Uses of Package
org.tensorflow.framework
Packages that use org.tensorflow.framework
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Classes in org.tensorflow.framework used by org.tensorflow.frameworkClassDescriptionProtobuf type
tensorflow.AllocationDescriptionProtobuf typetensorflow.AllocationDescriptionAn allocation/de-allocation operation performed by the allocator.An allocation/de-allocation operation performed by the allocator.Protobuf typetensorflow.AllocatorMemoryUsedProtobuf typetensorflow.AllocatorMemoryUsedAn 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.IfChangeLINT.IfChangeProtobuf typetensorflow.AutoParallelOptionsProtobuf typetensorflow.AutoParallelOptionsProtobuf typetensorflow.BatchingOptionsProtobuf typetensorflow.BatchingOptionsDefines 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.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.Protobuf typetensorflow.CostGraphDefTotal cost of this graph, typically used for balancing decisions.Total cost of this graph, typically used for balancing decisions.Protobuf typetensorflow.CostGraphDefProtobuf typetensorflow.CostGraphDef.NodeProtobuf typetensorflow.CostGraphDef.NodeInputs of this node.Inputs of this node.Outputs of this node.Outputs of this node.(== suppress_warning documentation-presence ==) LINT.IfChangeProtobuf typetensorflow.DebuggedSourceFileProtobuf typetensorflow.DebuggedSourceFileProtobuf typetensorflow.DebuggedSourceFilesProtobuf typetensorflow.DebuggedSourceFilesOptions 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 typetensorflow.DeviceStepStatsProtobuf typetensorflow.DeviceStepStatsHighly 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 typetensorflow.GPUOptionsProtobuf typetensorflow.GPUOptionsProtobuf typetensorflow.GPUOptions.ExperimentalProtobuf typetensorflow.GPUOptions.ExperimentalWhether 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 typetensorflow.GraphDebugInfoProtobuf typetensorflow.GraphDebugInfoThis 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 operationsRepresents the graph of operationsProtobuf typetensorflow.GraphOptionsProtobuf typetensorflow.GraphOptionsFor 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.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 typetensorflow.NodeDefProtobuf typetensorflow.NodeDefProtobuf typetensorflow.NodeDef.ExperimentalDebugInfoProtobuf typetensorflow.NodeDef.ExperimentalDebugInfoTime/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 opInformation about version-dependent deprecation of an opA collection of OpDefsA collection of OpDefsOptions passed to the graph optimizerOptions passed to the graph optimizerControl the use of the compiler/jit.Optimization levelRegisteredGradient 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.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 parametersMessage to describe custom graph optimizer and its parametersProtobuf enumtensorflow.RewriterConfig.MemOptTypeEnum controlling the number of times to run optimizers.Protobuf enumtensorflow.RewriterConfig.ToggleMetadata output (i.e., non-Tensor) for a single Run() call.Metadata output (i.e., non-Tensor) for a single Run() call.Protobuf typetensorflow.RunMetadata.FunctionGraphsProtobuf typetensorflow.RunMetadata.FunctionGraphsOptions 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 typetensorflow.SaveSliceInfoDefProtobuf typetensorflow.SaveSliceInfoDefProtobuf typetensorflow.ScopedAllocatorOptionsProtobuf typetensorflow.ScopedAllocatorOptionsRepresents a serialized tf.dtypes.DtypeRepresents a serialized tf.dtypes.DtypeMetadata about the session.Metadata about the session.SignatureDef defines the signature of a computation supported by a TensorFlow graph.SignatureDef defines the signature of a computation supported by a TensorFlow graph.Protobuf typetensorflow.StepStatsProtobuf typetensorflow.StepStatsDefines a connection between two tensors in a `GraphDef`.Defines a connection between two tensors in a `GraphDef`.Protobuf typetensorflow.TensorDescriptionProtobuf typetensorflow.TensorDescriptionInformation 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 typetensorflow.ThreadPoolOptionProtoProtobuf typetensorflow.ThreadPoolOptionProtoIndicates 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 enumtensorflow.VerifierConfig.ToggleVersion 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. -
Classes in org.tensorflow.framework used by tensorflowClassDescription(== suppress_warning documentation-presence ==) LINT.IfChangeProtocol buffer representing a tensor.Protocol buffer representing a tensor.Dimensions of a tensor.Dimensions of a tensor.Indicates how a distributed variable will be aggregated.Indicates when a distributed variable will be synced.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.
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Classes in org.tensorflow.framework used by tensorflow.servingClassDescriptionThe canonical error codes for TensorFlow APIs.A pair of tensor name and tensor values.A pair of tensor name and tensor values.Metadata output (i.e., non-Tensor) for a single Run() call.Metadata output (i.e., non-Tensor) for a single Run() call.Options for a single Run() call.Options for a single Run() call.SignatureDef defines the signature of a computation supported by a TensorFlow graph.SignatureDef defines the signature of a computation supported by a TensorFlow graph.Protocol buffer representing a tensor.Protocol buffer representing a tensor.