| 1 | // Copyright 2018 Developers of the Rand project. | 
| 2 | // | 
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| 3 | // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or | 
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| 4 | // https://www.apache.org/licenses/LICENSE-2.0> or the MIT license | 
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| 5 | // <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your | 
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| 6 | // option. This file may not be copied, modified, or distributed | 
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| 7 | // except according to those terms. | 
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| 8 |  | 
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| 9 | //! The implementations of the `Standard` distribution for other built-in types. | 
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| 10 |  | 
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| 11 | use core::char; | 
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| 12 | use core::num::Wrapping; | 
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| 13 | #[ cfg(feature = "alloc")] | 
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| 14 | use alloc::string::String; | 
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| 15 |  | 
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| 16 | use crate::distributions::{Distribution, Standard, Uniform}; | 
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| 17 | #[ cfg(feature = "alloc")] | 
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| 18 | use crate::distributions::DistString; | 
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| 19 | use crate::Rng; | 
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| 20 |  | 
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| 21 | #[ cfg(feature = "serde1")] | 
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| 22 | use serde::{Serialize, Deserialize}; | 
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| 23 | #[ cfg(feature = "min_const_gen")] | 
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| 24 | use core::mem::{self, MaybeUninit}; | 
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| 25 |  | 
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| 26 |  | 
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| 27 | // ----- Sampling distributions ----- | 
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| 28 |  | 
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| 29 | /// Sample a `u8`, uniformly distributed over ASCII letters and numbers: | 
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| 30 | /// a-z, A-Z and 0-9. | 
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| 31 | /// | 
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| 32 | /// # Example | 
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| 33 | /// | 
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| 34 | /// ``` | 
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| 35 | /// use rand::{Rng, thread_rng}; | 
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| 36 | /// use rand::distributions::Alphanumeric; | 
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| 37 | /// | 
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| 38 | /// let mut rng = thread_rng(); | 
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| 39 | /// let chars: String = (0..7).map(|_| rng.sample(Alphanumeric) as char).collect(); | 
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| 40 | /// println!( "Random chars: {}", chars); | 
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| 41 | /// ``` | 
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| 42 | /// | 
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| 43 | /// The [`DistString`] trait provides an easier method of generating | 
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| 44 | /// a random `String`, and offers more efficient allocation: | 
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| 45 | /// ``` | 
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| 46 | /// use rand::distributions::{Alphanumeric, DistString}; | 
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| 47 | /// let string = Alphanumeric.sample_string(&mut rand::thread_rng(), 16); | 
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| 48 | /// println!( "Random string: {}", string); | 
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| 49 | /// ``` | 
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| 50 | /// | 
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| 51 | /// # Passwords | 
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| 52 | /// | 
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| 53 | /// Users sometimes ask whether it is safe to use a string of random characters | 
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| 54 | /// as a password. In principle, all RNGs in Rand implementing `CryptoRng` are | 
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| 55 | /// suitable as a source of randomness for generating passwords (if they are | 
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| 56 | /// properly seeded), but it is more conservative to only use randomness | 
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| 57 | /// directly from the operating system via the `getrandom` crate, or the | 
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| 58 | /// corresponding bindings of a crypto library. | 
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| 59 | /// | 
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| 60 | /// When generating passwords or keys, it is important to consider the threat | 
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| 61 | /// model and in some cases the memorability of the password. This is out of | 
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| 62 | /// scope of the Rand project, and therefore we defer to the following | 
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| 63 | /// references: | 
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| 64 | /// | 
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| 65 | /// - [Wikipedia article on Password Strength](https://en.wikipedia.org/wiki/Password_strength) | 
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| 66 | /// - [Diceware for generating memorable passwords](https://en.wikipedia.org/wiki/Diceware) | 
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| 67 | #[ derive(Debug, Clone, Copy)] | 
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| 68 | #[ cfg_attr(feature = "serde1", derive(Serialize, Deserialize))] | 
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| 69 | pub struct Alphanumeric; | 
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| 70 |  | 
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| 71 |  | 
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| 72 | // ----- Implementations of distributions ----- | 
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| 73 |  | 
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| 74 | impl Distribution<char> for Standard { | 
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| 75 | #[ inline] | 
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| 76 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> char { | 
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| 77 | // A valid `char` is either in the interval `[0, 0xD800)` or | 
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| 78 | // `(0xDFFF, 0x11_0000)`. All `char`s must therefore be in | 
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| 79 | // `[0, 0x11_0000)` but not in the "gap" `[0xD800, 0xDFFF]` which is | 
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| 80 | // reserved for surrogates. This is the size of that gap. | 
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| 81 | const GAP_SIZE: u32 = 0xDFFF - 0xD800 + 1; | 
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| 82 |  | 
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| 83 | // Uniform::new(0, 0x11_0000 - GAP_SIZE) can also be used but it | 
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| 84 | // seemed slower. | 
