Caffe2 - Python API
A deep learning, cross platform ML framework
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Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level
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►
N
caffe2
►
N
distributed
►
N
store_ops_test_util
C
StoreOpsTests
►
N
experiments
►
N
python
►
N
device_reduce_sum_bench
C
Benchmark
C
BenchmarkMeta
C
SoftMaxWithLoss
C
SumElements
C
SumSqrElements
►
N
SparseTransformer
C
NetDefNode
►
N
python
►
N
attention
C
AttentionType
►
N
binarysize
C
Trie
►
N
brew
C
HelperWrapper
►
N
cached_reader
C
CachedReader
►
N
caffe_translator
C
TranslatorRegistry
►
N
checkpoint
C
CheckpointManager
C
Job
C
JobRunner
C
MultiNodeCheckpointManager
C
UploadTaskGroupBuilder
►
N
cnn
C
CNNModelHelper
►
N
context
C
_ContextInfo
C
_ContextRegistry
C
define_context
►
N
core
C
BlobReference
C
DataType
C
ExecutionStep
C
GradientRegistry
C
IR
C
Net
C
Plan
C
RemapEntry
►
N
crf
C
CRFWithLoss
►
N
data_parallel_model
C
CollectivesConcurrencyControl
►
N
data_workers
C
BatchFeeder
C
DataWorker
C
GlobalCoordinator
►
N
dataio
C
CompositeReader
C
CompositeReaderBuilder
C
CounterReader
C
Pipe
C
PipedReaderBuilder
C
Reader
C
ReaderBuilder
C
ReaderWithDelay
C
ReaderWithLimit
C
ReaderWithLimitBase
C
ReaderWithTimeLimit
C
Writer
►
N
dataset
C
_DatasetRandomReader
C
_DatasetReader
C
_DatasetWriter
C
Dataset
►
N
db_file_reader
C
DBFileReader
►
N
device_checker
C
DeviceChecker
►
N
docs
►
N
formatter
C
Formatter
C
Markdown
►
N
generator
C
DocGenerator
C
DocUploader
C
OpDocGenerator
C
OperatorDoc
C
OperatorEngine
►
N
github
C
GHMarkdown
C
GHOpDocGenerator
C
GHOpDocUploader
C
GHOperatorDoc
C
GHOperatorEngine
►
N
parser
C
Parser
►
N
examples
►
N
char_rnn
C
CharRNN
►
N
experiment_util
C
ExternalLogger
C
ModelTrainerLog
►
N
functional
C
_Functional
►
N
gradient_checker
C
GradientChecker
C
NetGradientChecker
►
N
gru_cell
C
GRUCell
►
N
hypothesis_test_util
C
HypothesisTestCase
►
N
layer_model_helper
C
LayerModelHelper
►
N
layer_test_util
C
LayersTestCase
C
OpSpec
►
N
layers
►
N
adaptive_weight
C
AdaptiveWeight
►
N
add_bias
C
AddBias
►
N
arc_cosine_feature_map
C
ArcCosineFeatureMap
►
N
batch_distill_lr_loss
C
BatchDistillLRLoss
►
N
batch_lr_loss
C
BatchLRLoss
►
N
batch_mse_loss
C
BatchMSELoss
►
N
batch_normalization
C
BatchNormalization
►
N
batch_sigmoid_cross_entropy_loss
C
BatchSigmoidCrossEntropyLoss
►
N
batch_softmax_loss
C
BatchSoftmaxLoss
►
N
blob_weighted_sum
C
BlobWeightedSum
►
N
bucket_weighted
C
BucketWeighted
►
N
build_index
