1#![doc = include_str!("../README.md")]
2#![cfg_attr(docsrs, feature(doc_cfg))]
3#![allow(clippy::doc_markdown)]
4#![allow(clippy::missing_const_for_fn)]
5#![allow(clippy::missing_errors_doc)]
6#![allow(clippy::module_name_repetitions)]
7#![allow(clippy::must_use_candidate)]
8
9pub mod core;
11pub mod error;
13#[doc(hidden)]
14pub mod ffi;
15pub mod filters;
17mod generated;
18pub mod image;
20pub mod matrix;
22pub mod ndarray;
24pub mod neural;
26pub mod ray;
28pub mod state;
30
31pub use crate::core::{
32 device_options, hint_temporary_memory_high_water_mark, preferred_device,
33 set_heap_cache_duration, supports_mtl_device, CommandBuffer as MpsCommandBuffer, Predicate,
34 PreferredDevice,
35};
36pub use crate::error::{Error, Result};
37pub use crate::filters::{
38 HistogramInfo, ImageAdd, ImageBilinearScale, ImageBox, ImageConvolution, ImageGaussianBlur,
39 ImageHistogram, ImageLanczosScale, ImageMedian, ImageReduceRowMax, ImageReduceRowMean,
40 ImageReduceRowMin, ImageReduceRowSum, ImageScaleAndAdd, ImageSobel, ImageStatisticsMean,
41 ImageStatisticsMinAndMax, ImageThresholdBinary, ScaleTransform,
42};
43pub use crate::image::{
44 feature_channel_format, image_edge_mode, image_layout, kernel_options, Image, ImageDescriptor,
45 ImageReadWriteParams, ImageRegion,
46};
47pub use crate::matrix::{
48 data_type, data_type_size, Matrix, MatrixDescriptor, MatrixMultiplication,
49 MatrixMultiplicationDescriptor, Vector, VectorDescriptor,
50};
51pub use crate::ndarray::{
52 NDArray, NDArrayDescriptor, NDArrayIdentity, NDArrayMatrixMultiplication,
53};
54pub use crate::neural::{
55 cnn_accumulator_precision_option, cnn_convolution_flags, cnn_convolution_weights_layout,
56 nn_regularization_type, rnn_bidirectional_combine_mode, rnn_sequence_direction, CnnConvolution,
57 CnnConvolutionDescriptor, CnnConvolutionWeightsAndBiasesState, CnnNeuronReluNode,
58 CnnPoolingMaxNode, CnnSoftMaxNode, CnnUpsamplingNearestNode, GruDescriptor, LstmDescriptor,
59 NNGraph, NNImageNode, NNOptimizer, NNOptimizerAdam, NNOptimizerDescriptor, NNOptimizerRmsProp,
60 NNOptimizerStochasticGradientDescent, RnnDescriptor, RnnImageInferenceLayer,
61 RnnRecurrentImageState, RnnSingleGateDescriptor,
62};
63pub use crate::ray::{
64 acceleration_structure_status, acceleration_structure_usage, cull_mode, intersection_data_type,
65 intersection_type, polygon_type, ray_data_type, winding, PolygonAccelerationStructure,
66 RayIntersector, SVGF,
67};
68pub use crate::state::{
69 state_batch_increment_read_count, state_batch_resource_size, state_batch_synchronize,
70 state_resource_type, State, StateResourceList, StateTextureInfo,
71};