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| 85 | let range: Uniform = Uniform::new(GAP_SIZE, high:0x11_0000); | 
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| 86 |  | 
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| 87 | let mut n: u32 = range.sample(rng); | 
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| 88 | if n <= 0xDFFF { | 
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| 89 | n -= GAP_SIZE; | 
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| 90 | } | 
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| 91 | unsafe { char::from_u32_unchecked(n) } | 
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| 92 | } | 
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| 93 | } | 
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| 94 |  | 
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| 95 | /// Note: the `String` is potentially left with excess capacity; optionally the | 
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| 96 | /// user may call `string.shrink_to_fit()` afterwards. | 
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| 97 | #[ cfg(feature = "alloc")] | 
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| 98 | impl DistString for Standard { | 
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| 99 | fn append_string<R: Rng + ?Sized>(&self, rng: &mut R, s: &mut String, len: usize) { | 
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| 100 | // A char is encoded with at most four bytes, thus this reservation is | 
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| 101 | // guaranteed to be sufficient. We do not shrink_to_fit afterwards so | 
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| 102 | // that repeated usage on the same `String` buffer does not reallocate. | 
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| 103 | s.reserve(additional:4 * len); | 
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| 104 | s.extend(iter:Distribution::<char>::sample_iter(self, rng).take(len)); | 
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| 105 | } | 
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| 106 | } | 
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| 107 |  | 
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| 108 | impl Distribution<u8> for Alphanumeric { | 
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| 109 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u8 { | 
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| 110 | const RANGE: u32 = 26 + 26 + 10; | 
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| 111 | const GEN_ASCII_STR_CHARSET: &[u8] = b"ABCDEFGHIJKLMNOPQRSTUVWXYZ\ | 
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| 112 |                 abcdefghijklmnopqrstuvwxyz\ | 
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| 113 |                 0123456789"; | 
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| 114 | // We can pick from 62 characters. This is so close to a power of 2, 64, | 
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| 115 | // that we can do better than `Uniform`. Use a simple bitshift and | 
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| 116 | // rejection sampling. We do not use a bitmask, because for small RNGs | 
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| 117 | // the most significant bits are usually of higher quality. | 
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| 118 | loop { | 
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| 119 | let var: u32 = rng.next_u32() >> (32 - 6); | 
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| 120 | if var < RANGE { | 
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| 121 | return GEN_ASCII_STR_CHARSET[var as usize]; | 
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| 122 | } | 
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| 123 | } | 
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| 124 | } | 
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| 125 | } | 
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| 126 |  | 
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| 127 | #[ cfg(feature = "alloc")] | 
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| 128 | impl DistString for Alphanumeric { | 
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| 129 | fn append_string<R: Rng + ?Sized>(&self, rng: &mut R, string: &mut String, len: usize) { | 
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| 130 | unsafe { | 
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| 131 | let v: &mut Vec = string.as_mut_vec(); | 
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| 132 | v.extend(self.sample_iter(rng).take(len)); | 
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| 133 | } | 
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| 134 | } | 
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| 135 | } | 
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| 136 |  | 
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| 137 | impl Distribution<bool> for Standard { | 
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| 138 | #[ inline] | 
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| 139 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> bool { | 
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| 140 | // We can compare against an arbitrary bit of an u32 to get a bool. | 
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| 141 | // Because the least significant bits of a lower quality RNG can have | 
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| 142 | // simple patterns, we compare against the most significant bit. This is | 
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| 143 | // easiest done using a sign test. | 
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| 144 | (rng.next_u32() as i32) < 0 | 
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| 145 | } | 
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| 146 | } | 
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| 147 |  | 
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| 148 | macro_rules! tuple_impl { | 
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| 149 | // use variables to indicate the arity of the tuple | 
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| 150 | ($($tyvar:ident),* ) => { | 
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| 151 | // the trailing commas are for the 1 tuple | 
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| 152 | impl< $( $tyvar ),* > | 
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| 153 | Distribution<( $( $tyvar ),* , )> | 
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| 154 | for Standard | 
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| 155 | where $( Standard: Distribution<$tyvar> ),* | 
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| 156 | { | 
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| 157 | #[inline] | 
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| 158 | fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> ( $( $tyvar ),* , ) { | 
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| 159 | ( | 
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| 160 | // use the $tyvar's to get the appropriate number of | 
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| 161 | // repeats (they're not actually needed) | 
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| 162 | $( | 
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| 163 | _rng.gen::<$tyvar>() | 
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| 164 | ),* | 
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| 165 | , | 
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| 166 | ) | 
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| 167 | } | 
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| 168 | } | 
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| 169 | } | 
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| 170 | } | 
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| 171 |  | 
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| 172 | impl Distribution<()> for Standard { | 
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| 173 | #[ allow(clippy::unused_unit)] | 
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| 174 | #[ inline] | 
