jit)   TupleInstance (torch._jit_internal)   
AddBias (caffe2.python.layers.add_bias)   Exponential (torch.distributions.exponential)   Model (model)   ScriptModule (torch.jit)   Type (torch.autograd._functions.tensor)   
AffineTransform (torch.distributions.transforms)   ExponentialFamily (torch.distributions.exp_family)   ModelDownloader (caffe2.python.models.download)   SeedDataset (test_dataloader)   
  U  
AlphaDropout (torch.nn.modules.dropout)   ExponentialLR (torch.optim.lr_scheduler)   ModelHelper (caffe2.python.model_helper)   SegfaultDataset (test_dataloader)   
Analyzer (caffe2.python.net_printer)   ExportTypes (torch.onnx)   ModelLayer (caffe2.python.layers.layers)   SelectRecordByContext (caffe2.python.layers.select_record_by_context)   UndefinedArguments (tools.cwrap.plugins.NullableArguments)   
ArcCosineFeatureMap (caffe2.python.layers.arc_cosine_feature_map)   ExprBuilder (torch.jit.frontend)   ModelTrainerLog (caffe2.python.experiment_util)   SELU (torch.nn.modules.activation)   Unfold (torch.nn.modules.fold)   
ArgcountChecker (tools.cwrap.plugins.ArgcountChecker)   ExpRelaxedCategorical (torch.distributions.relaxed_categorical)   ModifierContext (caffe2.python.modifier_context)   SemiRandomFeatures (caffe2.python.layers.semi_random_features)   Uniform (torch.distributions.uniform)   
Argument (common_with_cwrap)   ExpTransform (torch.distributions.transforms)   Module (torch.nn.modules.module)   Seq2SeqModelCaffe2 (caffe2.python.models.seq2seq.train)   UniformSampling (caffe2.python.layers.uniform_sampling)   
Argument (torch._thnn.utils)   ExtensionVersioner (torch.utils._cpp_extension_versioner)   Module (torch.jit.annotations)   Seq2SeqModelCaffe2EnsembleDecoder (caffe2.python.models.seq2seq.translate)   UnpoolingNet (test_nn)   
ArgumentReferences (tools.cwrap.plugins.ArgumentReferences)   ExternalInitializer (caffe2.python.modeling.initializers)   ModuleDict (torch.nn.modules.container)   Seq2SeqModelCaffe2EnsembleDecoderBase (caffe2.python.models.seq2seq.translate)   UnrolledCell (caffe2.python.rnn_cell)   
ASGD (torch.optim.asgd)   ExternalLogger (caffe2.python.experiment_util)   ModuleList (torch.nn.modules.container)   Seq2SeqModelHelper (caffe2.python.models.seq2seq.seq2seq_model_helper)   Unserializable (torch.backends.cudnn.rnn)   
AssignmentAlgorithm (caffe2.python.memonger)   
  F  
ModuleTest (common_nn)   Sequential (torch.nn.modules.container)   Unsupported (caffe2.python.onnx.error)   
AttentionCell (caffe2.python.rnn_cell)   ModuleWrapper (torch.nn.cpp)   SequentialSampler (torch.utils.data.sampler)   UnsupportedNodeError (torch.jit.frontend)   
AttentionType (caffe2.python.attention)   FC (caffe2.python.layers.fc)   MSELoss (torch.nn.modules.loss)   SerializedTestCase (caffe2.python.serialized_test.serialized_test_util)   UploadTaskGroupBuilder (caffe2.python.checkpoint)   
AutoGPU (tools.cwrap.plugins.AutoGPU)   FCWithoutBias (caffe2.python.layers.fc_without_bias)   MultiLabelMarginLoss (torch.nn.modules.loss)   Session (caffe2.python.session)   Upsample (torch.nn.modules.upsampling)   
AvgPool1d (torch.nn.modules.pooling)   FeatureAlphaDropout (torch.nn.modules.dropout)   MultiLabelSoftMarginLoss (torch.nn.modules.loss)   SetupNets (caffe2.python.task)   UpsamplingBilinear2d (torch.nn.modules.upsampling)   
AvgPool2d (torch.nn.modules.pooling)   FeatureSparseToDense (caffe2.python.layers.feature_sparse_to_dense)   MultiMarginLoss (torch.nn.modules.loss)   SGD (torch.optim.sgd)   UpsamplingNearest2d (torch.nn.modules.upsampling)   
AvgPool3d (torch.nn.modules.pooling)   Field (caffe2.python.schema)   MultiNodeCheckpointManager (caffe2.python.checkpoint)   SgdOptimizer (caffe2.python.optimizer)   UpscaleBlock (model_defs.srresnet)   
  B  
FileBaton (torch.utils.file_baton)   Multinomial (torch.distributions.multinomial)   SharedCache (torch.multiprocessing.reductions)   UseModifierBase (caffe2.python.modifier_context)   
FilelikeMock (test_torch)   MultiPrecisionSgdOptimizer (caffe2.python.optimizer)   ShortStorage (torch)   UseNormalizer (caffe2.python.normalizer_context)   
