Update docs (#2553)

* add module docs for candle-core

* doc each of the candle-nn modules and add the links to the doc page

candle-core/src/lib.rs

@@ -32,6 +32,20 @@
 //! Python can really add overhead in more complex workflows and the [GIL](https://www.backblaze.com/blog/the-python-gil-past-present-and-future/) is a notorious source of headaches.
 //!
 //! Rust is cool, and a lot of the HF ecosystem already has Rust crates [safetensors](https://github.com/huggingface/safetensors) and [tokenizers](https://github.com/huggingface/tokenizers)
+//!
+//! ## Other Crates
+//!
+//! Candle consists of a number of crates. This crate holds core the common data structures but you may wish
+//! to look at the docs for the other crates which can be found here:
+//!
+//! - [candle-core](https://docs.rs/candle-core/). Core Datastructures and DataTypes.
+//! - [candle-nn](https://docs.rs/candle-nn/). Building blocks for Neural Nets.
+//! - [candle-datasets](https://docs.rs/candle-datasets/). Rust access to commonly used Datasets like MNIST.
+//! - [candle-examples](https://docs.rs/candle-examples/). Examples of Candle in Use.
+//! - [candle-onnx](https://docs.rs/candle-onnx/). Loading and using ONNX models.
+//! - [candle-pyo3](https://docs.rs/candle-pyo3/). Access to Candle from Python.
+//! - [candle-transformers](https://docs.rs/candle-transformers/). Candle implemntation of many published transformer models.
+//!
 
 #[cfg(feature = "accelerate")]
 mod accelerate;

candle-nn/src/activation.rs

@@ -1,3 +1,5 @@
+//! Activation Functions
+//!
 use candle::{Result, Tensor};
 use serde::Deserialize;
 

candle-nn/src/kv_cache.rs

@@ -1,3 +1,5 @@
+//! Cache Implementations
+//!
 use candle::{Device, Result, Tensor};
 
 #[derive(Debug, Clone)]

candle-nn/src/lib.rs

@@ -1,3 +1,20 @@
+//! candle-nn
+//!
+//! ## Other Crates
+//!
+//! Candle consists of a number of crates. This crate holds structs and functions
+//! that allow you to build and train neural nets. You may wish
+//! to look at the docs for the other crates which can be found here:
+//!
+//! - [candle-core](https://docs.rs/candle-core/). Core Datastructures and DataTypes.
+//! - [candle-nn](https://docs.rs/candle-nn/). Building blocks for Neural Nets.
+//! - [candle-datasets](https://docs.rs/candle-datasets/). Rust access to commonly used Datasets like MNIST.
+//! - [candle-examples](https://docs.rs/candle-examples/). Examples of Candle in Use.
+//! - [candle-onnx](https://docs.rs/candle-onnx/). Loading and using ONNX models.
+//! - [candle-pyo3](https://docs.rs/candle-pyo3/). Access to Candle from Python.
+//! - [candle-transformers](https://docs.rs/candle-transformers/). Candle implemntation of many published transformer models.
+//!
+
 pub mod activation;
 pub mod batch_norm;
 pub mod conv;

candle-nn/src/loss.rs

@@ -1,3 +1,5 @@
+//! Loss Calculations
+//!
 use candle::{Result, Tensor};
 
 /// The negative log likelihood loss.

candle-nn/src/ops.rs

@@ -1,3 +1,6 @@
+//! Tensor ops.
+//!
+
 use candle::{CpuStorage, DType, Layout, Module, Result, Shape, Tensor, D};
 use rayon::prelude::*;
 

candle-nn/src/rotary_emb.rs

@@ -1,3 +1,5 @@
+//! Rotary Embeddings
+//!
 use candle::{CpuStorage, Layout, Result, Shape, Tensor, D};
 use rayon::prelude::*;
 

candle-nn/src/sequential.rs

@@ -1,3 +1,5 @@
+//! Sequential Layer
+//!
 //! A sequential layer used to chain multiple layers and closures.
 use candle::{Module, Result, Tensor};
 

candle-nn/src/var_builder.rs

@@ -1,3 +1,5 @@
+//! A `VarBuilder` for variable retrieval from models
+//!
 //! A `VarBuilder` is used to retrieve variables used by a model. These variables can either come
 //! from a pre-trained checkpoint, e.g. using `VarBuilder::from_mmaped_safetensors`, or initialized
 //! for training, e.g. using `VarBuilder::from_varmap`.

candle-nn/src/var_map.rs

@@ -1,3 +1,5 @@
+//! A `VarMap` is a store that holds named variables.
+//!
 use candle::{DType, Device, Result, Shape, Tensor, Var};
 use std::collections::HashMap;
 use std::sync::{Arc, Mutex};