[−][src]Module tensorflow_proto::tensorflow
Modules
Structs
AllocationDescription | |
AllocationRecord | An allocation/de-allocation operation performed by the allocator. |
AllocatorMemoryUsed | |
ApiDef | Used to specify and override the default API & behavior in the generated code for client languages, from what you would get from the OpDef alone. There will be a set of ApiDefs that are common to all client languages, and another set per client language. The per-client-language ApiDefs will inherit values from the common ApiDefs which it can either replace or modify. |
ApiDefs | |
AssetFileDef | An asset file def for a single file or a set of sharded files with the same name. |
AttrValue | Protocol buffer representing the value for an attr used to configure an Op. Comment indicates the corresponding attr type. Only the field matching the attr type may be filled. |
AutoParallelOptions | |
AutotuneResult | |
AutotuningLog | |
AvailableDeviceInfo | Matches DeviceAttributes |
BenchmarkEntries | |
BenchmarkEntry | Each unit test or benchmark in a test or benchmark run provides some set of information. Here we provide some reasonable keys one would expect to see, with optional key/value pairs for things we haven't considered. |
BigQueryTablePartition | This proto specifies a table partition in BigQuery. |
BuildConfiguration | |
BundleEntryProto | Describes the metadata related to a checkpointed tensor. |
BundleHeaderProto | Special header that is associated with a bundle. |
BytesList | Containers to hold repeated fundamental values. |
CallTraceback | Data on the traceback of a debugged call, e.g., a Session.run() call, or the execution of an eager operation. |
CallableOptions | Defines a subgraph in another |
Channel | |
CheckpointState | Protocol buffer representing the checkpoint state. |
CleanupAllRequest | |
CleanupAllResponse | |
CleanupGraphRequest | |
CleanupGraphResponse | |
CloseSessionRequest | |
CloseSessionResponse | |
ClusterDef | Defines a TensorFlow cluster as a set of jobs. |
CollectionDef | CollectionDef should cover most collections. To add a user-defined collection, do one of the following: |
CommitId | |
CompleteGroupRequest | Supplies one or more device names as members of the group identified by group_key. Service will respond when all group_size devices become known. All devices in group must have same type. |
CompleteGroupResponse | Gives the complete membership of the group identified by group_key. |
CompleteInstanceRequest | Supplies data about one collective op belonging to the instance identified by instance_key. Service will respond when all group_size ops have become known. Most of the data being sent is for correctness checking, to ensure that all ops in the instance share common attributes. |
CompleteInstanceResponse | Confirms that every op in the instance has consistently declared itself. Also gives the source_rank in case of broadcast. |
ComputeCapability | |
CondContextDef | Protocol buffer representing a CondContext object. |
ConfigProto | Session configuration parameters. The system picks appropriate values for fields that are not set. |
ControlFlowContextDef | Container for any kind of control flow context. Any other control flow contexts that are added below should also be added here. |
ConvolutionProto | A convolution. Currently it's only used for logging. In the future, we may want to use it in the API as well. |
CostGraphDef | |
CppShapeInferenceInputsNeeded | |
CppShapeInferenceResult | |
CpuInfo | |
CreateSessionRequest | |
CreateSessionResponse | |
CreateWorkerSessionRequest | |
CreateWorkerSessionResponse | |
CriticalSectionDef | Protocol buffer representing a CriticalSection. |
CriticalSectionExecutionDef | Protocol buffer representing a CriticalSection execution. |
CudnnVersion | |
DebugOptions | Options for initializing DebuggerState in TensorFlow Debugger (tfdbg). |
DebugTensorWatch | Option for watching a node in TensorFlow Debugger (tfdbg). |
DebuggedSourceFile | |
DebuggedSourceFiles | |
DeleteWorkerSessionRequest | |
DeleteWorkerSessionResponse | |
DeregisterGraphRequest | |
DeregisterGraphResponse | TODO(mrry): Optionally add summary stats for the graph. |
DeviceAttributes | |