Backend (torch.distributed.distributed_c10d)   FileManager (gen)   MultiProcessTestCase (test_c10d)   ShortStorage (torch.cuda)   UseOptimizer (caffe2.python.optimizer_context)   
Backend (torch._thnn)   FileStoreTest (test_c10d)   MultiRNNCell (caffe2.python.rnn_cell)   ShortStorage (torch.distributed.deprecated.remote_types)   UseRegularizer (caffe2.python.regularizer_context)   
Backends (torch._thnn)   FilterDescriptor (torch.backends.cudnn)   MultiRNNCellInitializer (caffe2.python.rnn_cell)   Sigmoid (torch.nn.modules.activation)   
  V  
BackwardCFunction (torch.autograd.function)   Fire (model_defs.squeezenet)   MultiStepLR (torch.optim.lr_scheduler)   SigmoidTransform (torch.distributions.transforms)   
Barrier (test_distributed)   FisherSnedecor (torch.distributions.fishersnedecor)   MultivariateNormal (torch.distributions.multivariate_normal)   SimpleCustomBatch (test_dataloader)   Variable (torch.autograd.variable)   
Barrier (test_thd_distributed)   FloatStorage (torch.cuda)   TestPytorchExportModes.MyModel (test_jit)   SimpleQueue (torch.multiprocessing.queue)   VariableMeta (torch.autograd.variable)   
BaseException (caffe2.python.onnx.error)   FloatStorage (torch.distributed.deprecated.remote_types)   
  N  
SleepDataset (test_dataloader)   VFModule (torch.nn._VF)   
BasicRNNCell (caffe2.python.rnn_cell)   FloatStorage (torch)   SmoothL1Loss (torch.nn.modules.loss)   Visitor (caffe2.python.net_printer)   
BatchDistillLRLoss (caffe2.python.layers.batch_distill_lr_loss)   Fold (torch.nn.modules.fold)   NamedTupleDataset (test_dataloader)   SoftMarginLoss (torch.nn.modules.loss)   
  W  
BatchFeeder (caffe2.python.data_workers)   FooToPickle (test_jit)   NCHW (caffe2.python.visualize)   Softmax (torch.nn.modules.activation)   
BatchLRLoss (caffe2.python.layers.batch_lr_loss)   FormattedTimesMixin (torch.autograd.profiler)   NegativeBinomial (torch.distributions.negative_binomial)   Softmax2d (torch.nn.modules.activation)   Warning (torch.utils.backcompat)   
BatchMSELoss (caffe2.python.layers.batch_mse_loss)   Formatter (caffe2.python.docs.formatter)   NestedIOFunction (torch.autograd.function)   SoftmaxTransform (torch.distributions.transforms)   WatcherThread (caffe2.python.timeout_guard)   
BatchNorm1d (torch.nn.modules.batchnorm)   FP16SgdOptimizer (caffe2.python.optimizer)   Net (network1)   SoftMaxWithLoss (caffe2.experiments.python.device_reduce_sum_bench)   WeakScriptModuleProxy (torch.jit)   
BatchNorm2d (torch.nn.modules.batchnorm)   FractionalMaxPool2d (torch.nn.modules.pooling)   Net (network2)   Softmin (torch.nn.modules.activation)   Weibull (torch.distributions.weibull)   
BatchNorm3d (torch.nn.modules.batchnorm)   FractionalMaxPool3d (torch.nn.modules.pooling)   Net (test_c10d)   Softplus (torch.nn.modules.activation)   WeightDecayBuilder (caffe2.python.optimizer)   
BatchNormalization (caffe2.python.layers.batch_normalization)   FrontendError (torch.jit.frontend)   Net (test_distributed)   Softshrink (torch.nn.modules.activation)   WeightedRandomSampler (torch.utils.data.sampler)   
BatchNormalizer (caffe2.python.normalizer)   FrontendTypeError (torch.jit.frontend)   Net (test_thd_distributed)   Softsign (torch.nn.modules.activation)   WeightNorm (torch.nn.utils.weight_norm)   
BatchNormNet (test_distributed)   FtrlOptimizer (caffe2.python.optimizer)   Net (caffe2.python.core)   SomeClass (update-caffe2-models)   WngradOptimizer (caffe2.python.optimizer)   
BatchSampler (torch.utils.data.sampler)   FuncModule (test_operators)   NetBuilder (caffe2.python.net_builder)   SourceChangeWarning (torch.serialization)   Worker (caffe2.python.parallel_workers)   
BatchSigmoidCrossEntropyLoss (caffe2.python.layers.batch_sigmoid_cross_entropy_loss)   Function (common_with_cwrap)   NetDefNode (caffe2.experiments.python.SparseTransformer)   SourceContext (torch.jit.frontend)   WorkerCoordinator (caffe2.python.parallel_workers)   
BatchSoftmaxLoss (caffe2.python.layers.batch_softmax_loss)   Function (torch._thnn.utils)   NetGradientChecker (caffe2.python.gradient_checker)   SparseAdam (torch.optim.sparse_adam)   Workspace (caffe2.python.onnx.workspace)   
