All Classes and Interfaces
Class
Description
Protobuf type
tensorflow.AllocationDescriptionProtobuf type
tensorflow.AllocationDescription
An allocation/de-allocation operation performed by the allocator.
An allocation/de-allocation operation performed by the allocator.
Protobuf type
tensorflow.AllocatorMemoryUsedProtobuf type
tensorflow.AllocatorMemoryUsed
`Any` contains an arbitrary serialized protocol buffer message along with a
URL that describes the type of the serialized message.
`Any` contains an arbitrary serialized protocol buffer message along with a
URL that describes the type of the serialized message.
An asset file def for a single file or a set of sharded files with the same
name.
An asset file def for a single file or a set of sharded files with the same
name.
Protocol buffer representing the value for an attr used to configure an Op.
Protocol buffer representing the value for an attr used to configure an Op.
LINT.IfChange
LINT.IfChange
Protobuf type
tensorflow.AutoParallelOptionsProtobuf type
tensorflow.AutoParallelOptionsProtobuf type
tensorflow.BatchingOptionsProtobuf type
tensorflow.BatchingOptions
Wrapper message for `bool`.
Wrapper message for `bool`.
LINT.IfChange
Containers to hold repeated fundamental values.
LINT.IfChange
Containers to hold repeated fundamental values.
Wrapper message for `bytes`.
Wrapper message for `bytes`.
Defines a subgraph in another `GraphDef` as a set of feed points and nodes
to be fetched or executed.
Defines a subgraph in another `GraphDef` as a set of feed points and nodes
to be fetched or executed.
A single class.
A single class.
Protobuf type
tensorflow.serving.ClassificationRequestProtobuf type
tensorflow.serving.ClassificationRequestProtobuf type
tensorflow.serving.ClassificationResponseProtobuf type
tensorflow.serving.ClassificationResponse
Contains one result per input example, in the same order as the input in
ClassificationRequest.
Contains one result per input example, in the same order as the input in
ClassificationRequest.
List of classes for a single item (tensorflow.Example).
List of classes for a single item (tensorflow.Example).
Defines a TensorFlow cluster as a set of jobs.
Defines a TensorFlow cluster as a set of jobs.
The canonical error codes for TensorFlow APIs.
CollectionDef should cover most collections.
AnyList is used for collecting Any protos.
AnyList is used for collecting Any protos.
CollectionDef should cover most collections.
BytesList is used for collecting strings and serialized protobufs.
BytesList is used for collecting strings and serialized protobufs.
FloatList is used for collecting float values.
FloatList is used for collecting float values.
Int64List is used for collecting int, int64 and long values.
Int64List is used for collecting int, int64 and long values.
NodeList is used for collecting nodes in graph.
NodeList is used for collecting nodes in graph.
Session configuration parameters.
Session configuration parameters.
Everything inside Experimental is subject to change and is not subject
to API stability guarantees in
https://www.tensorflow.org/guide/version_compat.
Everything inside Experimental is subject to change and is not subject
to API stability guarantees in
https://www.tensorflow.org/guide/version_compat.
An enum that describes the state of the MLIR bridge rollout.
Represents a job type and the number of tasks under this job.
Represents a job type and the number of tasks under this job.
Coordination service configuration parameters.
Coordination service configuration parameters.
Protobuf type
tensorflow.CostGraphDef
Total cost of this graph, typically used for balancing decisions.
Total cost of this graph, typically used for balancing decisions.
Protobuf type
tensorflow.CostGraphDefProtobuf type
tensorflow.CostGraphDef.NodeProtobuf type
tensorflow.CostGraphDef.Node
Inputs of this node.
Inputs of this node.
Outputs of this node.
Outputs of this node.
(== suppress_warning documentation-presence ==)
LINT.IfChange
Protobuf type
tensorflow.DebuggedSourceFileProtobuf type
tensorflow.DebuggedSourceFileProtobuf type
tensorflow.DebuggedSourceFilesProtobuf type
tensorflow.DebuggedSourceFiles
Options for initializing DebuggerState in TensorFlow Debugger (tfdbg).
