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Posted to commits@teaclave.apache.org by hs...@apache.org on 2023/06/08 07:30:40 UTC
[incubator-teaclave-sgx-sdk] branch v2.0.0-preview updated: Remove cargo doc warnings
This is an automated email from the ASF dual-hosted git repository.
hsun pushed a commit to branch v2.0.0-preview
in repository https://gitbox.apache.org/repos/asf/incubator-teaclave-sgx-sdk.git
The following commit(s) were added to refs/heads/v2.0.0-preview by this push:
new 0eef86cc Remove cargo doc warnings
0eef86cc is described below
commit 0eef86cc85d30f719cbecc56051b3cb40bbe911e
Author: sunhe05 <su...@baidu.com>
AuthorDate: Thu Jun 8 07:30:16 2023 +0000
Remove cargo doc warnings
---
sgx_rand/src/chacha.rs | 4 ++--
sgx_rand/src/distributions/exponential.rs | 4 ++--
sgx_rand/src/distributions/gamma.rs | 6 +++---
sgx_rand/src/distributions/normal.rs | 4 ++--
sgx_rand/src/isaac.rs | 8 ++++----
sgx_rand/src/lib.rs | 8 ++++----
6 files changed, 17 insertions(+), 17 deletions(-)
diff --git a/sgx_rand/src/chacha.rs b/sgx_rand/src/chacha.rs
index 157bb3db..8c86b4fa 100644
--- a/sgx_rand/src/chacha.rs
+++ b/sgx_rand/src/chacha.rs
@@ -24,14 +24,14 @@ const KEY_WORDS: usize = 8; // 8 words for the 256-bit key
const STATE_WORDS: usize = 16;
const CHACHA_ROUNDS: u32 = 20; // Cryptographically secure from 8 upwards as of this writing
-/// A random number generator that uses the ChaCha20 algorithm [1].
+/// A random number generator that uses the ChaCha20 algorithm \[1\].
///
/// The ChaCha algorithm is widely accepted as suitable for
/// cryptographic purposes, but this implementation has not been
/// verified as such. Prefer a generator like `OsRng` that defers to
/// the operating system for cases that need high security.
///
-/// [1]: D. J. Bernstein, [*ChaCha, a variant of
+/// \[1\]: D. J. Bernstein, [*ChaCha, a variant of
/// Salsa20*](http://cr.yp.to/chacha.html)
#[derive(Copy, Clone, Debug)]
pub struct ChaChaRng {
diff --git a/sgx_rand/src/distributions/exponential.rs b/sgx_rand/src/distributions/exponential.rs
index 219f959a..cccffaac 100644
--- a/sgx_rand/src/distributions/exponential.rs
+++ b/sgx_rand/src/distributions/exponential.rs
@@ -24,11 +24,11 @@ use crate::{Rand, Rng};
///
/// See `Exp` for the general exponential distribution.
///
-/// Implemented via the ZIGNOR variant[1] of the Ziggurat method. The
+/// Implemented via the ZIGNOR variant\[1\] of the Ziggurat method. The
/// exact description in the paper was adjusted to use tables for the
/// exponential distribution rather than normal.
///
-/// [1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
+/// \[1\]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
/// Generate Normal Random
/// Samples*](http://www.doornik.com/research/ziggurat.pdf). Nuffield
/// College, Oxford
diff --git a/sgx_rand/src/distributions/gamma.rs b/sgx_rand/src/distributions/gamma.rs
index a3df4cf0..07d0a810 100644
--- a/sgx_rand/src/distributions/gamma.rs
+++ b/sgx_rand/src/distributions/gamma.rs
@@ -35,9 +35,9 @@ use crate::{Open01, Rng};
/// where `Γ` is the Gamma function, `k` is the shape and `θ` is the
/// scale and both `k` and `θ` are strictly positive.
///
-/// The algorithm used is that described by Marsaglia & Tsang 2000[1],
+/// The algorithm used is that described by Marsaglia & Tsang 2000\[1\],
/// falling back to directly sampling from an Exponential for `shape
-/// == 1`, and using the boosting technique described in [1] for
+/// == 1`, and using the boosting technique described in \[1\] for
/// `shape < 1`.
