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.
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.
Classification inputs.
Classification method name used in a SignatureDef.
Classification classes output.
Classification scores output.
Key in the signature def map for default serving signatures. The default signature is used in inference requests where a specific signature was not specified.
Predict inputs.
Prediction method name used in a SignatureDef.
Predict outputs.
Regression inputs.
Regression method name used in a SignatureDef.
Regression outputs.
A Rust type that maps to a DataType.
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.
Deprecated alias for FetchToken.
Convenience type for Result with Status as the error type.
Deprecated alias for SessionRunArgs.
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