Replace SeedableRng impl for SmallRng with inherent fns

benches/generators.rs

@@ -50,7 +50,7 @@ gen_bytes!(gen_bytes_chacha12, ChaCha12Rng::from_entropy());
 gen_bytes!(gen_bytes_chacha20, ChaCha20Rng::from_entropy());
 gen_bytes!(gen_bytes_std, StdRng::from_entropy());
 #[cfg(feature = "small_rng")]
-gen_bytes!(gen_bytes_small, SmallRng::from_entropy());
+gen_bytes!(gen_bytes_small, SmallRng::from_thread_rng());
 gen_bytes!(gen_bytes_os, OsRng);
 
 macro_rules! gen_uint {
@@ -80,7 +80,7 @@ gen_uint!(gen_u32_chacha12, u32, ChaCha12Rng::from_entropy());
 gen_uint!(gen_u32_chacha20, u32, ChaCha20Rng::from_entropy());
 gen_uint!(gen_u32_std, u32, StdRng::from_entropy());
 #[cfg(feature = "small_rng")]
-gen_uint!(gen_u32_small, u32, SmallRng::from_entropy());
+gen_uint!(gen_u32_small, u32, SmallRng::from_thread_rng());
 gen_uint!(gen_u32_os, u32, OsRng);
 
 gen_uint!(gen_u64_step, u64, StepRng::new(0, 1));
@@ -93,7 +93,7 @@ gen_uint!(gen_u64_chacha12, u64, ChaCha12Rng::from_entropy());
 gen_uint!(gen_u64_chacha20, u64, ChaCha20Rng::from_entropy());
 gen_uint!(gen_u64_std, u64, StdRng::from_entropy());
 #[cfg(feature = "small_rng")]
-gen_uint!(gen_u64_small, u64, SmallRng::from_entropy());
+gen_uint!(gen_u64_small, u64, SmallRng::from_thread_rng());
 gen_uint!(gen_u64_os, u64, OsRng);
 
 macro_rules! init_gen {

benches/uniform.rs

@@ -23,7 +23,7 @@ const N_RESAMPLES: usize = 10_000;
 macro_rules! sample {
     ($R:ty, $T:ty, $U:ty, $g:expr) => {
         $g.bench_function(BenchmarkId::new(stringify!($R), "single"), |b| {
-            let mut rng = <$R>::from_entropy();
+            let mut rng = <$R>::from_rng(thread_rng()).unwrap();
             let x = rng.gen::<$U>();
             let bits = (<$T>::BITS / 2);
             let mask = (1 as $U).wrapping_neg() >> bits;
@@ -35,7 +35,7 @@ macro_rules! sample {
         });
 
         $g.bench_function(BenchmarkId::new(stringify!($R), "distr"), |b| {
-            let mut rng = <$R>::from_entropy();
+            let mut rng = <$R>::from_rng(thread_rng()).unwrap();
             let x = rng.gen::<$U>();
             let bits = (<$T>::BITS / 2);
             let mask = (1 as $U).wrapping_neg() >> bits;

benches/uniform_float.rs

@@ -27,7 +27,7 @@ const N_RESAMPLES: usize = 10_000;
 macro_rules! single_random {
     ($R:ty, $T:ty, $g:expr) => {
         $g.bench_function(BenchmarkId::new(stringify!($T), stringify!($R)), |b| {
-            let mut rng = <$R>::from_entropy();
+            let mut rng = <$R>::from_rng(thread_rng()).unwrap();
             let (mut low, mut high);
             loop {
                 low = <$T>::from_bits(rng.gen());
@@ -63,7 +63,7 @@ fn single_random(c: &mut Criterion) {
 macro_rules! distr_random {
     ($R:ty, $T:ty, $g:expr) => {
         $g.bench_function(BenchmarkId::new(stringify!($T), stringify!($R)), |b| {
-            let mut rng = <$R>::from_entropy();
+            let mut rng = <$R>::from_rng(thread_rng()).unwrap();
             let dist = loop {
                 let low = <$T>::from_bits(rng.gen());
                 let high = <$T>::from_bits(rng.gen());

rand_core/src/block.rs

@@ -80,7 +80,7 @@ pub trait BlockRngCore {
 /// A marker trait used to indicate that an [`RngCore`] implementation is
 /// supposed to be cryptographically secure.
 ///
-/// See [`CryptoRng`][crate::CryptoRng] docs for more information.
+/// See [`CryptoRng`] docs for more information.
 pub trait CryptoBlockRng: BlockRngCore { }
 
