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Awni Hannun 2023-11-29 12:38:32 -08:00
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commit c1b6bf3f33

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mlx/random.h Normal file
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#pragma once
#include <optional>
#include "mlx/array.h"
#include "mlx/stream.h"
namespace mlx::core::random {
class KeySequence {
public:
explicit KeySequence(uint64_t seed);
void seed(uint64_t seed);
array next();
// static defualt
static KeySequence& default_() {
static KeySequence ks(0);
return ks;
}
private:
array key_;
};
/** Get a PRNG key from a seed. */
array key(uint64_t seed);
/** Seed the default PRNG key. */
void seed(uint64_t seed);
/** Generate an array with type uint32 filled with random bits. */
array bits(
const std::vector<int>& shape,
int width,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
inline array bits(
const std::vector<int>& shape,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {}) {
return bits(shape, 4, key, s);
}
/** Split the rng key into a pair of keys. */
std::pair<array, array> split(const array& key, StreamOrDevice s = {});
/** Split the rng key into `num` keys. */
array split(const array& key, int num, StreamOrDevice s = {});
/** Generate uniform random numbers between low and high. */
array uniform(
const array& low,
const array& high,
const std::vector<int>& shape,
Dtype dtype = float32,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
template <typename T, typename U>
array uniform(
T low,
U high,
const std::vector<int>& shape,
Dtype dtype = float32,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {}) {
return uniform(array(low), array(high), shape, dtype, key, to_stream(s));
}
/** Generate uniform random numbers between 0 and 1. */
array uniform(
const std::vector<int>& shape,
Dtype dtype,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
inline array uniform(
const std::vector<int>& shape,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {}) {
return uniform(shape, float32, key);
}
/** Generate samples from the standard normal distribution. */
array normal(
const std::vector<int>& shape,
Dtype dtype,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
inline array normal(
const std::vector<int>& shape,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {}) {
return normal(shape, float32, key, s);
}
/** Generate integer samples uniformly at random */
array randint(
const array& low,
const array& high,
const std::vector<int>& shape,
Dtype dtype = int32,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
template <typename T, typename U>
array randint(
T low,
U high,
const std::vector<int>& shape,
Dtype dtype = int32,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {}) {
return randint(array(low), array(high), shape, dtype, key, to_stream(s));
};
/** Generate binary variables with probability to be true equal to p */
array bernoulli(
const array& p,
const std::vector<int>& shape,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
array bernoulli(
const array& p,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
template <typename T>
array bernoulli(
T p,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {}) {
return bernoulli(array(p), key, s);
};
template <typename T>
array bernoulli(
T p,
const std::vector<int>& shape,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {}) {
return bernoulli(array(p), shape, key, s);
};
array bernoulli(
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
array truncated_normal(
const array& lower,
const array& upper,
const std::vector<int>& shape,
Dtype dtype = float32,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
array truncated_normal(
const array& lower,
const array& upper,
Dtype dtype = float32,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
array gumbel(
const std::vector<int>& shape,
Dtype dtype = float32,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
array categorical(
const array& logits,
int axis,
const std::vector<int>& shape,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
array categorical(
const array& logits_,
int axis,
int num_samples,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
array categorical(
const array& logits,
int axis = -1,
const std::optional<array>& key = std::nullopt,
StreamOrDevice s = {});
} // namespace mlx::core::random