C
MapToRange
►
N
concat
C
Concat
►
N
constant_weight
C
ConstantWeight
►
N
conv
C
Conv
►
N
dropout
C
Dropout
►
N
fc
C
FC
►
N
fc_without_bias
C
FCWithoutBias
►
N
feature_sparse_to_dense
C
FeatureSparseToDense
►
N
functional
C
Functional
►
N
gather_record
C
GatherRecord
►
N
homotopy_weight
C
HomotopyWeight
►
N
label_smooth
C
LabelSmooth
►
N
last_n_window_collector
C
LastNWindowCollector
►
N
layer_normalization
C
LayerNormalization
►
N
layers
C
InstantiationContext
C
LayerParameter
C
ModelLayer
►
N
margin_rank_loss
C
MarginRankLoss
►
N
merge_id_lists
C
MergeIdLists
►
N
pairwise_similarity
C
PairwiseSimilarity
►
N
position_weighted
C
PositionWeighted
►
N
random_fourier_features
C
RandomFourierFeatures
►
N
reservoir_sampling
C
ReservoirSampling
►
N
sampling_train
C
SamplingTrain
►
N
sampling_trainable_mixin
C
SamplingTrainableMixin
►
N
select_record_by_context
C
SelectRecordByContext
►
N
semi_random_features
C
SemiRandomFeatures
►
N
sparse_feature_hash
C
SparseFeatureHash
►
N
sparse_lookup
C
SparseLookup
►
N
split
C
Split
►
N
tags
C
TagContext
C
Tags
►
N
uniform_sampling
C
UniformSampling
►
N
memonger
C
AssignmentAlgorithm
►
N
model_helper
C
ModelHelper
►
N
modeling
►
N
compute_histogram_for_blobs
C
ComputeHistogramForBlobs
►
N
compute_norm_for_blobs
C
ComputeNormForBlobs
►
N
compute_statistics_for_blobs
C
ComputeStatisticsForBlobs
►
N
get_entry_from_blobs
C
GetEntryFromBlobs
►
N
gradient_clipping
C
GradientClipping
►
N
initializers
C
ExternalInitializer
C
Initializer
C
PseudoFP16Initializer
C
ReversePseudoFP16Initializer
►
N
net_modifier
C
NetModifier
►
N
parameter_info
C
ParameterInfo
C
ParameterTags
►
N
parameter_sharing
C
ParameterSharingContext
►
N
models
►
N
download
C
ModelDownloader
►
N
resnet
C
ResNetBuilder
►
N
seq2seq
►
N
beam_search
C
BeamSearchForwardOnly
►
N
seq2seq_model_helper
C
Seq2SeqModelHelper
►
N
seq2seq_util
C
LSTMWithAttentionDecoder
►
N
train
C
Seq2SeqModelCaffe2
►
N
translate
C
Seq2SeqModelCaffe2EnsembleDecoder
C
Seq2SeqModelCaffe2EnsembleDecoderBase
►
N
modifier_context
C
ModifierContext
C
UseModifierBase
►
N
net_builder
C
_Loop
C
_ReporterBuilder
C
_RunElseNet
C
_RunIf
C
_RunIfNet
C
_RunOnce
C
_RunWhileCondition
C
_RunWhileNet
C
_SetupBuilder
C
_StopGuard
C
NetBuilder
C
Operations
►
N
net_printer
C
Analyzer
C
Printer
C
Text
C
Visitor
►
N
nomnigraph
C
NNModule
►
N
normalizer
C
BatchNormalizer
C
LayerNormalizer
C
Normalizer
►
N
normalizer_context
C
NormalizerContext
C
UseNormalizer
►
N
onnx
►
N
backend
C
Caffe2Backend
C
OnnxAttributes
