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.
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 https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/bfloat16.h for details.
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.
ImportGraphDefResults holds results that are generated by Graph::import_graph_def_with_results().
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.
Iterator over the operations in a
Names a specific Output in the graph.
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.
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
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 method name used in a SignatureDef.
Classification classes output.
Classification scores output.
Key in the signature def map for
Prediction method name used in a SignatureDef.
Regression method name used in a SignatureDef.
A Rust type that maps to a
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
Returns a string describing version information of the
Deprecated alias for FetchToken.
Convenience type for
Deprecated alias for SessionRunArgs.