BCELoss (torch.nn.modules.loss)   Function (torch.autograd.function)   NetModifier (caffe2.python.modeling.net_modifier)   SparseFeatureHash (caffe2.python.layers.sparse_feature_hash)   WorkspaceType (caffe2.python.task)   
BCEWithLogitsLoss (torch.nn.modules.loss)   Functional (caffe2.python.layers.functional)   NetProcessor (caffe2.python.pipeline)   SparseLookup (caffe2.python.layers.sparse_lookup)   WrapDim (tools.cwrap.plugins.WrapDim)   
BeamSearchForwardOnly (caffe2.python.models.seq2seq.beam_search)   FunctionBackend (torch.nn.backends.backend)   NewCriterionTest (test_nn)   SpawnContext (torch.multiprocessing.spawn)   Writer (caffe2.python.dataio)   
BeforeAfterCall (tools.cwrap.plugins.BeforeAfterCall)   FunctionEvent (torch.autograd.profiler)   NewModuleTest (test_nn)   SpawnTest (test_multiprocessing_spawn)   
  Y  
Benchmark (caffe2.experiments.python.device_reduce_sum_bench)   FunctionEventAvg (torch.autograd.profiler)   NHWC (caffe2.python.visualize)   SpectralNorm (torch.nn.utils.spectral_norm)   
BenchmarkMeta (caffe2.experiments.python.device_reduce_sum_bench)   FunctionMeta (torch.autograd.function)   NLLLoss (torch.nn.modules.loss)   SpectralNormLoadStateDictPreHook (torch.nn.utils.spectral_norm)   YellowFinOptimizer (caffe2.python.optimizer)   
Bernoulli (torch.distributions.bernoulli)   
  G  
NLLLoss2d (torch.nn.modules.loss)   SpectralNormStateDictHook (torch.nn.utils.spectral_norm)   
  Z  
Beta (torch.distributions.beta)   NNExtension (tools.cwrap.plugins.NNExtension)   Split (caffe2.python.layers.split)   
Bilinear (torch.nn.modules.linear)   Gamma (torch.distributions.gamma)   NNModule (caffe2.python.nomnigraph)   SqueezeNet (model_defs.squeezenet)   ZeroPad2d (torch.nn.modules.padding)   
Binomial (torch.distributions.binomial)   Gather (torch.nn.parallel._functions)   NNTestCase (common_nn)   SRResNet (model_defs.srresnet)   
  _  
BlobReference (caffe2.python.core)   GatherRecord (caffe2.python.layers.gather_record)   NoArgsClass (common_methods_invocations)   TestScript.StarTestReturnThree (test_jit)   
BlobWeightedSum (caffe2.python.layers.blob_weighted_sum)   Geometric (torch.distributions.geometric)   Node (caffe2.python.task)   TestScript.StarTestSumAndReturnThree (test_jit)   __PrinterOptions (torch._tensor_str)   
BoolStorage (torch.cuda)   GetEntryFromBlobs (caffe2.python.modeling.get_entry_from_blobs)   Normal (torch.distributions.normal)   TestScript.StarTestSumStarred (test_jit)   _AdaptiveAvgPoolNd (torch.nn.modules.pooling)   
BoolStorage (torch)   GFtrlOptimizer (caffe2.python.optimizer)   Normalizer (caffe2.python.normalizer)   State (caffe2.python.parallel_workers)   _AdaptiveLogSoftmaxWithLoss (test_nn)   
BoundedGradientProjection (caffe2.python.regularizer)   GHMarkdown (caffe2.python.docs.github)   NormalizerContext (caffe2.python.normalizer_context)   StepLR (torch.optim.lr_scheduler)   _AdaptiveMaxPoolNd (torch.nn.modules.pooling)   
Broadcast (torch.nn.parallel._functions)   GHOpDocGenerator (caffe2.python.docs.github)   NotSupportedError (torch.jit.frontend)   StickBreakingTransform (torch.distributions.transforms)   _AvgPoolNd (torch.nn.modules.pooling)   
BroadcastingListCls (torch._jit_internal)   GHOpDocUploader (caffe2.python.docs.github)   NullableArguments (tools.cwrap.plugins.NullableArguments)   StmtBuilder (torch.jit.frontend)   _BatchNorm (torch.nn.modules.batchnorm)   
BucketWeighted (caffe2.python.layers.bucket_weighted)   GHOperatorDoc (caffe2.python.docs.github)   NumpyTests (test_indexing)   StorageWeakRef (torch.multiprocessing.reductions)   _BlobDict (caffe2.python.workspace)   
Builder (torch.jit.frontend)   GHOperatorEngine (caffe2.python.docs.github)   NYIError (function_wrapper)   StoreOpsTests (caffe2.distributed.store_ops_test_util)   _Boolean (torch.distributions.constraints)   
BuildExtension (torch.utils.cpp_extension)   GILRelease (tools.cwrap.plugins.GILRelease)   
  O  
StoreTestBase (test_c10d)   _ConstantPadNd (torch.nn.modules.padding)   
BytesIOContext (test_torch)   GlobalCoordinator (caffe2.python.data_workers)   Stream (torch.cuda.streams)   _ConstModuleList (torch.jit)   