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| 175 | fn sample<R: Rng + ?Sized>(&self, _: &mut R) -> () { | 
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| 176 | () | 
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| 177 | } | 
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| 178 | } | 
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| 179 | tuple_impl! {A} | 
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| 180 | tuple_impl! {A, B} | 
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| 181 | tuple_impl! {A, B, C} | 
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| 182 | tuple_impl! {A, B, C, D} | 
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| 183 | tuple_impl! {A, B, C, D, E} | 
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| 184 | tuple_impl! {A, B, C, D, E, F} | 
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| 185 | tuple_impl! {A, B, C, D, E, F, G} | 
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| 186 | tuple_impl! {A, B, C, D, E, F, G, H} | 
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| 187 | tuple_impl! {A, B, C, D, E, F, G, H, I} | 
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| 188 | tuple_impl! {A, B, C, D, E, F, G, H, I, J} | 
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| 189 | tuple_impl! {A, B, C, D, E, F, G, H, I, J, K} | 
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| 190 | tuple_impl! {A, B, C, D, E, F, G, H, I, J, K, L} | 
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| 191 |  | 
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| 192 | #[ cfg(feature = "min_const_gen")] | 
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| 193 | #[ cfg_attr(doc_cfg, doc(cfg(feature = "min_const_gen")))] | 
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| 194 | impl<T, const N: usize> Distribution<[T; N]> for Standard | 
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| 195 | where Standard: Distribution<T> | 
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| 196 | { | 
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| 197 | #[ inline] | 
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| 198 | fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; N] { | 
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| 199 | let mut buff: [MaybeUninit<T>; N] = unsafe { MaybeUninit::uninit().assume_init() }; | 
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| 200 |  | 
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| 201 | for elem in &mut buff { | 
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| 202 | *elem = MaybeUninit::new(_rng.gen()); | 
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| 203 | } | 
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| 204 |  | 
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| 205 | unsafe { mem::transmute_copy::<_, _>(&buff) } | 
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| 206 | } | 
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| 207 | } | 
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| 208 |  | 
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| 209 | #[ cfg(not(feature = "min_const_gen"))] | 
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| 210 | macro_rules! array_impl { | 
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| 211 | // recursive, given at least one type parameter: | 
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| 212 | {$n:expr, $t:ident, $($ts:ident,)*} => { | 
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| 213 | array_impl!{($n - 1), $($ts,)*} | 
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| 214 |  | 
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| 215 | impl<T> Distribution<[T; $n]> for Standard where Standard: Distribution<T> { | 
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| 216 | #[inline] | 
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| 217 | fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] { | 
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| 218 | [_rng.gen::<$t>(), $(_rng.gen::<$ts>()),*] | 
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| 219 | } | 
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| 220 | } | 
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| 221 | }; | 
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| 222 | // empty case: | 
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| 223 | {$n:expr,} => { | 
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| 224 | impl<T> Distribution<[T; $n]> for Standard { | 
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| 225 | fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] { [] } | 
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| 226 | } | 
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| 227 | }; | 
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| 228 | } | 
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| 229 |  | 
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| 230 | #[ cfg(not(feature = "min_const_gen"))] | 
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| 231 | array_impl! {32, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T,} | 
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| 232 |  | 
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| 233 | impl<T> Distribution<Option<T>> for Standard | 
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| 234 | where Standard: Distribution<T> | 
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| 235 | { | 
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| 236 | #[ inline] | 
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| 237 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Option<T> { | 
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| 238 | // UFCS is needed here: https://github.com/rust-lang/rust/issues/24066 | 
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| 239 | if rng.gen::<bool>() { | 
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| 240 | Some(rng.gen()) | 
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| 241 | } else { | 
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| 242 | None | 
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| 243 | } | 
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| 244 | } | 
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| 245 | } | 
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| 246 |  | 
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| 247 | impl<T> Distribution<Wrapping<T>> for Standard | 
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| 248 | where Standard: Distribution<T> | 
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| 249 | { | 
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| 250 | #[ inline] | 
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| 251 | fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Wrapping<T> { | 
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| 252 | Wrapping(rng.gen()) | 
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| 253 | } | 
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| 254 | } | 
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| 255 |  | 
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| 256 |  | 
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| 257 | #[ cfg(test)] | 
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| 258 | mod tests { | 
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| 259 | use super::*; | 
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| 260 | use crate::RngCore; | 
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| 261 | #[ cfg(feature = "alloc")] use alloc::string::String; | 
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| 262 |  | 
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| 263 | #[ test] | 
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| 264 | fn test_misc() { | 
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| 265 | let rng: &mut dyn RngCore = &mut crate::test::rng(820); | 
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| 266 |  | 
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| 267 | rng.sample::<char, _>(Standard); | 
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| 268 | rng.sample::<bool, _>(Standard); | 