Options for initializing DebuggerState in TensorFlow Debugger (tfdbg).
Option for watching a node in TensorFlow Debugger (tfdbg).
Option for watching a node in TensorFlow Debugger (tfdbg).
Protobuf type
tensorflow.DeviceStepStatsProtobuf type
tensorflow.DeviceStepStats
Wrapper message for `double`.
Wrapper message for `double`.
Protobuf type
tensorflow.ExampleProtobuf type
tensorflow.Example
Containers for non-sequential data.
Containers for non-sequential data.
Containers for sequential data.
Containers for sequential data.
Protobuf type
tensorflow.FeatureListsProtobuf type
tensorflow.FeatureListsProtobuf type
tensorflow.FeaturesProtobuf type
tensorflow.Features
Config proto for FileSystemStoragePathSource.
Config proto for FileSystemStoragePathSource.
A servable name and base path to look for versions of the servable.
A servable name and base path to look for versions of the servable.
A policy that dictates which version(s) of a servable should be served.
Serve all versions found on disk.
Serve all versions found on disk.
A policy that dictates which version(s) of a servable should be served.
Serve the latest versions (i.e. the ones with the highest version
numbers), among those found on disk.
Serve the latest versions (i.e. the ones with the highest version
numbers), among those found on disk.
FileSystemStoragePathSource.FileSystemStoragePathSourceConfig.ServableVersionPolicy.PolicyChoiceCase
Serve a specific version (or set of versions).
FileSystemStoragePathSource.FileSystemStoragePathSourceConfig.ServableVersionPolicy.Specific.Builder
Serve a specific version (or set of versions).
Protobuf type
tensorflow.FloatListProtobuf type
tensorflow.FloatList
Wrapper message for `float`.
Wrapper message for `float`.
Highly experimental and very likely to change.
Highly experimental and very likely to change.
LINT.IfChange
Experimental.
A function can be instantiated when the runtime can bind every attr
with a value.
Attributes for function arguments.
Attributes for function arguments.
A function can be instantiated when the runtime can bind every attr
with a value.
A library is a set of named functions.
A library is a set of named functions.
Protobuf type
tensorflow.serving.GetModelMetadataRequestProtobuf type
tensorflow.serving.GetModelMetadataRequestProtobuf type
tensorflow.serving.GetModelMetadataResponseProtobuf type
tensorflow.serving.GetModelMetadataResponse
Message returned for "signature_def" field.
Message returned for "signature_def" field.
GetModelStatusRequest contains a ModelSpec indicating the model for which
to get status.
GetModelStatusRequest contains a ModelSpec indicating the model for which
to get status.
Response for ModelStatusRequest on successful run.
Response for ModelStatusRequest on successful run.
Version number, state, and status for a single version of a model.
Version number, state, and status for a single version of a model.
States that map to ManagerState enum in
tensorflow_serving/core/servable_state.h
Protobuf type
tensorflow.GPUOptionsProtobuf type
tensorflow.GPUOptionsProtobuf type
tensorflow.GPUOptions.ExperimentalProtobuf type
tensorflow.GPUOptions.Experimental
Whether to merge data transfer streams into the compute stream in the
same stream group.
Whether to merge data transfer streams into the compute stream in the
same stream group.
Configuration for breaking down a visible GPU into multiple "virtual"
devices.
Configuration for breaking down a visible GPU into multiple "virtual"
devices.
GradientDef defines the gradient function of a function defined in
a function library.
GradientDef defines the gradient function of a function defined in
a function library.
Protobuf type
tensorflow.GraphDebugInfoProtobuf type
tensorflow.GraphDebugInfo
This represents a file/line location in the source code.
This represents a file/line location in the source code.
This represents a stack trace which is a ordered list of `FileLineCol`.
This represents a stack trace which is a ordered list of `FileLineCol`.