DeviceLocality | |
DeviceProperties | |
DeviceStepStats | |
DictValue | Represents a Python dict keyed by |
EmbeddingInfo | |
EntryValue | |
EnumProfileSessionsAndToolsRequest | |
EnumProfileSessionsAndToolsResponse | |
ErrorStatusProto | |
Event | Protocol buffer representing an event that happened during the execution of a Brain model. |
EventReply | Reply message from EventListener to the client, i.e., to the source of the Event protocol buffers, e.g., debug ops inserted by a debugged runtime to a TensorFlow graph being executed. |
Example | |
ExampleParserConfiguration | |
ExampleWithExtras | This message is parallel to Example, but with additional fields to test unknown fields handling in example_proto_fast_parsing_test.cc. |
ExecutorOpts | Options specific to the execution of a single step. |
ExtendSessionRequest | |
ExtendSessionResponse | TODO(mrry): Return something about the operation? |
Feature | Containers for non-sequential data. |
FeatureConfiguration | |
FeatureList | Containers for sequential data. |
FeatureLists | |
Features | |
FixedLenFeatureProto | |
FloatList | |
FunctionDef | A function can be instantiated when the runtime can bind every attr with a value. When a GraphDef has a call to a function, it must have binding for every attr defined in the signature. |
FunctionDefLibrary | A library is a set of named functions. |
FunctionSpec | Represents |
GetRemoteAddressRequest | |
GetRemoteAddressResponse | |
GetStatusRequest | |
GetStatusResponse | |
GetStepSequenceRequest | Request for next agreed-upon step_id for the specified graph_keys. This is used to enable multiple graphs containing nodes from a common collective instance to coordinate using the same step_ids. |
GetStepSequenceResponse | Next valid step_ids for one or more graph_keys. |
GpuInfo | |
GpuOptions | |
GradientDef | GradientDef defines the gradient function of a function defined in a function library. |
GraphDebugInfo | |
GraphDef | Represents the graph of operations |
GraphOptions | |
GraphTransferConstNodeInfo | |
GraphTransferGraphInputNodeInfo | |
GraphTransferGraphOutputNodeInfo | |
GraphTransferInfo | Protocol buffer representing a handle to a tensorflow resource. Handles are not valid across executions, but can be serialized back and forth from within a single run. |
GraphTransferNodeInfo | |
GraphTransferNodeInput | |
GraphTransferNodeInputInfo | |
GraphTransferNodeOutputInfo | |
HParamDef | Protocol buffer holding hyper parameters. Examples of hyper parameters: learning_rate = 0.1, num_hidden_units = 100, activations = ['relu', 'tanh'] |
HistogramProto | Serialization format for histogram module in core/lib/histogram/histogram.h |
Int64List | |
InterconnectLink | |
JobDef | Defines a single job in a TensorFlow cluster. |
KernelDef | |
KernelList | A collection of KernelDefs |
LabeledStepStats | |
ListDevicesRequest | |
ListDevicesResponse | |
ListValue | Represents a Python list. |
LocalLinks | |
LogMessage | Protocol buffer used for logging messages to the events file. |
LogNormalDistribution | |
LoggingRequest | Out-of-band request to begin or end logging, or to retrieve logs for particular steps. |
LoggingResponse | |
MachineConfiguration | |
MakeCallableRequest | |
MakeCallableResponse | |
MarkRecvFinishedRequest | Message for managing the response cache maintained on the sender side. Currently only used by the gRPC worker service. |
MarkRecvFinishedResponse | |
MemmappedFileSystemDirectory | A directory of regions in a memmapped file. |
MemmappedFileSystemDirectoryElement | A message that describes one region of memmapped file. |
MemoryInfo | |
MemoryLogRawAllocation | |
MemoryLogRawDeallocation | |
MemoryLogStep | |
MemoryLogTensorAllocation | |
MemoryLogTensorDeallocation | |
MemoryLogTensorOutput | |
MemoryRegion | |
MemoryStats | For memory tracking. |
MetaGraphDef | NOTE: This protocol buffer is evolving, and will go through revisions in the coming months. |
MetricEntry | |
MonitorRequest | |
MonitorResponse | |
MpiRecvTensorResponse | |
NameAttrList | A list of attr names and their values. The whole list is attached with a string name. E.g., MatMul[T=float]. |
NamedDevice | |