ByteStorage (torch.cuda)   GlobalWorkerCoordinator (caffe2.python.parallel_workers)   OneHotCategorical (torch.distributions.one_hot_categorical)   StringDataset (test_dataloader)   _ConstSequential (torch.jit)   
ByteStorage (torch.distributed.deprecated.remote_types)   GLU (torch.nn.modules.activation)   OnnxAttributes (caffe2.python.onnx.backend)   StringTable (torch.autograd.profiler)   _ContextInfo (caffe2.python.context)   
ByteStorage (torch)   GradientChecker (caffe2.python.gradient_checker)   OnnxifiTest (caffe2.python.onnx.test_onnxifi)   Struct (caffe2.python.schema)   _ContextMethodMixin (torch.autograd.function)   
  C  
GradientClipping (caffe2.python.modeling.gradient_clipping)   OnnxifiTransformTest (caffe2.python.onnx.test_onnxifi)   StudentT (torch.distributions.studentT)   _ContextRegistry (caffe2.python.context)   
GradientRegistry (caffe2.python.core)   OnnxNode (caffe2.python.onnx.backend)   SubProcess (test_multiprocessing)   _ConvNd (torch.nn.modules.conv)   
CachedReader (caffe2.python.cached_reader)   GroupL1Norm (caffe2.python.regularizer)   OpDocGenerator (caffe2.python.docs.generator)   Subset (torch.utils.data.dataset)   _ConvTransposeMixin (torch.nn.modules.conv)   
Caffe2Backend (caffe2.python.onnx.backend)   GroupMember (torch.distributed.distributed_c10d)   Operations (caffe2.python.net_builder)   SubsetRandomSampler (torch.utils.data.sampler)   _CudaBase (torch.cuda)   
Caffe2CppRep (caffe2.python.onnx.backend_cpp_rep)   GroupNorm (torch.nn.modules.normalization)   OperatorDoc (caffe2.python.docs.generator)   SumElements (caffe2.experiments.python.device_reduce_sum_bench)   _DataLoaderIter (torch.utils.data.dataloader)   
Caffe2Frontend (caffe2.python.onnx.frontend)   GRU (torch.nn.modules.rnn)   OperatorEngine (caffe2.python.docs.generator)   SumSqrElements (caffe2.experiments.python.device_reduce_sum_bench)   _DatasetRandomReader (caffe2.python.dataset)   
Caffe2Rep (caffe2.python.onnx.backend_rep)   GRUCell (caffe2.python.gru_cell)   OpSpec (caffe2.python.layer_test_util)   SuperResolutionNet (model_defs.super_resolution)   _DatasetReader (caffe2.python.dataset)   
Categorical (torch.distributions.categorical)   GRUCell (torch.nn.modules.rnn)   Optimizer (torch.optim.optimizer)   SyncBatchNorm (torch.nn.modules.batchnorm)   _DatasetWriter (caffe2.python.dataset)   
Cauchy (torch.distributions.cauchy)   Gumbel (torch.distributions.gumbel)   Optimizer (caffe2.python.optimizer)   SyncBatchNorm (torch.nn.modules._functions)   _Dependent (torch.distributions.constraints)   
CELU (torch.nn.modules.activation)   
  H  
OptimizerContext (caffe2.python.optimizer_context)   SynchronizedSeedDataset (test_dataloader)   _DependentProperty (torch.distributions.constraints)   
CharRNN (caffe2.python.examples.char_rnn)   OptimizerTestBase (caffe2.python.optimizer_test_util)   
  T  
_Dirichlet (torch.distributions.dirichlet)   
CharStorage (torch.cuda)   HalfCauchy (torch.distributions.half_cauchy)   OptionalArguments (tools.cwrap.plugins.OptionalArguments)   _disable_tracing (torch.jit)   
CharStorage (torch.distributed.deprecated.remote_types)   HalfNormal (torch.distributions.half_normal)   OrderedBufferDict (torch.jit)   TagContext (caffe2.python.layers.tags)   _DistributedBase (torch.distributed.deprecated.remote_types)   
CharStorage (torch)   HalfStorage (torch.cuda)   OrderedDictWrapper (torch.jit)   Tags (caffe2.python.layers.tags)   _DistributedRequest (torch.distributed.deprecated)   
CheckpointFunction (torch.utils.checkpoint)   HalfStorage (torch.distributed.deprecated.remote_types)   OrderedDictWrapper (torch.nn.cpp)   Tanh (torch.nn.modules.activation)   _DistTestBase (test_distributed)   
CheckpointManager (caffe2.python.checkpoint)   HalfStorage (torch)   OrderedModuleDict (torch.jit)   Tanhshrink (torch.nn.modules.activation)   _DistTestBase (test_thd_distributed)   
Chi2 (torch.distributions.chi2)   Hardshrink (torch.nn.modules.activation)   OrderedParameterDict (torch.jit)   Task (caffe2.python.task)   _DropoutNd (torch.nn.modules.dropout)   