Represents the graph of operations
Represents the graph of operations
Protobuf type
tensorflow.GraphOptionsProtobuf type
tensorflow.GraphOptions
Inference result, matches the type of request or is an error.
Inference result, matches the type of request or is an error.
Inference request such as classification, regression, etc...
Inference request such as classification, regression, etc...
Inference request containing one or more requests.
Inference request containing one or more requests.
Inference request containing one or more responses.
Inference request containing one or more responses.
Specifies one or more fully independent input Examples.
Specifies one or more fully independent input Examples.
Specifies one or more independent input Examples, with a common context
Example.
Specifies one or more independent input Examples, with a common context
Example.
Protobuf type
tensorflow.serving.InputProtobuf type
tensorflow.serving.Input
Wrapper message for `int32`.
Wrapper message for `int32`.
Protobuf type
tensorflow.Int64ListProtobuf type
tensorflow.Int64List
Wrapper message for `int64`.
Wrapper message for `int64`.
Defines a single job in a TensorFlow cluster.
Defines a single job in a TensorFlow cluster.
Protobuf type
tensorflow.serving.LogCollectorConfigProtobuf type
tensorflow.serving.LogCollectorConfig
Metadata logged along with the request logs.
Metadata logged along with the request logs.
Configuration for logging query/responses.
Configuration for logging query/responses.
Protobuf type
tensorflow.serving.SamplingConfig
Attributes of requests that can be optionally sampled.
Protobuf type
tensorflow.serving.SamplingConfig
For memory tracking.
For memory tracking.
Protocol buffer containing the following which are necessary to restart
training, run inference.
Protocol buffer containing the following which are necessary to restart
training, run inference.
Meta information regarding the graph to be exported.
Meta information regarding the graph to be exported.
Metadata for an inference request such as the model name and version.
Metadata for an inference request such as the model name and version.
Protobuf type
tensorflow.serving.MetricProtobuf type
tensorflow.serving.MetricProtobuf type
tensorflow.serving.ReloadConfigRequestProtobuf type
tensorflow.serving.ReloadConfigRequestProtobuf type
tensorflow.serving.ReloadConfigResponseProtobuf type
tensorflow.serving.ReloadConfigResponse
Common configuration for loading a model being served.
Common configuration for loading a model being served.
Static list of models to be loaded for serving.
Static list of models to be loaded for serving.
ModelServer config.
ModelServer config.
The type of model.
ModelService provides methods to query and update the state of the server,
e.g. which models/versions are being served.
ModelService provides methods to query and update the state of the server,
e.g. which models/versions are being served.
A stub to allow clients to do limited synchronous rpc calls to service ModelService.
A stub to allow clients to do synchronous rpc calls to service ModelService.
A stub to allow clients to do ListenableFuture-style rpc calls to service ModelService.
Base class for the server implementation of the service ModelService.
A stub to allow clients to do asynchronous rpc calls to service ModelService.
Configuration for monitoring.
Configuration for monitoring.
Configuration for Prometheus monitoring.
Configuration for Prometheus monitoring.
A list of attr names and their values.
A list of attr names and their values.
A pair of tensor name and tensor values.
A pair of tensor name and tensor values.
Protobuf type
tensorflow.NodeDefProtobuf type
tensorflow.NodeDefProtobuf type
tensorflow.NodeDef.ExperimentalDebugInfoProtobuf type
tensorflow.NodeDef.ExperimentalDebugInfo
Time/size stats recorded for a single execution of a graph node.
Time/size stats recorded for a single execution of a graph node.
Output sizes recorded for a single execution of a graph node.
Output sizes recorded for a single execution of a graph node.
Defines an operation.
For describing inputs and outputs.
For describing inputs and outputs.
Description of the graph-construction-time configuration of this
Op.
Description of the graph-construction-time configuration of this
Op.
Defines an operation.
Information about version-dependent deprecation of an op
Information about version-dependent deprecation of an op
A collection of OpDefs
A collection of OpDefs
Options passed to the graph optimizer
Options passed to the graph optimizer
Control the use of the compiler/jit.