 /// A wrapper type implementing [`RngCore`] for some type implementing

src/rngs/small.rs

@@ -22,58 +22,20 @@ type Rng = super::xoshiro128plusplus::Xoshiro128PlusPlus;
 /// Note that depending on the application, [`StdRng`] may be faster on many
 /// modern platforms while providing higher-quality randomness. Furthermore,
 /// `SmallRng` is **not** a good choice when:
-/// - Security against prediction is important. Use [`StdRng`] instead.
-/// - Seeds with many zeros are provided. In such cases, it takes `SmallRng`
-///   about 10 samples to produce 0 and 1 bits with equal probability. Either
-///   provide seeds with an approximately equal number of 0 and 1 (for example
-///   by using [`SeedableRng::from_entropy`] or [`SeedableRng::seed_from_u64`]),
-///   or use [`StdRng`] instead.
 ///
-/// The algorithm is deterministic but should not be considered reproducible
-/// due to dependence on platform and possible replacement in future
-/// library versions. For a reproducible generator, use a named PRNG from an
-/// external crate, e.g. [rand_xoshiro] or [rand_chacha].
-/// Refer also to [The Book](https://rust-random.github.io/book/guide-rngs.html).
+/// - Portability is required. Its implementation is not fixed. Use a named
+///   generator from an external crate instead, for example [rand_xoshiro] or
+///   [rand_chacha]. Refer also to
+///   [The Book](https://rust-random.github.io/book/guide-rngs.html).
+/// - Security against prediction is important. Use [`StdRng`] instead.
 ///
 /// The PRNG algorithm in `SmallRng` is chosen to be efficient on the current
 /// platform, without consideration for cryptography or security. The size of
 /// its state is much smaller than [`StdRng`]. The current algorithm is
 /// `Xoshiro256PlusPlus` on 64-bit platforms and `Xoshiro128PlusPlus` on 32-bit
 /// platforms. Both are also implemented by the [rand_xoshiro] crate.
 ///
-/// # Examples
-///
-/// Initializing `SmallRng` with a random seed can be done using [`SeedableRng::from_entropy`]:
-///
-/// ```
-/// use rand::{Rng, SeedableRng};
-/// use rand::rngs::SmallRng;
-///
-/// // Create small, cheap to initialize and fast RNG with a random seed.
-/// // The randomness is supplied by the operating system.
-/// let mut small_rng = SmallRng::from_entropy();
-/// # let v: u32 = small_rng.gen();
-/// ```
-///
-/// When initializing a lot of `SmallRng`'s, using [`thread_rng`] can be more
-/// efficient:
-///
-/// ```
-/// use rand::{SeedableRng, thread_rng};
-/// use rand::rngs::SmallRng;
-///
-/// // Create a big, expensive to initialize and slower, but unpredictable RNG.
-/// // This is cached and done only once per thread.
-/// let mut thread_rng = thread_rng();
-/// // Create small, cheap to initialize and fast RNGs with random seeds.
-/// // One can generally assume this won't fail.
-/// let rngs: Vec<SmallRng> = (0..10)
-///     .map(|_| SmallRng::from_rng(&mut thread_rng).unwrap())
-///     .collect();
-/// ```
-///
 /// [`StdRng`]: crate::rngs::StdRng
-/// [`thread_rng`]: crate::thread_rng
 /// [rand_chacha]: https://crates.io/crates/rand_chacha
 /// [rand_xoshiro]: https://crates.io/crates/rand_xoshiro
 #[cfg_attr(doc_cfg, doc(cfg(feature = "small_rng")))]
@@ -102,21 +64,53 @@ impl RngCore for SmallRng {
     }
 }
 
-impl SeedableRng for SmallRng {
-    type Seed = <Rng as SeedableRng>::Seed;
-
+impl SmallRng {
+    /// Construct an instance seeded from another `Rng`
+    ///
+    /// We recommend that the source (master) RNG uses a different algorithm
+    /// (i.e. is not `SmallRng`) to avoid correlations between the child PRNGs.
+    ///
+    /// # Example
+    /// ```
+    /// # use rand::rngs::SmallRng;
+    /// let rng = SmallRng::from_rng(rand::thread_rng());
+    /// ```
     #[inline(always)]
-    fn from_seed(seed: Self::Seed) -> Self {
-        SmallRng(Rng::from_seed(seed))
+    pub fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error> {
+        Rng::from_rng(rng).map(SmallRng)
     }
 
+    /// Construct an instance seeded from the thread-local RNG
+    ///
+    /// # Panics
+    ///
+    /// This method panics only if [`thread_rng`](crate::thread_rng) fails to
+    /// initialize.
+    #[cfg(all(feature = "std", feature = "std_rng", feature = "getrandom"))]
     #[inline(always)]
-    fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error> {
-        Rng::from_rng(rng).map(SmallRng)
+    pub fn from_thread_rng() -> Self {
+        let mut seed = <Rng as SeedableRng>::Seed::default();
+        crate::thread_rng().fill_bytes(seed.as_mut());
+        SmallRng(Rng::from_seed(seed))
     }
 
+    /// Construct an instance from a `u64` seed
+    ///
+    /// This provides a convenient method of seeding a `SmallRng` from a simple
+    /// number by use of another algorithm to mutate and expand the input.
+    /// This is suitable for use with low Hamming Weight numbers like 0 and 1.
+    ///
+    /// **Warning:** the implementation is deterministic but not portable:
+    /// output values may differ according to platform and may be changed by a
+    /// future version of the library.
+    ///
+    /// # Example
+    /// ```
+    /// # use rand::rngs::SmallRng;
+    /// let rng = SmallRng::seed_from_u64(1);
+    /// ```
     #[inline(always)]
-    fn seed_from_u64(state: u64) -> Self {
+    pub fn seed_from_u64(state: u64) -> Self {
         SmallRng(Rng::seed_from_u64(state))
     }
 }

src/rngs/std.rs

@@ -57,7 +57,8 @@ impl RngCore for StdRng {
 }
 
 impl SeedableRng for StdRng {
-    type Seed = <Rng as SeedableRng>::Seed;
+    // Fix to 256 bits. Changing this is a breaking change!
+    type Seed = [u8; 32];
 
     #[inline(always)]
     fn from_seed(seed: Self::Seed) -> Self {