///
/// # Example
@@ -50,7 +50,7 @@ use crate::{Open01, Rng};
/// println!("{} is from a Gamma(2, 5) distribution", v);
/// ```
///
-/// [1]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple Method
+/// \[1\]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple Method
/// for Generating Gamma Variables" *ACM Trans. Math. Softw.* 26, 3
/// (September 2000),
/// 363-372. DOI:[10.1145/358407.358414](http://doi.acm.org/10.1145/358407.358414)
diff --git a/sgx_rand/src/distributions/normal.rs b/sgx_rand/src/distributions/normal.rs
index 443a6764..a61f18e4 100644
--- a/sgx_rand/src/distributions/normal.rs
+++ b/sgx_rand/src/distributions/normal.rs
@@ -24,9 +24,9 @@ use crate::{Open01, Rand, Rng};
///
/// See `Normal` for the general normal distribution.
///
-/// Implemented via the ZIGNOR variant[1] of the Ziggurat method.
+/// Implemented via the ZIGNOR variant\[1\] of the Ziggurat method.
///
-/// [1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
+/// \[1\]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method to
/// Generate Normal Random
/// Samples*](http://www.doornik.com/research/ziggurat.pdf). Nuffield
/// College, Oxford
diff --git a/sgx_rand/src/isaac.rs b/sgx_rand/src/isaac.rs
index b25c40ac..0ca7194e 100644
--- a/sgx_rand/src/isaac.rs
+++ b/sgx_rand/src/isaac.rs
@@ -30,14 +30,14 @@ const RAND_SIZE_LEN: usize = 8;
const RAND_SIZE: u32 = 1 << RAND_SIZE_LEN;
const RAND_SIZE_USIZE: usize = 1 << RAND_SIZE_LEN;
-/// A random number generator that uses the ISAAC algorithm[1].
+/// A random number generator that uses the ISAAC algorithm\[1\].
///
/// The ISAAC algorithm is generally accepted as suitable for
/// cryptographic purposes, but this implementation has not be
/// verified as such. Prefer a generator like `OsRng` that defers to
/// the operating system for cases that need high security.
///
-/// [1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number
+/// \[1\]: Bob Jenkins, [*ISAAC: A fast cryptographic random number
/// generator*](http://www.burtleburtle.net/bob/rand/isaacafa.html)
#[derive(Copy)]
pub struct IsaacRng {
@@ -309,7 +309,7 @@ impl fmt::Debug for IsaacRng {
const RAND_SIZE_64_LEN: usize = 8;
const RAND_SIZE_64: usize = 1 << RAND_SIZE_64_LEN;
-/// A random number generator that uses ISAAC-64[1], the 64-bit
+/// A random number generator that uses ISAAC-64\[1\], the 64-bit
/// variant of the ISAAC algorithm.
///
/// The ISAAC algorithm is generally accepted as suitable for
@@ -317,7 +317,7 @@ const RAND_SIZE_64: usize = 1 << RAND_SIZE_64_LEN;
/// verified as such. Prefer a generator like `OsRng` that defers to
/// the operating system for cases that need high security.
///
-/// [1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number
+/// \[1\]: Bob Jenkins, [*ISAAC: A fast cryptographic random number
/// generator*](http://www.burtleburtle.net/bob/rand/isaacafa.html)
#[derive(Copy)]
pub struct Isaac64Rng {
diff --git a/sgx_rand/src/lib.rs b/sgx_rand/src/lib.rs
index 462c5ff9..9ed62063 100644
--- a/sgx_rand/src/lib.rs
+++ b/sgx_rand/src/lib.rs
@@ -144,8 +144,8 @@ pub trait Rng {
/// See:
/// A PRNG specialized in double precision floating point numbers using
/// an affine transition
- /// http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/ARTICLES/dSFMT.pdf
- /// http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/dSFMT-slide-e.pdf
+ /// <http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/ARTICLES/dSFMT.pdf>
+ /// <http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/dSFMT-slide-e.pdf>
///
/// By default this is implemented in terms of `next_u32`, but a
/// random number generator which can generate numbers satisfying
@@ -535,14 +535,14 @@ pub trait SeedableRng<Seed>: Rng {
fn from_seed(seed: Seed) -> Self;
}
-/// An Xorshift[1] random number
+/// An Xorshift\[1\] random number
/// generator.
///
/// The Xorshift algorithm is not suitable for cryptographic purposes
/// but is very fast. If you do not know for sure that it fits your
/// requirements, use a more secure one such as `IsaacRng` or `RdRand`.
///
-/// [1]: Marsaglia, George (July 2003). ["Xorshift
+/// \[1\]: Marsaglia, George (July 2003). ["Xorshift
/// RNGs"](http://www.jstatsoft.org/v08/i14/paper). *Journal of
/// Statistical Software*. Vol. 8 (Issue 14).
#[allow(missing_copy_implementations)]
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