Optimization level
Configuration for a servable platform e.g. tensorflow or other ML systems.
Configuration for a servable platform e.g. tensorflow or other ML systems.
Protobuf type
tensorflow.serving.PlatformConfigMapProtobuf type
tensorflow.serving.PlatformConfigMap
PredictRequest specifies which TensorFlow model to run, as well as
how inputs are mapped to tensors and how outputs are filtered before
returning to user.
PredictRequest specifies which TensorFlow model to run, as well as
how inputs are mapped to tensors and how outputs are filtered before
returning to user.
Options for PredictRequest.
Options for PredictRequest.
Deterministic mode for the request.
Response for PredictRequest on successful run.
Response for PredictRequest on successful run.
Options only used for streaming requests that control how inputs/ouputs are
handled in the stream.
Options only used for streaming requests that control how inputs/ouputs are
handled in the stream.
Protobuf enum
tensorflow.serving.PredictStreamedOptions.RequestStateProtobuf type
tensorflow.serving.ClassifyLogProtobuf type
tensorflow.serving.ClassifyLogProtobuf type
tensorflow.serving.MultiInferenceLogProtobuf type
tensorflow.serving.MultiInferenceLog
Logged model inference request.
Logged model inference request.
Protobuf type
tensorflow.serving.PredictLogProtobuf type
tensorflow.serving.PredictLogProtobuf type
tensorflow.serving.PredictStreamedLogProtobuf type
tensorflow.serving.PredictStreamedLogProtobuf type
tensorflow.serving.RegressLogProtobuf type
tensorflow.serving.RegressLogProtobuf type
tensorflow.serving.SessionRunLogProtobuf type
tensorflow.serving.SessionRunLog
open source marker; do not remove
PredictionService provides access to machine-learned models loaded by
model_servers.
open source marker; do not remove
PredictionService provides access to machine-learned models loaded by
model_servers.
A stub to allow clients to do limited synchronous rpc calls to service PredictionService.
A stub to allow clients to do synchronous rpc calls to service PredictionService.
A stub to allow clients to do ListenableFuture-style rpc calls to service PredictionService.
Base class for the server implementation of the service PredictionService.
A stub to allow clients to do asynchronous rpc calls to service PredictionService.
RegisteredGradient stores a gradient function that is registered in the
gradients library and used in the ops of a function in the function library.
RegisteredGradient stores a gradient function that is registered in the
gradients library and used in the ops of a function in the function library.
Regression result for a single item (tensorflow.Example).
Regression result for a single item (tensorflow.Example).
Protobuf type
tensorflow.serving.RegressionRequestProtobuf type
tensorflow.serving.RegressionRequestProtobuf type
tensorflow.serving.RegressionResponseProtobuf type
tensorflow.serving.RegressionResponse
Contains one result per input example, in the same order as the input in
RegressionRequest.
Contains one result per input example, in the same order as the input in
RegressionRequest.
Protocol buffer representing a handle to a tensorflow resource.
Protocol buffer representing a handle to a tensorflow resource.
Protocol buffer representing a pair of (data type, tensor shape).
Protocol buffer representing a pair of (data type, tensor shape).
Graph rewriting is experimental and subject to change, not covered by any
API stability guarantees.
Graph rewriting is experimental and subject to change, not covered by any
API stability guarantees.
Enum for layout conversion between NCHW and NHWC on CPU.
Message to describe custom graph optimizer and its parameters
Message to describe custom graph optimizer and its parameters
Protobuf enum
tensorflow.RewriterConfig.MemOptType
Enum controlling the number of times to run optimizers.
Protobuf enum
tensorflow.RewriterConfig.Toggle
RPC options for distributed runtime.
RPC options for distributed runtime.
Metadata output (i.e., non-Tensor) for a single Run() call.
Metadata output (i.e., non-Tensor) for a single Run() call.
