Crate tensorflow

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This crate provides Rust bindings for the TensorFlow machine learning library.

If you aren’t sure how to use something, please see the examples folder.

Modules

  • eager
    C API extensions to experiment with eager execution of kernels.
  • expr
    This module builds computation graphs.
  • io
    A module for reading and writing TFRecords, Tensorflow’s preferred on-disk data format.
  • ops
    This module exposes functions for building standard operations.
  • train
    This module supports building and training models.

Structs

  • AttrMetadata
    AttrMetadata describes the value of an attribute on an operation.
  • BFloat16
    BFloat16 provides a Rust type for BFloat16. Note that this is not the same as half::f16. BFloat16 is not an IEEE-754 16-bit float. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/bfloat16.h for details.
  • CheckpointMaker
    This struct supports saving and restoring variables using Tensorflow checkpoints in SaveV2 format. First, the user creates a CheckpointMaker attached to an Scope indicating the list of variables to be saved/restored. The CheckpointMaker lazily modifies the graph creating the nodes needed for saving/restoring. When one wants to save/restore from or into a session, one calls the save/restore methods
  • Device
    Metadata about a device.
  • FetchToken
    An opaque token for retrieving an output from a computation.
  • Function
    Function is a grouping of operations with defined inputs and outputs. Once created and added to graphs, functions can be invoked by creating an operation whose operation type matches the function name.
  • FunctionOptions
    Options that can be passed during function creation.
  • Graph
    Represents a computation graph. Graphs may be shared between sessions. Graphs are thread-safe when used as directed.
  • ImportGraphDefOptions
    ImportGraphDefOptions holds options that can be passed to Graph::import_graph_def.
  • ImportGraphDefResults
    ImportGraphDefResults holds results that are generated by Graph::import_graph_def_with_results().
  • Input
    A Input is one end of a graph edge. It holds an operation and an index into the inputs of that operation.
  • Library
    Dynamically loaded plugins. The C API doesn’t provide a way to unload libraries, so nothing happens when this goes out of scope.
  • MetaGraphDef
    Contains data necessary to restart training, run inference. It can be used to serialize/de-serialize memory objects necessary for running computation in a graph when crossing the process boundary. It can be used for long term storage of graphs, cross-language execution of graphs, etc.
  • OpArgDef
    An argument definition for a graph operation.
  • OpAttrDef
    An attribute definition for a graph operation.
  • OpDef
    A Graph operation exposed from an external plugin
  • OpList
    Collection of OpDefs exposed from an external plugin
  • Operation
    An Operation is a node in a Graph. It is a computation which accepts inputs and produces outputs.
  • OperationDescription
    An OperationDescription is an Operation in the process of being built (i.e. the builder pattern).
  • OperationIter
    Iterator over the operations in a Graph.
  • Output
    A Output is one end of a graph edge. It holds an operation and an index into the outputs of that operation.
  • OutputName
    Names a specific Output in the graph.
  • PluggableDeviceLibrary
    PluggableDeviceLibrary handler.
  • QInt8
    Quantized type for i8.
  • QInt16
    Quantized type for i16.
  • QInt32
    Quantized type for i32.
  • QUInt8
    Quantized type for u8.
  • QUInt16
    Quantized type for u16.
  • SaveModelError
    Error generated while saving a model.
  • SavedModelBuilder
    Builds a SavedModelSaver, which can be used to save models.
  • SavedModelBundle
    Aggregation type for a saved model bundle.
  • SavedModelSaver
    Creates saved models. Use a SavedModelBuilder to create a SavedModelSaver.
  • Scope
    A Scope object represents a set of related TensorFlow ops that have the same properties such as a common name prefix.
  • Session
    Manages a single graph and execution.
  • SessionOptions
    Options that can be passed during session creation.
  • SessionRunArgs
    Manages the inputs and outputs for a single execution of a graph.
  • Shape
    A Shape is the shape of a tensor. A Shape may be an unknown rank, or it may have a known rank with each dimension being known or unknown.
  • SignatureDef
    SignatureDef defines the signature of a computation supported by a TensorFlow graph.
  • Status
    Holds error information when communicating with back and forth with tensorflow.
  • Tensor
    Holds a multi-dimensional array of elements of a single data type.
  • TensorInfo
    Information about a Tensor necessary for feeding or retrieval.
  • Variable
    Holds state in the form of a tensor that persists across steps.
  • VariableBuilder
    Builds a Variable.
  • WhileBuilder
    A WhileBuilder is used to build a while loop.

Enums

  • AttrType
    Describes the type of the value of an attribute on an operation.
  • Code
    Error values that can be returned.
  • DataType
    Type of a single tensor element.

Constants

Traits

Functions

  • get_all_registered_kernels
    Returns a serialized KernelList protocol buffer containing KernelDefs for all registered kernels.
  • get_registered_kernels_for_op
    Returns a serialized KernelList protocol buffer containing KernelDefs for all kernels registered for the operation named name.
  • version
    Returns a string describing version information of the TensorFlow library. TensorFlow is using semantic versioning.

Type Definitions

  • OutputTokenDeprecated
    Deprecated alias for FetchToken.
  • Result
    Convenience type for Result with Status as the error type.
  • StepWithGraphDeprecated
    Deprecated alias for SessionRunArgs.