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| 269 | } | 
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| 270 |  | 
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| 271 | #[ cfg(feature = "alloc")] | 
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| 272 | #[ test] | 
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| 273 | fn test_chars() { | 
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| 274 | use core::iter; | 
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| 275 | let mut rng = crate::test::rng(805); | 
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| 276 |  | 
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| 277 | // Test by generating a relatively large number of chars, so we also | 
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| 278 | // take the rejection sampling path. | 
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| 279 | let word: String = iter::repeat(()) | 
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| 280 | .map(|()| rng.gen::<char>()) | 
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| 281 | .take(1000) | 
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| 282 | .collect(); | 
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| 283 | assert!(!word.is_empty()); | 
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| 284 | } | 
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| 285 |  | 
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| 286 | #[ test] | 
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| 287 | fn test_alphanumeric() { | 
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| 288 | let mut rng = crate::test::rng(806); | 
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| 289 |  | 
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| 290 | // Test by generating a relatively large number of chars, so we also | 
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| 291 | // take the rejection sampling path. | 
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| 292 | let mut incorrect = false; | 
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| 293 | for _ in 0..100 { | 
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| 294 | let c: char = rng.sample(Alphanumeric).into(); | 
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| 295 | incorrect |= !(( '0'..= '9').contains(&c) || | 
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| 296 | ( 'A'..= 'Z').contains(&c) || | 
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| 297 | ( 'a'..= 'z').contains(&c) ); | 
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| 298 | } | 
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| 299 | assert!(!incorrect); | 
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| 300 | } | 
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| 301 |  | 
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| 302 | #[ test] | 
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| 303 | fn value_stability() { | 
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| 304 | fn test_samples<T: Copy + core::fmt::Debug + PartialEq, D: Distribution<T>>( | 
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| 305 | distr: &D, zero: T, expected: &[T], | 
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| 306 | ) { | 
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| 307 | let mut rng = crate::test::rng(807); | 
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| 308 | let mut buf = [zero; 5]; | 
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| 309 | for x in &mut buf { | 
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| 310 | *x = rng.sample(&distr); | 
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| 311 | } | 
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| 312 | assert_eq!(&buf, expected); | 
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| 313 | } | 
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| 314 |  | 
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| 315 | test_samples(&Standard, 'a', &[ | 
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| 316 | '\u{8cdac} ', | 
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| 317 | '\u{a346a} ', | 
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| 318 | '\u{80120} ', | 
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| 319 | '\u{ed692} ', | 
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| 320 | '\u{35888} ', | 
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| 321 | ]); | 
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| 322 | test_samples(&Alphanumeric, 0, &[104, 109, 101, 51, 77]); | 
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| 323 | test_samples(&Standard, false, &[true, true, false, true, false]); | 
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| 324 | test_samples(&Standard, None as Option<bool>, &[ | 
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| 325 | Some(true), | 
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| 326 | None, | 
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| 327 | Some(false), | 
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| 328 | None, | 
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| 329 | Some(false), | 
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| 330 | ]); | 
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| 331 | test_samples(&Standard, Wrapping(0i32), &[ | 
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| 332 | Wrapping(-2074640887), | 
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| 333 | Wrapping(-1719949321), | 
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| 334 | Wrapping(2018088303), | 
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| 335 | Wrapping(-547181756), | 
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| 336 | Wrapping(838957336), | 
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| 337 | ]); | 
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| 338 |  | 
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| 339 | // We test only sub-sets of tuple and array impls | 
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| 340 | test_samples(&Standard, (), &[(), (), (), (), ()]); | 
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| 341 | test_samples(&Standard, (false,), &[ | 
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| 342 | (true,), | 
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| 343 | (true,), | 
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| 344 | (false,), | 
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| 345 | (true,), | 
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| 346 | (false,), | 
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| 347 | ]); | 
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| 348 | test_samples(&Standard, (false, false), &[ | 
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| 349 | (true, true), | 
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| 350 | (false, true), | 
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| 351 | (false, false), | 
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| 352 | (true, false), | 
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| 353 | (false, false), | 
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| 354 | ]); | 
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| 355 |  | 
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| 356 | test_samples(&Standard, [0u8; 0], &[[], [], [], [], []]); | 
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| 357 | test_samples(&Standard, [0u8; 3], &[ | 
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| 358 | [9, 247, 111], | 
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| 359 | [68, 24, 13], | 
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| 360 | [174, 19, 194], | 
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| 361 | [172, 69, 213], | 
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| 362 | [149, 207, 29], | 
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| 363 | ]); | 
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| 364 | } | 
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| 365 | } | 
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| 366 |  | 
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