jax.random
E438359
jax.random is JAX’s module for generating and manipulating pseudo-random numbers in a functional, reproducible way using PRNG keys.
All labels observed (1)
| Label | Occurrences |
|---|---|
| jax.random canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4425388 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: jax.random Context triple: [JAX, hasComponent, jax.random]
-
A.
cuRAND
cuRAND is NVIDIA's GPU-accelerated random number generation library designed to efficiently produce high-quality random numbers for parallel applications using CUDA.
-
B.
Random
Random is a fictional character who serves as the main protagonist in the story "Out of the Blue."
-
C.
Random
Random is a Julia standard library module that provides functionality for generating and manipulating random numbers and random processes.
-
D.
Chainer
Chainer is an open-source deep learning framework for Python that pioneered a flexible "define-by-run" computation graph approach to building neural networks.
-
E.
Theano
Theano is an open-source numerical computation library for Python that allows efficient definition, optimization, and evaluation of mathematical expressions, particularly those involving multi-dimensional arrays, and was widely used as a backend for deep learning frameworks.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: jax.random Target entity description: jax.random is JAX’s module for generating and manipulating pseudo-random numbers in a functional, reproducible way using PRNG keys.
-
A.
cuRAND
cuRAND is NVIDIA's GPU-accelerated random number generation library designed to efficiently produce high-quality random numbers for parallel applications using CUDA.
-
B.
Random
Random is a fictional character who serves as the main protagonist in the story "Out of the Blue."
-
C.
Random
Random is a Julia standard library module that provides functionality for generating and manipulating random numbers and random processes.
-
D.
Chainer
Chainer is an open-source deep learning framework for Python that pioneered a flexible "define-by-run" computation graph approach to building neural networks.
-
E.
Theano
Theano is an open-source numerical computation library for Python that allows efficient definition, optimization, and evaluation of mathematical expressions, particularly those involving multi-dimensional arrays, and was widely used as a backend for deep learning frameworks.
- F. None of above. chosen
Statements (60)
| Predicate | Object |
|---|---|
| instanceOf |
JAX submodule
ⓘ
Python module ⓘ |
| compatibleWith |
jax.grad
ⓘ
jax.jit ⓘ jax.pmap ⓘ jax.vmap ⓘ |
| designedFor | pure functional style ⓘ |
| distributedBy |
JAX project
ⓘ
linked to:
JAX
|
| documentationURL | https://jax.readthedocs.io/en/latest/jax.random.html ⓘ |
| ensures |
explicit handling of random state
ⓘ
stateless random number generation ⓘ |
| hostedOn | GitHub (google/jax) ⓘ |
| implementedIn | Python ⓘ |
| implements | pseudo-random number generation ⓘ |
| partOf |
jax
ⓘ
linked to:
jax.experimental
|
| providesFunction |
PRNGKey
ⓘ
bernoulli ⓘ beta ⓘ binomial ⓘ categorical ⓘ cauchy ⓘ chisquare ⓘ choice ⓘ default_prng_impl ⓘ dirichlet ⓘ exponential ⓘ f ⓘ fold_in ⓘ gamma ⓘ geometric ⓘ gumbel ⓘ key ⓘ laplace ⓘ logistic ⓘ lognormal ⓘ logseries ⓘ multivariate_normal ⓘ normal ⓘ orthogonal ⓘ pareto ⓘ permutation ⓘ poisson ⓘ rademacher ⓘ randint ⓘ seed ⓘ shuffle ⓘ split ⓘ t ⓘ threefry2x32 ⓘ threefry_2x32 ⓘ triangular ⓘ truncated_exponential ⓘ truncated_normal ⓘ uniform ⓘ vonmises ⓘ wald ⓘ weibull_min ⓘ |
| requires | PRNGKey ⓘ |
| supports | reproducible random number generation ⓘ |
| uses | functional PRNG model ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: jax.random Description of subject: jax.random is JAX’s module for generating and manipulating pseudo-random numbers in a functional, reproducible way using PRNG keys.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.