JEP 9263: Typed keys & pluggable RNGs#

Jake VanderPlas, Roy Frostig

August 2023


Going forward, RNG keys in JAX will be more type-safe and customizable. Rather than representing a single PRNG key by a length-2 uint32 array, it will be represented as a scalar array with a special RNG dtype that satisfies jnp.issubdtype(key.dtype, jax.dtypes.prng_key).

For now, old-style RNG keys can still be created with jax.random.PRNGKey():

>>> key = jax.random.PRNGKey(0)
>>> key
Array([0, 0], dtype=uint32)
>>> key.shape
>>> key.dtype

Starting now, new-style RNG keys can be created with jax.random.key():

>>> key = jax.random.key(0)
>>> key
Array((), dtype=key<fry>) overlaying:
[0 0]
>>> key.shape
>>> key.dtype

This (scalar-shaped) array behaves the same as any other JAX array, except that its element type is a key (and associated metadata). We can make non-scalar key arrays as well, for example by applying jax.vmap() to jax.random.key():

>>> key_arr = jax.vmap(jax.random.key)(jnp.arange(4))
>>> key_arr
Array((4,), dtype=key<fry>) overlaying:
[[0 0]
 [0 1]
 [0 2]
 [0 3]]
>>> key_arr.shape

Aside from switching to a new constructor, most PRNG-related code should continue to work as expected. You can continue to use keys in jax.random APIs as before; for example:

# split
new_key, subkey = jax.random.split(key)

# random number generation
data = jax.random.uniform(key, shape=(5,))

However, not all numerical operations work on key arrays. They now intentionally raise errors:

>>> key = key + 1
ValueError: dtype=key<fry> is not a valid dtype for JAX type promotion.

If for some reason you need to recover the underlying buffer (the old-style key), you can do so with jax.random.key_data():

>>> jax.random.key_data(key)
Array([0, 0], dtype=uint32)

For old-style keys, key_data() is an identity operation.

What does this mean for users?#

For JAX users, this change does not require any code changes now, but we hope that you will find the upgrade worthwhile and switch to using typed keys. To try this out, replace uses of jax.random.PRNGKey() with jax.random.key(). This may introduce breakages in your code that fall into one of a few categories:

  • If your code performs unsafe/unsupported operations on keys (such as indexing, arithmetic, transposition, etc; see Type Safety section below), this change will catch it. You can update your code to avoid such unsupported operations, or use jax.random.key_data() and jax.random.wrap_key_data() to manipulate raw key buffers in an unsafe way.

  • If your code includes explicit logic about key.shape, you may need to update this logic to account for the fact that the trailing key buffer dimension is no longer an explicit part of the shape.

  • If your code includes explicit logic about key.dtype, you will need to upgrade it to use the new public APIs for reasoning about RNG dtypes, such as dtypes.issubdtype(dtype, dtypes.prng_key).

  • If you call a JAX-based library which does not yet handle typed PRNG keys, you can use raw_key = jax.random.key_data(key) for now to recover the raw buffer, but please keep a TODO to remove this once the downstream library supports typed RNG keys.

At some point in the future, we plan to deprecate jax.random.PRNGKey() and require the use of jax.random.key().

Detecting new-style typed keys#

To check whether an object is a new-style typed PRNG key, you can use jax.dtypes.issubdtype or jax.numpy.issubdtype:

>>> typed_key = jax.random.key(0)
>>> jax.dtypes.issubdtype(typed_key.dtype, jax.dtypes.prng_key)
>>> raw_key = jax.random.PRNGKey(0)
>>> jax.dtypes.issubdtype(raw_key.dtype, jax.dtypes.prng_key)

Type annotations for PRNG Keys#

The recommended type annotation for both old and new-style PRNG keys is jax.Array. A PRNG key is distinguished from other arrays based on its dtype, and it is not currently possible to specify dtypes of JAX arrays within a type annotation. Previously it was possible to use jax.random.KeyArray or jax.random.PRNGKeyArray as type annotations, but these have always been aliased to Any under type checking, and so jax.Array has much more specificity.