C
OnnxNode
►
N
backend_cpp_rep
C
Caffe2CppRep
►
N
backend_rep
C
Caffe2Rep
►
N
error
C
BaseException
C
Unsupported
►
N
frontend
C
Caffe2Frontend
►
N
test_onnxifi
C
OnnxifiTest
C
OnnxifiTransformTest
►
N
tests
►
N
test_utils
C
DownloadingTestCase
C
TestCase
►
N
workspace
C
_WorkspaceCtx
C
Workspace
►
N
optimizer
C
AdadeltaOptimizer
C
AdagradOptimizer
C
AdamOptimizer
C
FP16SgdOptimizer
C
FtrlOptimizer
C
GFtrlOptimizer
C
MultiPrecisionSgdOptimizer
C
Optimizer
C
RmsPropOptimizer
C
SgdOptimizer
C
WeightDecayBuilder
C
WngradOptimizer
C
YellowFinOptimizer
►
N
optimizer_context
C
OptimizerContext
C
UseOptimizer
►
N
optimizer_test_util
C
LRModificationTestBase
C
OptimizerTestBase
►
N
parallel_workers
C
GlobalWorkerCoordinator
C
Metrics
C
State
C
Worker
C
WorkerCoordinator
►
N
pipeline
C
NetProcessor
C
Output
C
ProcessingReader
►
N
predictor
►
N
predictor_exporter
C
PredictorExportMeta
►
N
queue_util
C
_QueueReader
C
_QueueWriter
C
Queue
C
QueueWrapper
►
N
record_queue
C
_QueueReader
C
_QueueWriter
C
RecordQueue
►
N
regularizer
C
BoundedGradientProjection
C
ConstantNorm
C
GroupL1Norm
C
L1Norm
C
L2Norm
C
LogBarrier
C
MaxNorm
C
RegularizationBy
C
Regularizer
►
N
regularizer_context
C
RegularizerContext
C
UseRegularizer
►
N
rnn_cell
C
AttentionCell
C
BasicRNNCell
C
DropoutCell
C
LayerNormLSTMCell
C
LayerNormMILSTMCell
C
LSTMCell
C
LSTMInitializer
C
LSTMWithAttentionCell
C
MILSTMCell
C
MILSTMWithAttentionCell
C
MultiRNNCell
C
MultiRNNCellInitializer
C
RNNCell
C
UnrolledCell
►
N
schema
C
_SchemaNode
C
Field
C
List
C
Metadata
C
Scalar
C
Struct
►
N
serialized_test
►
N
serialized_test_util
C
SerializedTestCase
►
N
session
C
CompiledRunnable
C
LocalSession
C
Session
►
N
task
C
Cluster
C
Node
C
SetupNets
C
Task
C
TaskGroup
C
TaskOutput
C
TaskOutputList
C
WorkspaceType
►
N
test
►
N
executor_test_util
C
ExecutorTestBase
►
N
test_util
C
TestCase
►
N
text_file_reader
C
TextFileReader
►
N
timeout_guard
C
WatcherThread
►
N
transformations
C
Transformer
►
N
trt
►
N
test_trt
C
TensorRTOpTest
C
TensorRTTransformTest
►
N
utils
C
DebugMode
►
N
visualize
C
NCHW
C
NHWC
C
PatchVisualizer
►
N
workspace
C
_BlobDict
►
N
code_template
C
CodeTemplate
►
N
common_methods_invocations
C
dont_convert
C
NoArgsClass
C
non_differentiable
►
N
common_nn
C
CriterionTest
C
ModuleTest
C
NNTestCase
C
TestBase
►
N
common_utils
C
CudaMemoryLeakCheck
C
TestCase
►
N
common_with_cwrap
C
Argument
C
Function
►
N
expecttest
C
EditHistory
C
TestCase
►
N
function_wrapper
C
NYIError
►
N
gen
C
FileManager
►
N
model
C