Cluster (caffe2.python.task)   Hardtanh (torch.nn.modules.activation)   Output (caffe2.python.pipeline)   TaskGroup (caffe2.python.task)   _FakeDict (pytorch_helper)   
CNNModelHelper (caffe2.python.cnn)   HelperWrapper (caffe2.python.brew)   
  P  
TaskOutput (caffe2.python.task)   _FC2 (test_distributed)   
CodeTemplate (code_template)   HingeEmbeddingLoss (torch.nn.modules.loss)   TaskOutputList (caffe2.python.task)   _FC2 (test_thd_distributed)   
CollectivesConcurrencyControl (caffe2.python.data_parallel_model)   HomotopyWeight (caffe2.python.layers.homotopy_weight)   PackedSequence (torch.nn.utils.rnn)   TCPStoreTest (test_c10d)   _Formatter (torch._tensor_str)   
CompilationUnit (torch.jit)   HypothesisTestCase (caffe2.python.hypothesis_test_util)   PackedSequenceTest (test_nn)   Tensor (torch.tensor)   _Functional (caffe2.python.functional)   
CompiledRunnable (caffe2.python.session)   
  I  
PairwiseDistance (torch.nn.modules.distance)   TensorDataset (torch.utils.data.dataset)   _GreaterThan (torch.distributions.constraints)   
ComposeTransform (torch.distributions.transforms)   PairwiseSimilarity (caffe2.python.layers.pairwise_similarity)   TensorDescriptor (torch.backends.cudnn)   _GreaterThanEq (torch.distributions.constraints)   
CompositeReader (caffe2.python.dataio)   Independent (torch.distributions.independent)   Parameter (torch.nn.parameter)   TensorDescriptorArray (torch.backends.cudnn)   _HalfOpenInterval (torch.distributions.constraints)   
CompositeReaderBuilder (caffe2.python.dataio)   Initializer (caffe2.python.modeling.initializers)   ParameterDict (torch.nn.modules.container)   TensorRTOpTest (caffe2.python.trt.test_trt)   _HookMixin (torch.autograd.function)   
ComputeHistogramForBlobs (caffe2.python.modeling.compute_histogram_for_blobs)   InplaceFunction (torch.autograd.function)   ParameterInfo (caffe2.python.modeling.parameter_info)   TensorRTTransformTest (caffe2.python.trt.test_trt)   _InstanceNorm (torch.nn.modules.instancenorm)   
ComputeNormForBlobs (caffe2.python.modeling.compute_norm_for_blobs)   InputError (pyHIPIFY.hipify_python)   ParameterList (torch.nn.modules.container)   TestAgainstScipy (test_distributions)   _IntegerGreaterThan (torch.distributions.constraints)   
ComputeStatisticsForBlobs (caffe2.python.modeling.compute_statistics_for_blobs)   InputVariableMixin (test_nn)   ParameterSharingContext (caffe2.python.modeling.parameter_sharing)   TestAutograd (test_autograd)   _IntegerInterval (torch.distributions.constraints)   
Concat (caffe2.python.layers.concat)   InstanceNorm1d (torch.nn.modules.instancenorm)   ParameterTags (caffe2.python.modeling.parameter_info)   TestBase (common_nn)   _IntegerLessThan (torch.distributions.constraints)   
ConcatDataset (torch.utils.data.dataset)   InstanceNorm2d (torch.nn.modules.instancenorm)   Pareto (torch.distributions.pareto)   TestBatched (test_jit)   _Interval (torch.distributions.constraints)   
ConnectionWrapper (torch.multiprocessing.queue)   InstanceNorm3d (torch.nn.modules.instancenorm)   Parser (caffe2.python.docs.parser)   TestBottleneck (test_utils)   _InverseTransform (torch.distributions.transforms)   
ConstantArguments (tools.cwrap.plugins.ConstantArguments)   InstantiationContext (caffe2.python.layers.layers)   PatchVisualizer (caffe2.python.visualize)   TestCaffe2Backend (test_pytorch_helper)   _LessThan (torch.distributions.constraints)   
ConstantNorm (caffe2.python.regularizer)   Interval (torch.autograd.profiler)   Pipe (caffe2.python.dataio)   TestCaffe2Backend (test_pytorch_onnx_caffe2)   _Loop (caffe2.python.net_builder)   
ConstantPad1d (torch.nn.modules.padding)   IntStorage (torch.cuda)   PipedReaderBuilder (caffe2.python.dataio)   TestCase (expecttest)   _Loss (torch.nn.modules.loss)   
ConstantPad2d (torch.nn.modules.padding)   IntStorage (torch.distributed.deprecated.remote_types)   PixelShuffle (torch.nn.modules.pixelshuffle)   TestCase (caffe2.python.onnx.tests.test_utils)   _LowerCholesky (torch.distributions.constraints)   
ConstantPad3d (torch.nn.modules.padding)   IntStorage (torch)   Plan (caffe2.python.core)   TestCase (caffe2.python.test_util)   _LowerTriangular (torch.distributions.constraints)   