NamedTensorProto | A pair of tensor name and tensor values. |
NamedTupleValue | Represents Python's namedtuple. |
NewProfileSessionRequest | |
NewProfileSessionResponse | |
NewReplaySession | Records the creation of a new replay session. We record the device listing here to capture the state of the cluster. |
NodeDef | |
NodeExecStats | Time/size stats recorded for a single execution of a graph node. |
NodeOutput | Output sizes recorded for a single execution of a graph node. |
NoneValue | Represents None. |
NormalDistribution | |
OpDef | Defines an operation. A NodeDef in a GraphDef specifies an Op by using the "op" field which should match the name of a OpDef. LINT.IfChange |
OpDeprecation | Information about version-dependent deprecation of an op |
OpInfo | Description of an operation as well as the parameters expected to impact its performance. |
OpList | A collection of OpDefs |
OpPerformance | Performance data for tensorflow operations |
OpPerformanceList | A collection of OpPerformance data points. |
OptimizerOptions | Options passed to the graph optimizer |
PairValue | Represents a (key, value) pair. |
PartialRunSetupRequest | |
PartialRunSetupResponse | |
PlatformInfo | |
ProfileOptions | |
ProfileRequest | |
ProfileResponse | |
ProfileSessionDataRequest | |
ProfileSessionDataResponse | |
ProfileSessionInfo | |
ProfileToolData | |
ProjectorConfig | |
QueueRunnerDef | Protocol buffer representing a QueueRunner. |
ReaderBaseState | For serializing and restoring the state of ReaderBase, see reader_base.h for details. |
RecvBufRequest | Use of the fields below may vary by implementation. For example the buf_ptr and num_bytes may be set only for local operations and not sent on the wire, or only sent on the wire in one direction. |
RecvBufRespExtra | Extra data needed on a non-RDMA RecvBufResponse. |
RecvBufResponse | Use of the fields below may vary by implementation. Comments give intended use. |
RecvTensorRequest | |
RecvTensorResponse | |
RegisterGraphRequest | |
RegisterGraphResponse | |
ReleaseCallableRequest | |
ReleaseCallableResponse | |
RemoteFusedGraphExecuteInfo | Protocol buffer representing a handle to a tensorflow resource. Handles are not valid across executions, but can be serialized back and forth from within a single run. |
RemoteMemoryRegion | |
ReplayOp | |
ResetRequest | Reset() allows misbehaving or slow sessions to be aborted and closed, and causes their resources eventually to be released. Reset() does not wait for the computations in old sessions to cease; it merely starts the process of tearing them down. However, if a new session is started after a Reset(), the new session is isolated from changes that old sessions (started prior to the Reset()) may continue to make to resources, provided all those resources are in containers listed in "containers". |
ResetResponse | |
ResourceHandleProto | Protocol buffer representing a handle to a tensorflow resource. Handles are not valid across executions, but can be serialized back and forth from within a single run. |
RewriterConfig | Graph rewriting is experimental and subject to change, not covered by any API stability guarantees. |
RpcOptions | |
RunCallableRequest | |
RunCallableResponse | |
RunConfiguration | Run-specific items such as arguments to the test / benchmark. |
RunGraphRequest | |
RunGraphResponse | |
RunMetadata | Metadata output (i.e., non-Tensor) for a single Run() call. |
RunOptions | Options for a single Run() call. |
RunStepRequest | |
RunStepResponse | |
SaveSliceInfoDef | |
SavedAsset | A SavedAsset points to an asset in the MetaGraph. |
SavedBareConcreteFunction | |
SavedConcreteFunction | Stores low-level information about a concrete function. Referenced in either a SavedFunction or a SavedBareConcreteFunction. |
SavedConstant | |
SavedFunction | A function with multiple signatures, possibly with non-Tensor arguments. |
SavedModel | SavedModel is the high level serialization format for TensorFlow Models. See [todo: doc links, similar to session_bundle] for more information. |
SavedObject | |
SavedObjectGraph | |
SavedResource | A SavedResource represents a TF object that holds state during its lifetime. An object of this type can have a reference to a: create_resource() and an initialize() function. |