Model
►
N
model_defs
►
N
dcgan
C
_netD
C
_netG
►
N
lstm_flattening_result
C
LstmFlatteningResult
►
N
mnist
C
MNIST
►
N
rnn_model_with_packed_sequence
C
RnnModelWithPackedSequence
►
N
squeezenet
C
Fire
C
SqueezeNet
►
N
srresnet
C
ResidualBlock
C
SRResNet
C
UpscaleBlock
►
N
super_resolution
C
SuperResolutionNet
►
N
word_language_model
C
RNNModel
►
N
network1
C
Net
►
N
network2
C
Net
►
N
pyHIPIFY
►
N
hipify_python
C
bcolors
C
disablefuncmode
C
InputError
C
Trie
►
N
pytorch_helper
C
_FakeDict
►
N
setup
C
build_ext
C
clean
C
install
►
N
test_autograd
C
TestAutograd
►
N
test_c10d
C
DistributedDataParallelTest
C
FileStoreTest
C
MultiProcessTestCase
C
Net
C
PrefixFileStoreTest
C
PrefixTCPStoreTest
C
ProcessGroupGlooTest
C
ProcessGroupNCCLTest
C
RendezvousEnvTest
C
RendezvousFileTest
C
RendezvousTCPTest
C
RendezvousTest
C
StoreTestBase
C
TCPStoreTest
►
N
test_cpp_extensions
C
TestCppExtension
C
TestMSNPUTensor
►
N
test_cuda
C
Model
►
N
test_cuda_primary_ctx
C
TestCudaPrimaryCtx
►
N
test_custom_ops
C
TestCustomOperators
►
N
test_dataloader
C
DictDataset
C
ErrorDataset
C
ErrorTrackingProcess
C
NamedTupleDataset
C
SeedDataset
C
SegfaultDataset
C
SimpleCustomBatch
C
SleepDataset
C
StringDataset
C
SynchronizedSeedDataset
C
TestConcatDataset
C
TestCustomPinFn
C
TestDataLoader
C
TestDatasetRandomSplit
C
TestDictDataLoader
C
TestIndividualWorkerQueue
C
TestNamedTupleDataLoader
C
TestProperExitDataset
C
TestStringDataLoader
C
TestTensorDataset
C
TestWorkerQueueDataset
►
N
test_distributed
C
_DistTestBase
C
_FC2
C
Barrier
C
BatchNormNet
C
Net
C
TestDistBackend
C
TestMPI
►
N
test_distributions
C
TestAgainstScipy
C
TestConstraintRegistry
C
TestConstraints
C
TestDistributions
C
TestDistributionShapes
C
TestJit
C
TestKL
C
TestLazyLogitsInitialization
C
TestNumericalStability
C
TestRsample
C
TestTransforms
C
TestValidation
►
N
test_docs_coverage
C
TestDocCoverage
►
N
test_expecttest
C
TestExpectTest
►
N
test_indexing
C
NumpyTests
C
TestIndexing
►
N
test_jit
C
FooToPickle
C
JitTestCase
C
MnistNet
C
TestBatched
C
TestEndToEndHybridFrontendModels
C
TestJit
►
C
TestPytorchExportModes
C
MyModel
►
C
TestScript
C
DerivedStateModule
C
StarTestReturnThree
C
StarTestSumAndReturnThree
C
StarTestSumStarred
►
N
test_models
C
TestModels
►
N
test_multiprocessing
C
leak_checker
C
SubProcess
C
TestMultiprocessing
►
N
test_multiprocessing_spawn
C
SpawnTest
►
N
test_namedtuple_return_api
C
TestNamedTupleAPI
►
N
test_nccl
C
TestNCCL
►
N
test_nn
C
_AdaptiveLogSoftmaxWithLoss
C
InputVariableMixin
C