ConstantWeight (caffe2.python.layers.constant_weight)   IR (caffe2.python.core)   Poisson (torch.distributions.poisson)   TestCase (common_utils)   _LPPoolNd (torch.nn.modules.pooling)   
Constraint (torch.distributions.constraints)   
  J  
PoissonNLLLoss (torch.nn.modules.loss)   TestCheckpoint (test_utils)   _LRScheduler (torch.optim.lr_scheduler)   
ConstraintRegistry (torch.distributions.constraint_registry)   Pool (torch.multiprocessing.pool)   TestCollectEnv (test_utils)   _Match (torch.distributions.kl)   
Container (torch.nn.modules.container)   JitTestCase (test_jit)   PositionWeighted (caffe2.python.layers.position_weighted)   TestConcatDataset (test_dataloader)   _MaxPoolNd (torch.nn.modules.pooling)   
ContextProp (torch.backends.cudnn)   Job (caffe2.python.checkpoint)   PowerTransform (torch.distributions.transforms)   TestConstraintRegistry (test_distributions)   _MaxUnpoolNd (torch.nn.modules.pooling)   
ContextProp (torch.backends.cuda)   JobRunner (caffe2.python.checkpoint)   PredictorExportMeta (caffe2.python.predictor.predictor_exporter)   TestConstraints (test_distributions)   _netD (model_defs.dcgan)   
Conv (caffe2.python.layers.conv)   
  K  
PrefixFileStoreTest (test_c10d)   TestCppExtension (test_cpp_extensions)   _netG (model_defs.dcgan)   
Conv1d (torch.nn.modules.conv)   PrefixTCPStoreTest (test_c10d)   TestCudaPrimaryCtx (test_cuda_primary_ctx)   _OpNamespace (torch._ops)   
Conv2d (torch.nn.modules.conv)   KLDivLoss (torch.nn.modules.loss)   PReLU (torch.nn.modules.activation)   TestCudaSparse (test_sparse)   _Ops (torch._ops)   
Conv3d (torch.nn.modules.conv)   
  L  
Printer (caffe2.python.net_printer)   TestCudaUncoalescedSparse (test_sparse)   _PositiveDefinite (torch.distributions.constraints)   
ConvTranspose1d (torch.nn.modules.conv)   ProcessGroupGlooTest (test_c10d)   TestCustomOperators (test_custom_ops)   _QueueReader (caffe2.python.queue_util)   
ConvTranspose2d (torch.nn.modules.conv)   L1Loss (torch.nn.modules.loss)   ProcessGroupNCCLTest (test_c10d)   TestCustomPinFn (test_dataloader)   _QueueReader (caffe2.python.record_queue)   
ConvTranspose3d (torch.nn.modules.conv)   L1Norm (caffe2.python.regularizer)   ProcessingReader (caffe2.python.pipeline)   TestDataLoader (test_dataloader)   _QueueWriter (caffe2.python.queue_util)   
CosineAnnealingLR (torch.optim.lr_scheduler)   L2Norm (caffe2.python.regularizer)   PseudoFP16Initializer (caffe2.python.modeling.initializers)   TestDataLoader (test_utils)   _QueueWriter (caffe2.python.record_queue)   
CosineEmbeddingLoss (torch.nn.modules.loss)   LabelSmooth (caffe2.python.layers.label_smooth)   
  Q  
TestDatasetRandomSplit (test_dataloader)   _Real (torch.distributions.constraints)   
CosineSimilarity (torch.nn.modules.distance)   LambdaLR (torch.optim.lr_scheduler)   TestDictDataLoader (test_dataloader)   _RealVector (torch.distributions.constraints)   
CounterReader (caffe2.python.dataio)   LambdaLRTestObject (test_optim)   QuantizedGRUCell (torch.jit.quantized)   TestDistBackend (test_thd_distributed)   _ReflectionPadNd (torch.nn.modules.padding)   
CRFWithLoss (caffe2.python.crf)   Laplace (torch.distributions.laplace)   QuantizedLinear (torch.jit.quantized)   TestDistBackend (test_distributed)   _ReplicationPadNd (torch.nn.modules.padding)   
CriterionTest (common_nn)   LastNWindowCollector (caffe2.python.layers.last_n_window_collector)   QuantizedLSTMCell (torch.jit.quantized)   TestDistributions (test_distributions)   _ReporterBuilder (caffe2.python.net_builder)   
CrossEntropyLoss (torch.nn.modules.loss)   LayerModelHelper (caffe2.python.layer_model_helper)   QuantizedRNNCell (torch.jit.quantized)   TestDistributionShapes (test_distributions)   _RequiredParameter (torch.optim.optimizer)   
CrossMapLRN2d (torch.nn._functions.thnn.normalization)   LayerNorm (torch.nn.modules.normalization)   QuantizedRNNCellBase (torch.jit.quantized)   TestDocCoverage (test_docs_coverage)   _RunElseNet (caffe2.python.net_builder)   