Protobuf type
tensorflow.RunMetadata.FunctionGraphsProtobuf type
tensorflow.RunMetadata.FunctionGraphs
Options for a single Run() call.
Options for a single Run() call.
Everything inside Experimental is subject to change and is not subject
to API stability guarantees in
https://www.tensorflow.org/guide/version_compat.
Everything inside Experimental is subject to change and is not subject
to API stability guarantees in
https://www.tensorflow.org/guide/version_compat.
Options for run handler thread pool.
Options for run handler thread pool.
TODO(pbar) Turn this into a TraceOptions proto which allows
tracing to be controlled in a more orthogonal manner?
Protobuf type
tensorflow.CapturedTensorProtobuf type
tensorflow.CapturedTensor
Represents `FunctionSpec` used in `Function`.
Represents `FunctionSpec` used in `Function`.
Whether the function should be compiled by XLA.
Protobuf type
tensorflow.SaveableObjectProtobuf type
tensorflow.SaveableObject
A SavedAsset points to an asset in the MetaGraph.
A SavedAsset points to an asset in the MetaGraph.
Protobuf type
tensorflow.SavedBareConcreteFunctionProtobuf type
tensorflow.SavedBareConcreteFunction
Stores low-level information about a concrete function.
Stores low-level information about a concrete function.
Protobuf type
tensorflow.SavedConstantProtobuf type
tensorflow.SavedConstant
A function with multiple signatures, possibly with non-Tensor arguments.
A function with multiple signatures, possibly with non-Tensor arguments.
Protobuf type
tensorflow.SavedObjectProtobuf type
tensorflow.SavedObjectProtobuf type
tensorflow.SavedObjectGraphProtobuf type
tensorflow.SavedObjectGraph
A SavedResource represents a TF object that holds state during its lifetime.
A SavedResource represents a TF object that holds state during its lifetime.
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.
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.
Represents a Variable that is initialized by loading the contents from the
checkpoint.
Represents a Variable that is initialized by loading the contents from the
checkpoint.
Protocol buffer representing the configuration of a Saver.
Protocol buffer representing the configuration of a Saver.
A version number that identifies a different on-disk checkpoint format.
Protobuf type
tensorflow.SaveSliceInfoDefProtobuf type
tensorflow.SaveSliceInfoDefProtobuf type
tensorflow.ScopedAllocatorOptionsProtobuf type
tensorflow.ScopedAllocatorOptionsProtobuf type
tensorflow.SequenceExampleProtobuf type
tensorflow.SequenceExample
Represents a serialized tf.dtypes.Dtype
Represents a serialized tf.dtypes.Dtype
Metadata about the session.
Metadata about the session.
SessionService defines a service with which a client can interact to execute
Tensorflow model inference.
SessionService defines a service with which a client can interact to execute
Tensorflow model inference.
A stub to allow clients to do limited synchronous rpc calls to service SessionService.
A stub to allow clients to do synchronous rpc calls to service SessionService.
A stub to allow clients to do ListenableFuture-style rpc calls to service SessionService.
Base class for the server implementation of the service SessionService.
A stub to allow clients to do asynchronous rpc calls to service SessionService.
Protobuf type
tensorflow.serving.SessionRunRequestProtobuf type
tensorflow.serving.SessionRunRequestProtobuf type
tensorflow.serving.SessionRunResponseProtobuf type
tensorflow.serving.SessionRunResponse
SignatureDef defines the signature of a computation supported by a TensorFlow
graph.
SignatureDef defines the signature of a computation supported by a TensorFlow
graph.
Configuration for a secure gRPC channel
Configuration for a secure gRPC channel
Status that corresponds to Status in
third_party/tensorflow/core/lib/core/status.h.
Status that corresponds to Status in
third_party/tensorflow/core/lib/core/status.h.
Protobuf type
tensorflow.StepStatsProtobuf type
tensorflow.StepStats
Wrapper message for `string`.
Wrapper message for `string`.