NewCriterionTest
C
NewModuleTest
C
PackedSequenceTest
C
TestNN
C
TestNNInit
C
UnpoolingNet
►
N
test_numba_integration
C
TestNumbaIntegration
►
N
test_operators
C
FuncModule
C
TestOperators
►
N
test_optim
C
LambdaLRTestObject
C
LegacyCosineAnnealingLR
C
LegacyExponentialLR
C
LegacyMultiStepLR
C
LegacyStepLR
C
SchedulerTestNet
C
TestLRScheduler
C
TestOptim
►
N
test_pytorch_helper
C
TestCaffe2Backend
►
N
test_pytorch_onnx_caffe2
C
TestCaffe2Backend
►
N
test_sparse
C
TestCudaSparse
C
TestCudaUncoalescedSparse
C
TestSparse
C
TestSparseOneOff
C
TestUncoalescedSparse
►
N
test_thd_distributed
C
_DistTestBase
C
_FC2
C
Barrier
C
Net
C
TestDistBackend
C
TestMPI
►
N
test_torch
C
_TestTorchMixin
C
BytesIOContext
C
FilelikeMock
C
TestTorch
►
N
test_type_hints
C
TestTypeHints
►
N
test_type_info
C
TestDTypeInfo
►
N
test_utils
C
RandomDatasetMock
C
TestBottleneck
C
TestCheckpoint
C
TestCollectEnv
C
TestDataLoader
C
TestFFI
C
TestHub
C
TestONNXUtils
►
N
test_verify
C
TestVerify
►
N
tools
Module caffe2.python.helpers.tools
►
N
autograd
►
N
nested_dict
C
nested_dict
►
N
cwrap
►
N
cwrap
C
cwrap
►
N
plugins
►
N
ArgcountChecker
C
ArgcountChecker
►
N
ArgumentReferences
C
ArgumentReferences
►
N
AutoGPU
C
AutoGPU
►
N
BeforeAfterCall
C
BeforeAfterCall
►
N
ConstantArguments
C
ConstantArguments
►
N
CuDNNPlugin
C
CuDNNPlugin
►
N
GILRelease
C
GILRelease
►
N
NNExtension
C
NNExtension
►
N
NullableArguments
C
NullableArguments
C
UndefinedArguments
►
N
OptionalArguments
C
OptionalArguments
►
N
ReturnArguments
C
ReturnArguments
►
N
WrapDim
C
WrapDim
C
CWrapPlugin
►
N
jit
►
N
torch
►
N
_jit_internal
C
BroadcastingListCls
C
DictCls
C
DictInstance
C
ListCls
C
ListInstance
C
TupleCls
C
TupleInstance
►
N
_ops
C
_OpNamespace
C
_Ops
►
N
_tensor_str
C
__PrinterOptions
C
_Formatter
►
N
_thnn
►
N
utils
C
Argument
C
Function
C
THNNBackendBase
C
Backend
C
Backends
C
THNNCudaBackendStateMixin
►
N
autograd
►
N
_functions
►
N
tensor
C
Resize
C
Type
►
N
anomaly_mode
C
detect_anomaly
C
set_detect_anomaly
►
N
function
C
_ContextMethodMixin
C
_HookMixin
C
BackwardCFunction
C
Function
C
FunctionMeta
C
InplaceFunction
C
NestedIOFunction
►
N
grad_mode
C
enable_grad
C
no_grad
C
set_grad_enabled
►
N
profiler
C
emit_nvtx
C
EnforceUnique
CUDA checkpoints
C
EventList
C
FormattedTimesMixin
C
FunctionEvent
C
FunctionEventAvg
C
Interval
C
Kernel
C
profile
C
range
C
StringTable
►
N
variable
C
Variable
C
VariableMeta
►
N
backends
►
N
cuda
C
ContextProp
C
CUDAModule
C
cuFFTPlanCache
►
N
cudnn
►
N
rnn
C
Unserializable
C
