Crate tfrecord[−][src]
The crate provides the functionality to serialize and deserialize TFRecord data format from TensorFlow.
The crate provides several cargo features that you can conditionally compile modules.
Optional features:
full
: Enable all features.async_
: Enable async/await feature.dataset
: Enable the dataset API.summary
: Enable the summary and event API, which is mainly targeted for TensorBoard.
Third-party supports:
Re-exports
pub use error::Error; |
pub use markers::GenericRecord; |
pub use markers::HistogramProtoElement; |
pub use markers::TensorProtoElement; |
pub use protos::Event; |
pub use protos::Example as RawExample; |
pub use protos::Summary; |
pub use reader::BytesReader; |
pub use reader::EventReader; |
pub use reader::ExampleReader; |
pub use reader::RawExampleReader; |
pub use types::Example; |
pub use types::Feature; |
pub use writer::BytesWriter; |
pub use writer::ExampleWriter; |
pub use writer::RawExampleWriter; |
pub use writer::RecordWriter; |
pub use writer::RecordWriterInit; |
pub use dataset::Dataset; |
pub use dataset::DatasetInit; |
Modules
dataset | The dataset API that accesses multiple TFRecord files. |
error | Error types and error handling utilities. |
io | Low level synchronous and asynchronous I/O functions. |
markers | Marker traits. |
protos | ProtocolBuffer types compiled from TensorFlow. |
reader | Reading TFRecord data format. |
summary | Types of summaries and events and writers for TensorBoard. |
types | High level example, feature and many other types. |
writer | Writing TFRecord data format. |
Structs
EventInit | A Event initializer. |
EventWriter | The event writer type. |
EventWriterInit | The event writer initializer. |
Histogram | Concurrent histogram data structure. |
RecordReader | The generic reader type. |
RecordReaderInit | The reader initializer. |
RecordStreamInit | The stream initializer. |
SummaryInit | A Summary initializer. |