SavedSlice | Saved tensor slice: it stores the name of the tensors, the slice, and the raw data. |
SavedSliceMeta | Metadata describing the set of slices of the same tensor saved in a checkpoint file. |
SavedTensorSliceMeta | Metadata describing the set of tensor slices saved in a checkpoint file. It is always stored at the beginning of each checkpoint file. |
SavedTensorSlices | Each record in a v3 checkpoint file is a serialized SavedTensorSlices message. |
SavedUserObject | A SavedUserObject is an object (in the object-oriented language of the TensorFlow program) of some user- or framework-defined class other than those handled specifically by the other kinds of SavedObjects. |
SavedVariable | Represents a Variable that is initialized by loading the contents from the checkpoint. |
SaverDef | Protocol buffer representing the configuration of a Saver. |
ScopedAllocatorOptions | |
SequenceExample | |
ServerDef | Defines the configuration of a single TensorFlow server. |
SessionInfo | Description of the session when an op is run. |
SessionLog | Protocol buffer used for logging session state. |
SessionMetadata | Metadata about the session. |
SignatureDef | SignatureDef defines the signature of a computation supported by a TensorFlow graph. |
SpriteMetadata | |
StepSequence | |
StepStats | |
StructuredValue |
|
Summary | A Summary is a set of named values to be displayed by the visualizer. |
SummaryDescription | Metadata associated with a series of Summary data |
SummaryMetadata | A SummaryMetadata encapsulates information on which plugins are able to make use of a certain summary value. |
TaggedRunMetadata | For logging the metadata output for a single session.run() call. |
TensorConnection | Defines a connection between two tensors in a |
TensorDescription | |
TensorInfo | Information about a Tensor necessary for feeding or retrieval. |
TensorProto | Protocol buffer representing a tensor. |
TensorShapeProto | Dimensions of a tensor. |
TensorSliceProto | Can only be interpreted if you know the corresponding TensorShape. |
TensorSpecProto | A protobuf to tf.TensorSpec. |
TensorTracerReport | Tensor Tracer Report proto gives information about the trace including: |
TestResults | The output of one benchmark / test run. Each run contains a list of tests or benchmarks, stored as BenchmarkEntry messages. |
ThreadPoolOptionProto | |
ToolRequestOptions | |
TraceOpts | |
TracingRequest | Out-of-band request to configure distributed tracing. |
TracingResponse | |
TrackableObjectGraph | |
TupleValue | Represents a Python tuple. |
TypeSpecProto | Represents a tf.TypeSpec |
ValuesDef | Protocol buffer representing the values in ControlFlowContext. |
VarLenFeatureProto | |
VariableDef | Protocol buffer representing a Variable. |
VariantTensorDataProto | Protocol buffer representing the serialization format of DT_VARIANT tensors. |
VerifierConfig | The config for graph verifiers. |
VersionDef | Version information for a piece of serialized data |
WatchdogConfig | |
WhileContextDef | Protocol buffer representing a WhileContext object. |
WorkerHeartbeatRequest | |
WorkerHeartbeatResponse | |
XlaAutoClusteringActivity | Listeners listening for auto clustering events get messages of this type. |
XlaAutoClusteringSummary | Summarizes the results of auto-clustering a TensorFlow graph. |
XlaJitCompilationActivity | Listeners listening for JIT compilation events get messages of this type. Each instance of XlaJitCompilationActivity corresponds to a single compilation of a single XLA cluster. E.g. if a graph has two clusters, A and B, and A is compiled 5 times and B is compiled 2 times then we will generate 7 instances of XlaJitCompilationActivity. |
XlaOptimizationRemark | LINT.IfChange |
Enums
DataType | (== suppress_warning documentation-presence ==) LINT.IfChange |
VariableAggregation | Indicates how a distributed variable will be aggregated. |
VariableSynchronization | Indicates when a distributed variable will be synced. |
WorkerHealth | Current health status of a worker. |
WorkerShutdownMode | Indicates the behavior of the worker when an internal error or shutdown signal is received. |