ContextProp
C
CuDNNError
C
CuDNNHandle
C
CudnnModule
C
DropoutDescriptor
C
FilterDescriptor
C
RNNDescriptor
C
TensorDescriptor
C
TensorDescriptorArray
►
N
contrib
►
N
cuda
►
N
profiler
C
cudaOutputMode
►
N
streams
C
Event
C
Stream
C
_CudaBase
C
BoolStorage
C
ByteStorage
C
CharStorage
C
CudaError
C
cudaStatus
C
DeferredCudaCallError
C
device
C
device_of
C
DoubleStorage
C
FloatStorage
C
HalfStorage
C
IntStorage
C
LongStorage
C
ShortStorage
►
N
distributed
►
N
deprecated
►
N
remote_types
C
_DistributedBase
C
ByteStorage
C
CharStorage
C
DoubleStorage
C
FloatStorage
C
HalfStorage
C
IntStorage
C
LongStorage
C
ShortStorage
C
_DistributedRequest
C
dist_backend
C
group
C
reduce_op
►
N
distributed_c10d
C
Backend
C
group
C
GroupMember
C
reduce_op
►
N
distributions
►
N
bernoulli
C
Bernoulli
►
N
beta
C
Beta
►
N
binomial
C
Binomial
►
N
categorical
C
Categorical
►
N
cauchy
C
Cauchy
►
N
chi2
C
Chi2
►
N
constraint_registry
C
ConstraintRegistry
►
N
constraints
C
_Boolean
C
_Dependent
C
_DependentProperty
C
_GreaterThan
C
_GreaterThanEq
C
_HalfOpenInterval
C
_IntegerGreaterThan
C
_IntegerInterval
C
_IntegerLessThan
C
_Interval
C
_LessThan
C
_LowerCholesky
C
_LowerTriangular
C
_PositiveDefinite
C
_Real
C
_RealVector
C
_Simplex
C
Constraint
►
N
dirichlet
C
_Dirichlet
C
Dirichlet
►
N
distribution
C
Distribution
►
N
exp_family
C
ExponentialFamily
►
N
exponential
C
Exponential
►
N
fishersnedecor
C
FisherSnedecor
►
N
gamma
C
Gamma
►
N
geometric
C
Geometric
►
N
gumbel
C
Gumbel
►
N
half_cauchy
C
HalfCauchy
►
N
half_normal
C
HalfNormal
►
N
independent
C
Independent
►
N
kl
C
_Match
►
N
laplace
C
Laplace
►
N
log_normal
C
LogNormal
►
N
logistic_normal
C
LogisticNormal
►
N
lowrank_multivariate_normal
C
LowRankMultivariateNormal
►
N
multinomial
C
Multinomial
►
N
multivariate_normal
C
MultivariateNormal
►
N
negative_binomial
C
NegativeBinomial
►
N
normal
C
Normal
►
N
one_hot_categorical
C
OneHotCategorical
►
N
pareto
C
Pareto
►
N
poisson
C
Poisson
►
N
relaxed_bernoulli
C
LogitRelaxedBernoulli
C
RelaxedBernoulli
►
N
relaxed_categorical
C
ExpRelaxedCategorical
C
RelaxedOneHotCategorical
►
N
studentT
C
StudentT
►
N
transformed_distribution
C
TransformedDistribution
►
N
transforms
C
_InverseTransform
C
AbsTransform
C
AffineTransform
C
ComposeTransform
C
ExpTransform
C
LowerCholeskyTransform
C
PowerTransform
C
SigmoidTransform
C
SoftmaxTransform
C
StickBreakingTransform
C
Transform
►
N
uniform
C
Uniform
►
N
utils
C
lazy_property
►
N
weibull
C
Weibull
►
N
jit
►
N
annotations
C
Module
►
N
frontend
