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.


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


  • AttrMetadata describes the value of an attribute on an operation.
  • 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 for details.
  • 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
  • Metadata about a device.
  • An opaque token for retrieving an output from a computation.
  • 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.
  • Options that can be passed during function creation.
  • Represents a computation graph. Graphs may be shared between sessions. Graphs are thread-safe when used as directed.
  • ImportGraphDefOptions holds options that can be passed to Graph::import_graph_def.
  • ImportGraphDefResults holds results that are generated by Graph::import_graph_def_with_results().
  • A Input is one end of a graph edge. It holds an operation and an index into the inputs of that operation.
  • Dynamically loaded plugins. The C API doesn’t provide a way to unload libraries, so nothing happens when this goes out of scope.
  • 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.
  • An argument definition for a graph operation.
  • An attribute definition for a graph operation.
  • A Graph operation exposed from an external plugin
  • Collection of OpDefs exposed from an external plugin
  • An Operation is a node in a Graph. It is a computation which accepts inputs and produces outputs.
  • An OperationDescription is an Operation in the process of being built (i.e. the builder pattern).
  • Iterator over the operations in a Graph.
  • A Output is one end of a graph edge. It holds an operation and an index into the outputs of that operation.
  • Names a specific Output in the graph.
  • PluggableDeviceLibrary handler.
  • Quantized type for i8.
  • Quantized type for i16.
  • Quantized type for i32.
  • Quantized type for u8.
  • Quantized type for u16.
  • Error generated while saving a model.
  • Builds a SavedModelSaver, which can be used to save models.
  • Aggregation type for a saved model bundle.
  • Creates saved models. Use a SavedModelBuilder to create a SavedModelSaver.
  • A Scope object represents a set of related TensorFlow ops that have the same properties such as a common name prefix.
  • Manages a single graph and execution.
  • Options that can be passed during session creation.
  • Manages the inputs and outputs for a single execution of a graph.
  • 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 defines the signature of a computation supported by a TensorFlow graph.
  • Holds error information when communicating with back and forth with tensorflow.
  • Holds a multi-dimensional array of elements of a single data type.
  • Information about a Tensor necessary for feeding or retrieval.
  • Holds state in the form of a tensor that persists across steps.
  • Builds a Variable.
  • A WhileBuilder is used to build a while loop.


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




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

Type Definitions

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