CrossMapLRN2d (torch.nn.modules.normalization)   LayerNormalization (caffe2.python.layers.layer_normalization)   Queue (caffe2.python.queue_util)   TestDTypeInfo (test_type_info)   _RunIf (caffe2.python.net_builder)   
CTCLoss (torch.nn.modules.loss)   LayerNormalizer (caffe2.python.normalizer)   Queue (torch.multiprocessing.queue)   TestEndToEndHybridFrontendModels (test_jit)   _RunIfNet (caffe2.python.net_builder)   
CudaError (torch.cuda)   LayerNormLSTMCell (caffe2.python.rnn_cell)   QueueWrapper (caffe2.python.queue_util)   TestExpectTest (test_expecttest)   _RunOnce (caffe2.python.net_builder)   
CudaMemoryLeakCheck (common_utils)   LayerNormMILSTMCell (caffe2.python.rnn_cell)   
  R  
TestFFI (test_utils)   _RunWhileCondition (caffe2.python.net_builder)   
CUDAModule (torch.backends.cuda)   LayerParameter (caffe2.python.layers.layers)   TestHub (test_utils)   _RunWhileNet (caffe2.python.net_builder)   
CuDNNError (torch.backends.cudnn)   LayersTestCase (caffe2.python.layer_test_util)   RandomDatasetMock (test_utils)   TestIndexing (test_indexing)   _SchemaNode (caffe2.python.schema)   
CuDNNHandle (torch.backends.cudnn)   LBFGS (torch.optim.lbfgs)   RandomFourierFeatures (caffe2.python.layers.random_fourier_features)   TestIndividualWorkerQueue (test_dataloader)   _SetupBuilder (caffe2.python.net_builder)   
CudnnModule (torch.backends.cudnn)   LeakyReLU (torch.nn.modules.activation)   RandomSampler (torch.utils.data.sampler)   TestJit (test_jit)   _Simplex (torch.distributions.constraints)   
CuDNNPlugin (tools.cwrap.plugins.CuDNNPlugin)   LegacyCosineAnnealingLR (test_optim)   Reader (caffe2.python.dataio)   TestJit (test_distributions)   _StopGuard (caffe2.python.net_builder)   
CWrapPlugin (tools.cwrap.plugins)   LegacyExponentialLR (test_optim)   ReaderBuilder (caffe2.python.dataio)   TestKL (test_distributions)   _StorageBase (torch.storage)   
  D  
LegacyMultiStepLR (test_optim)   ReaderWithDelay (caffe2.python.dataio)   TestLazyLogitsInitialization (test_distributions)   _TestTorchMixin (test_torch)   
LegacyStepLR (test_optim)   ReaderWithLimit (caffe2.python.dataio)   TestLRScheduler (test_optim)   _WeightedLoss (torch.nn.modules.loss)   
DataLoader (torch.utils.data.dataloader)   LegacyTracedModule (torch.jit)   ReaderWithLimitBase (caffe2.python.dataio)   TestModels (test_models)   _WorkspaceCtx (caffe2.python.onnx.workspace)   
DataParallel (torch.nn.parallel.data_parallel)   Linear (torch.nn.modules.linear)   ReaderWithTimeLimit (caffe2.python.dataio)   TestMPI (test_distributed)   
  b  
Dataset (torch.utils.data.dataset)   List (caffe2.python.schema)   RecordQueue (caffe2.python.record_queue)   TestMPI (test_thd_distributed)   
Dataset (caffe2.python.dataset)   ListCls (torch._jit_internal)   ReduceAddCoalesced (torch.nn.parallel._functions)   TestMSNPUTensor (test_cpp_extensions)   bcolors (pyHIPIFY.hipify_python)   
DataType (caffe2.python.core)   ListInstance (torch._jit_internal)   ReduceLROnPlateau (torch.optim.lr_scheduler)   TestMultiprocessing (test_multiprocessing)   build_ext (setup)   
DataWorker (caffe2.python.data_workers)   LocalResponseNorm (torch.nn.modules.normalization)   ReflectionPad1d (torch.nn.modules.padding)   TestNamedTupleAPI (test_namedtuple_return_api)   
  c  
DBFileReader (caffe2.python.db_file_reader)   LocalSession (caffe2.python.session)   ReflectionPad2d (torch.nn.modules.padding)   TestNamedTupleDataLoader (test_dataloader)   
DebugMode (caffe2.python.utils)   LogBarrier (caffe2.python.regularizer)   RegularizationBy (caffe2.python.regularizer)   TestNCCL (test_nccl)   clean (setup)   
DeferredCudaCallError (torch.cuda)   LogisticNormal (torch.distributions.logistic_normal)   Regularizer (caffe2.python.regularizer)   TestNN (test_nn)   cudaOutputMode (torch.cuda.profiler)   
TestScript.DerivedStateModule (test_jit)   LogitRelaxedBernoulli (torch.distributions.relaxed_bernoulli)   RegularizerContext (caffe2.python.regularizer_context)   TestNNInit (test_nn)   cudaStatus (torch.cuda)   
DeviceChecker (caffe2.python.device_checker)   LogNormal (torch.distributions.log_normal)   RelaxedBernoulli (torch.distributions.relaxed_bernoulli)   TestNumbaIntegration (test_numba_integration)   cuFFTPlanCache (torch.backends.cuda)   