C
Builder
C
ExprBuilder
C
FrontendError
C
FrontendTypeError
C
NotSupportedError
C
SourceContext
C
StmtBuilder
C
UnsupportedNodeError
►
N
quantized
C
QuantizedGRUCell
C
QuantizedLinear
C
QuantizedLSTMCell
C
QuantizedRNNCell
C
QuantizedRNNCellBase
C
_ConstModuleList
C
_ConstSequential
C
_disable_tracing
C
Attribute
C
CompilationUnit
C
LegacyTracedModule
C
OrderedBufferDict
C
OrderedDictWrapper
C
OrderedModuleDict
C
OrderedParameterDict
C
ScriptClass
C
ScriptMeta
C
ScriptModule
C
TopLevelTracedModule
C
TracedModule
C
TracerWarning
C
TracingCheckError
C
WeakScriptModuleProxy
►
N
multiprocessing
►
N
pool
C
Pool
►
N
queue
C
ConnectionWrapper
C
Queue
C
SimpleQueue
►
N
reductions
C
SharedCache
C
StorageWeakRef
►
N
spawn
C
SpawnContext
►
N
nn
►
N
_functions
►
N
thnn
►
N
normalization
C
CrossMapLRN2d
►
N
sparse
C
EmbeddingBag
►
N
_VF
C
VFModule
►
N
backends
►
N
backend
C
FunctionBackend
►
N
thnn
C
THNNFunctionBackend
►
N
cpp
C
ModuleWrapper
C
OrderedDictWrapper
►
N
modules
►
N
_functions
C
SyncBatchNorm
►
N
activation
C
CELU
C
ELU
C
GLU
C
Hardshrink
C
Hardtanh
C
LeakyReLU
C
LogSigmoid
C
LogSoftmax
C
PReLU
C
ReLU
C
ReLU6
C
RReLU
C
SELU
C
Sigmoid
C
Softmax
C
Softmax2d
C
Softmin
C
Softplus
C
Softshrink
C
Softsign
C
Tanh
C
Tanhshrink
C
Threshold
►
N
adaptive
C
AdaptiveLogSoftmaxWithLoss
►
N
batchnorm
C
_BatchNorm
C
BatchNorm1d
C
BatchNorm2d
C
BatchNorm3d
C
SyncBatchNorm
►
N
container
C
Container
C
ModuleDict
C
ModuleList
C
ParameterDict
C
ParameterList
C
Sequential
►
N
conv
C
_ConvNd
C
_ConvTransposeMixin
C
Conv1d
C
Conv2d
C
Conv3d
C
ConvTranspose1d
C
ConvTranspose2d
C
ConvTranspose3d
►
N
distance
C
CosineSimilarity
C
PairwiseDistance
►
N
dropout
C
_DropoutNd
C
AlphaDropout
C
Dropout
C
Dropout2d
C
Dropout3d
C
FeatureAlphaDropout
►
N
fold
C
Fold
C
Unfold
►
N
instancenorm
C
_InstanceNorm
C
InstanceNorm1d
C
InstanceNorm2d
C
InstanceNorm3d
►
N
linear
C
Bilinear
C
Linear
►
N
loss
C
_Loss
C
_WeightedLoss
C
BCELoss
C
BCEWithLogitsLoss
C
CosineEmbeddingLoss
C
CrossEntropyLoss
C
CTCLoss
C
HingeEmbeddingLoss
C
KLDivLoss
C
L1Loss
C
MarginRankingLoss
C
MSELoss
C
MultiLabelMarginLoss
C
MultiLabelSoftMarginLoss
C
MultiMarginLoss
C
NLLLoss
C
NLLLoss2d
C
PoissonNLLLoss
C
SmoothL1Loss
C
SoftMarginLoss
C
TripletMarginLoss
►
N
module
C
Module
►
N
normalization
C
CrossMapLRN2d
C
GroupNorm
C
LayerNorm
C
LocalResponseNorm
►
N
padding
C
_ConstantPadNd
C
_ReflectionPadNd
C
_ReplicationPadNd
C
ConstantPad1d
C
ConstantPad2d
C
ConstantPad3d
C
ReflectionPad1d
C
ReflectionPad2d
C
ReplicationPad1d
