Add docs

Author: jamjamjon

Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "usls"
 edition = "2021"
-version = "0.1.0-beta.4"
+version = "0.1.0-rc.1"
 rust-version = "1.82"
 description = "A Rust library integrated with ONNXRuntime, providing a collection of ML models."
 repository = "https://github.com/jamjamjon/usls"
@@ -10,6 +10,7 @@ license = "MIT"
 readme = "README.md"
 exclude = ["assets/*", "examples/*", "runs/*", "benches/*", "tests/*"]
 
+
 [dependencies]
 anyhow = { version = "1" }
 aksr = { version = "0.0.3" }
@@ -47,8 +48,6 @@ tokenizers = { version = "0.21.1" }
 paste = "1.0.15"
 base64ct = "=1.7.3"
 
-[build-dependencies]
-prost-build = "0.13.5"
 
 [dev-dependencies]
 argh = "0.1.13"

README.md

@@ -1,12 +1,11 @@
 use aksr::Builder;
 
 use crate::{
-    impl_ort_config_methods, impl_processor_config_methods,
     models::{SamKind, YOLOPredsFormat},
     ORTConfig, ProcessorConfig, Scale, Task, Version,
 };
 
-/// Config for building models and inference
+/// Configuration for model inference including engines, processors, and task settings.
 #[derive(Builder, Debug, Clone)]
 pub struct Config {
     // Basics

build.rs

@@ -550,9 +550,19 @@ trait DataLoaderIterator {
     }
 }
 
+/// An iterator implementation for `DataLoader` that enables batch processing of images.
+///
+/// This struct is created by the `into_iter` method on `DataLoader`.
+/// It provides functionality for:
+/// - Receiving batches of images through a channel
+/// - Tracking progress with an optional progress bar
+/// - Processing images in configurable batch sizes
 pub struct DataLoaderIntoIterator {
+    /// Channel receiver for getting batches of images
     receiver: mpsc::Receiver<Vec<Image>>,
+    /// Optional progress bar for tracking iteration progress
     progress_bar: Option<ProgressBar>,
+    /// Number of images to process in each batch
     batch_size: u64,
 }
 
@@ -593,6 +603,15 @@ impl IntoIterator for DataLoader {
     }
 }
 
+/// A borrowing iterator for `DataLoader` that enables batch processing of images.
+///
+/// This iterator is created by the `iter()` method on `DataLoader`, allowing iteration
+/// over batches of images without taking ownership of the `DataLoader`.
+///
+/// # Fields
+/// - `receiver`: A reference to the channel receiver that provides batches of images
+/// - `progress_bar`: An optional reference to a progress bar for tracking iteration progress
+/// - `batch_size`: The number of images to process in each batch
 pub struct DataLoaderIter<'a> {
     receiver: &'a mpsc::Receiver<Vec<Image>>,
     progress_bar: Option<&'a ProgressBar>,

src/utils/config.rs src/core/config.rssrc/utils/config.rs renamed to src/core/config.rs

@@ -1,4 +1,5 @@
 #[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
+/// Device types for model execution.
 pub enum Device {
     Cpu(usize),
     Cuda(usize),

src/io/dataloader.rs src/core/dataloader.rssrc/io/dataloader.rs renamed to src/core/dataloader.rs

@@ -1,4 +1,5 @@
 #[derive(Default, Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
+/// Data type enumeration for tensor elements.
 pub enum DType {
     #[default]
     Auto,

src/utils/device.rs src/core/device.rssrc/utils/device.rs renamed to src/core/device.rs

@@ -46,35 +46,53 @@ impl From<TensorElementType> for DType {
 }
 
 /// A struct for tensor attrs composed of the names, the dtypes, and the dimensions.
+/// ONNX Runtime tensor attributes containing names, data types, and dimensions.
 #[derive(Builder, Debug, Clone, Default)]
+/// ONNX Runtime tensor attributes containing metadata.
 pub struct OrtTensorAttr {
+    /// Tensor names.
     pub names: Vec<String>,
+    /// Tensor data types.
     pub dtypes: Vec<TensorElementType>,
+    /// Tensor dimensions for each tensor.
     pub dimss: Vec<Vec<usize>>,
 }
 
+/// ONNX I/O structure containing input/output attributes and session.
 #[derive(Debug)]
 pub struct OnnxIo {
+    /// Input tensor attributes.
     pub inputs: OrtTensorAttr,
+    /// Output tensor attributes.
     pub outputs: OrtTensorAttr,
+    /// ONNX Runtime session.
     pub session: Session,
+    /// ONNX model protocol buffer.
     pub proto: onnx::ModelProto,
 }
 
+/// ONNX Runtime inference engine with configuration and session management.
 #[derive(Debug, Builder)]
 pub struct Engine {
+    /// Model file path.
     pub file: String,
+    /// Model specification string.
     pub spec: String,
+    /// Execution device.
     pub device: Device,
     #[args(inc)]
     pub iiixs: Vec<Iiix>,
     #[args(aka = "parameters")]
     pub params: Option<usize>,
     #[args(aka = "memory")]
     pub wbmems: Option<usize>,
+    /// Input min-opt-max configurations.
     pub inputs_minoptmax: Vec<Vec<MinOptMax>>,
+    /// ONNX I/O structure.
     pub onnx: Option<OnnxIo>,
+    /// Timing statistics.
     pub ts: Ts,
+    /// Number of dry runs for warmup.
     pub num_dry_run: usize,
 
     // global
@@ -158,7 +176,7 @@ impl Default for Engine {
             // cann
             cann_graph_inference: true,
             cann_dump_graphs: false,
-            cann_dump_om_model: false,
+            cann_dump_om_model: true,
             // nnapi
             nnapi_cpu_only: false,
             nnapi_disable_cpu: false,