A protobuf to represent tf.BoundedTensorSpec.
A protobuf to represent tf.BoundedTensorSpec.
Represents a Python dict keyed by `str`.
Represents a Python dict keyed by `str`.
Represents a Python list.
Represents a Python list.
Represents Python's namedtuple.
Represents Python's namedtuple.
Represents None.
Represents None.
Represents a (key, value) pair.
Represents a (key, value) pair.
`StructuredValue` represents a dynamically typed value representing various
data structures that are inspired by Python data structures typically used in
TensorFlow functions as inputs and outputs.
`StructuredValue` represents a dynamically typed value representing various
data structures that are inspired by Python data structures typically used in
TensorFlow functions as inputs and outputs.
A protobuf to represent tf.TensorSpec.
A protobuf to represent tf.TensorSpec.
Represents a Python tuple.
Represents a Python tuple.
Represents a tf.TypeSpec
Represents a tf.TypeSpec
Protobuf enum
tensorflow.TypeSpecProto.TypeSpecClass
Defines a connection between two tensors in a `GraphDef`.
Defines a connection between two tensors in a `GraphDef`.
Protobuf type
tensorflow.TensorDescriptionProtobuf type
tensorflow.TensorDescriptionGenerated by camel build tools - do NOT edit this file!
Generated by camel build tools - do NOT edit this file!
Constants used in Camel TensorFlow Serving component.
Converter methods to convert from / to TensorFlow types.
Generated by camel build tools - do NOT edit this file!
Generated by camel build tools - do NOT edit this file!
Generated by camel build tools - do NOT edit this file!
Information about a Tensor necessary for feeding or retrieval.
Information about a Tensor necessary for feeding or retrieval.
Generic encoding for composite tensors.
Generic encoding for composite tensors.
For sparse tensors, The COO encoding stores a triple of values, indices,
and shape.
For sparse tensors, The COO encoding stores a triple of values, indices,
and shape.
Protocol buffer representing a tensor.
Protocol buffer representing a tensor.
Dimensions of a tensor.
Dimensions of a tensor.
One dimension of the tensor.
One dimension of the tensor.
Protobuf type
tensorflow.ThreadPoolOptionProtoProtobuf type
tensorflow.ThreadPoolOptionProtoGenerated by camel build tools - do NOT edit this file!
Protobuf type
tensorflow.RegisteredSaverProtobuf type
tensorflow.RegisteredSaverProtobuf type
tensorflow.TrackableObjectGraphProtobuf type
tensorflow.TrackableObjectGraphProtobuf type
tensorflow.TrackableObjectGraph.TrackableObjectProtobuf type
tensorflow.TrackableObjectGraph.TrackableObjectProtobuf type
tensorflow.TrackableObjectGraph.TrackableObject.ObjectReferenceProtobuf type
tensorflow.TrackableObjectGraph.TrackableObject.ObjectReferenceProtobuf type
tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensorProtobuf type
tensorflow.TrackableObjectGraph.TrackableObject.SerializedTensorProtobuf type
tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReferenceProtobuf type
tensorflow.TrackableObjectGraph.TrackableObject.SlotVariableReference
Wrapper message for `uint32`.
Wrapper message for `uint32`.
Wrapper message for `uint64`.
Wrapper message for `uint64`.
Indicates how a distributed variable will be aggregated.
Protocol buffer representing a Variable.
Protocol buffer representing a Variable.
Indicates when a distributed variable will be synced.
Protocol buffer representing the serialization format of DT_VARIANT tensors.
Protocol buffer representing the serialization format of DT_VARIANT tensors.
The config for graph verifiers.
The config for graph verifiers.
Protobuf enum
tensorflow.VerifierConfig.Toggle
Version information for a piece of serialized data
There are different types of versions for each type of data
(GraphDef, etc.), but they all have the same common shape
described here.
Version information for a piece of serialized data
There are different types of versions for each type of data
(GraphDef, etc.), but they all have the same common shape
described here.