C
ReplicationPad2d
C
ReplicationPad3d
C
ZeroPad2d
►
N
pixelshuffle
C
PixelShuffle
►
N
pooling
C
_AdaptiveAvgPoolNd
C
_AdaptiveMaxPoolNd
C
_AvgPoolNd
C
_LPPoolNd
C
_MaxPoolNd
C
_MaxUnpoolNd
C
AdaptiveAvgPool1d
C
AdaptiveAvgPool2d
C
AdaptiveAvgPool3d
C
AdaptiveMaxPool1d
C
AdaptiveMaxPool2d
C
AdaptiveMaxPool3d
C
AvgPool1d
C
AvgPool2d
C
AvgPool3d
C
FractionalMaxPool2d
C
FractionalMaxPool3d
C
LPPool1d
C
LPPool2d
C
MaxPool1d
C
MaxPool2d
C
MaxPool3d
C
MaxUnpool1d
C
MaxUnpool2d
C
MaxUnpool3d
►
N
rnn
C
GRU
C
GRUCell
C
LSTM
C
LSTMCell
C
RNN
C
RNNBase
C
RNNCell
C
RNNCellBase
►
N
sparse
C
Embedding
C
EmbeddingBag
►
N
upsampling
C
Upsample
C
UpsamplingBilinear2d
C
UpsamplingNearest2d
►
N
parallel
►
N
_functions
C
Broadcast
C
Gather
C
ReduceAddCoalesced
C
Scatter
►
N
data_parallel
C
DataParallel
►
N
deprecated
►
N
distributed
C
DistributedDataParallel
►
N
distributed_cpu
C
DistributedDataParallelCPU
►
N
distributed
C
DistributedDataParallel
►
N
distributed_cpu
C
DistributedDataParallelCPU
►
N
parameter
C
Parameter
►
N
utils
►
N
rnn
C
PackedSequence
►
N
spectral_norm
C
SpectralNorm
C
SpectralNormLoadStateDictPreHook
C
SpectralNormStateDictHook
►
N
weight_norm
C
WeightNorm
►
N
onnx
C
ExportTypes
►
N
optim
►
N
adadelta
C
Adadelta
►
N
adagrad
C
Adagrad
►
N
adam
C
Adam
►
N
adamax
C
Adamax
►
N
asgd
C
ASGD
►
N
lbfgs
C
LBFGS
►
N
lr_scheduler
C
_LRScheduler
C
CosineAnnealingLR
C
ExponentialLR
C
LambdaLR
C
MultiStepLR
C
ReduceLROnPlateau
C
StepLR
►
N
optimizer
C
_RequiredParameter
C
Optimizer
►
N
rmsprop
C
RMSprop
►
N
rprop
C
Rprop
►
N
sgd
C
SGD
►
N
sparse_adam
C
SparseAdam
►
N
serialization
C
SourceChangeWarning
►
N
storage
C
_StorageBase
►
N
tensor
C
Tensor
►
N
utils
►
N
_cpp_extension_versioner
C
ExtensionVersioner
►
N
backcompat
C
Warning
►
N
checkpoint
C
CheckpointFunction
►
N
cpp_extension
C
BuildExtension
►
N
data
►
N
_utils
►
N
worker
C
ManagerWatchdog
C
ExceptionWrapper
►
N
dataloader
C
_DataLoaderIter
C
DataLoader
►
N
dataset
C
ConcatDataset
C
Dataset
C
Subset
C
TensorDataset
►
N
distributed
C
DistributedSampler
►
N
sampler
C
BatchSampler
C
RandomSampler
C
Sampler
C
SequentialSampler
C
SubsetRandomSampler
C
WeightedRandomSampler
►
N
file_baton
C
FileBaton
►
N
hooks
C
RemovableHandle
►
N
model_zoo
C
tqdm
C
BoolStorage
C
ByteStorage
C
CharStorage
C
DoubleStorage
C
FloatStorage
C
HalfStorage
C
IntStorage
C
LongStorage
C
ShortStorage
►
N
update-caffe2-models
C
SomeClass
►
N
verify
C
Errors
Generated on Thu Mar 21 2019 13:06:40 for Caffe2 - Python API by
1.8.11
1.8.11