DictCls (torch._jit_internal)   LogSigmoid (torch.nn.modules.activation)   RelaxedOneHotCategorical (torch.distributions.relaxed_categorical)   TestNumericalStability (test_distributions)   cwrap (tools.cwrap.cwrap)   
DictDataset (test_dataloader)   LogSoftmax (torch.nn.modules.activation)   ReLU (torch.nn.modules.activation)   TestONNXUtils (test_utils)   
  d  
DictInstance (torch._jit_internal)   LongStorage (torch.cuda)   ReLU6 (torch.nn.modules.activation)   TestOperators (test_operators)   
Dirichlet (torch.distributions.dirichlet)   LongStorage (torch.distributed.deprecated.remote_types)   RemapEntry (caffe2.python.core)   TestOptim (test_optim)   define_context (caffe2.python.context)   
DistributedDataParallel (torch.nn.parallel.deprecated.distributed)   LongStorage (torch)   RemovableHandle (torch.utils.hooks)   TestProperExitDataset (test_dataloader)   detect_anomaly (torch.autograd.anomaly_mode)   
DistributedDataParallel (torch.nn.parallel.distributed)   LowerCholeskyTransform (torch.distributions.transforms)   RendezvousEnvTest (test_c10d)   TestPytorchExportModes (test_jit)   device (torch.cuda)   
DistributedDataParallelCPU (torch.nn.parallel.deprecated.distributed_cpu)   LowRankMultivariateNormal (torch.distributions.lowrank_multivariate_normal)   RendezvousFileTest (test_c10d)   TestQuantized (test_quantized)   device_of (torch.cuda)   
DistributedDataParallelCPU (torch.nn.parallel.distributed_cpu)   LPPool1d (torch.nn.modules.pooling)   RendezvousTCPTest (test_c10d)   TestRsample (test_distributions)   disablefuncmode (pyHIPIFY.hipify_python)   
DistributedDataParallelTest (test_c10d)   LPPool2d (torch.nn.modules.pooling)   RendezvousTest (test_c10d)   TestScript (test_jit)   dist_backend (torch.distributed.deprecated)   
DistributedSampler (torch.utils.data.distributed)   LRModificationTestBase (caffe2.python.optimizer_test_util)   ReplicationPad1d (torch.nn.modules.padding)   TestSparse (test_sparse)   dont_convert (common_methods_invocations)   
Distribution (torch.distributions.distribution)   LSTM (torch.nn.modules.rnn)   ReplicationPad2d (torch.nn.modules.padding)   TestSparseOneOff (test_sparse)   
  e  
DocGenerator (caffe2.python.docs.generator)   LSTMCell (torch.nn.modules.rnn)   ReplicationPad3d (torch.nn.modules.padding)   TestStringDataLoader (test_dataloader)   
DocUploader (caffe2.python.docs.generator)   LSTMCell (caffe2.python.rnn_cell)   ReservoirSampling (caffe2.python.layers.reservoir_sampling)   TestTensorDataset (test_dataloader)   emit_nvtx (torch.autograd.profiler)   
DoubleStorage (torch.cuda)   LstmFlatteningResult (model_defs.lstm_flattening_result)   ResidualBlock (model_defs.srresnet)   TestTorch (test_torch)   enable_grad (torch.autograd.grad_mode)   
DoubleStorage (torch.distributed.deprecated.remote_types)   LSTMInitializer (caffe2.python.rnn_cell)   Resize (torch.autograd._functions.tensor)   TestTransforms (test_distributions)   
  g  
DoubleStorage (torch)   LSTMWithAttentionCell (caffe2.python.rnn_cell)   ResNetBuilder (caffe2.python.models.resnet)   TestTypeHints (test_type_hints)   
DownloadingTestCase (caffe2.python.onnx.tests.test_utils)   LSTMWithAttentionDecoder (caffe2.python.models.seq2seq.seq2seq_util)   ReturnArguments (tools.cwrap.plugins.ReturnArguments)   TestUncoalescedSparse (test_sparse)   group (torch.distributed.deprecated)   
Dropout (torch.nn.modules.dropout)   
  M  
ReversePseudoFP16Initializer (caffe2.python.modeling.initializers)   TestValidation (test_distributions)   group (torch.distributed.distributed_c10d)   
Dropout (caffe2.python.layers.dropout)   RMSprop (torch.optim.rmsprop)   TestVerify (test_verify)   
  i  
Dropout2d (torch.nn.modules.dropout)   ManagerWatchdog (torch.utils.data._utils.worker)   RmsPropOptimizer (caffe2.python.optimizer)   TestWorkerQueueDataset (test_dataloader)   
Dropout3d (torch.nn.modules.dropout)   MapToRange (caffe2.python.layers.build_index)   RNN (torch.nn.modules.rnn)   Text (caffe2.python.net_printer)   install (setup)   
A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | Y | Z | _