Note: jax.random.KeyArray and jax.random.PRNGKeyArray were deprecated in JAX version 0.4.16, and removed in JAX version 0.4.24.

Notes for JAX library authors#

If you maintain a JAX-based library, your users are also JAX users. Know that JAX will continue to support “raw” old-style keys in jax.random for now, so callers may expect them to remain accepted everywhere. If you prefer to require new-style typed keys in your library, then you may want to enforce them with a check along the following lines:

from jax import dtypes

def ensure_typed_key_array(key: Array) -> Array:
  if dtypes.issubdtype(key.dtype, dtypes.prng_key):
    return key
    raise TypeError("New-style typed JAX PRNG keys required")


Two major motivating factors for this change are customizability and safety.

Customizing PRNG implementations#

JAX currently operates with a single, globally configured PRNG algorithm. A PRNG key is a vector of unsigned 32-bit integers, which jax.random APIs consume to produce pseudorandom streams. Any higher-rank uint32 array is interpreted as an array of such key buffers, where the trailing dimension represents keys.

The drawbacks of this design became clearer as we introduced alternative PRNG implementations, which must be selected by setting a global or local configuration flag. Different PRNG implementations have different size key buffers, and different algorithms for generating random bits. Determining this behavior with a global flag is error-prone, especially when there is more than one key implementation in use process-wide.

Our new approach is to carry the implementation as part of the PRNG key type, i.e. with the element type of the key array. Using the new key API, here is an example of generating pseudorandom values under the default threefry2x32 implementation (which is implemented in pure Python and compiled with JAX), and under the non-default rbg implementation (which corresponds to a single XLA random-bit generation operation):

>>> key = jax.random.key(0, impl='threefry2x32')  # this is the default impl
>>> key
Array((), dtype=key<fry>) overlaying:
[0 0]
>>> jax.random.uniform(key, shape=(3,))
Array([0.9653214 , 0.31468165, 0.63302994], dtype=float32)

>>> key = jax.random.key(0, impl='rbg')
>>> key
Array((), dtype=key<rbg>) overlaying:
[0 0 0 0]
>>> jax.random.uniform(key, shape=(3,))
Array([0.39904642, 0.8805201 , 0.73571277], dtype=float32)

Safe PRNG key use#

PRNG keys are really only meant to support a few operations in principle, namely key derivation (e.g. splitting) and random number generation. The PRNG is designed to generate independent pseudorandom numbers, provided keys are properly split and that every key is consumed once.

Code that manipulates or consumes key data in other ways often indicates an accidental bug, and representing key arrays as raw uint32 buffers has allowed for easy misuse along these lines. Here are a few example misuses that we’ve encountered in the wild:

Key buffer indexing#

Access to the underlying integer buffers makes it easy to try and derive keys in non-standard ways, sometimes with unexpectedly bad consequences:

# Incorrect
key = random.PRNGKey(999)
new_key = random.PRNGKey(key[1])  # identical to the original key!
# Correct
key = random.PRNGKey(999)
key, new_key = random.split(key)

If this key were a new-style typed key made with random.key(999), indexing into the key buffer would error instead.

Key arithmetic#

Key arithmetic is a similarly treacherous way to derive keys from other keys. Deriving keys in a way that avoids jax.random.split() or jax.random.fold_in() by manipulating key data directly produces a batch of keys that—depending on the PRNG implementation—might then generate correlated random numbers within the batch:

# Incorrect
key = random.PRNGKey(0)
batched_keys = key + jnp.arange(10, dtype=key.dtype)[:, None]
# Correct
key = random.PRNGKey(0)
batched_keys = random.split(key, 10)

New-style typed keys created with random.key(0) address this by disallowing arithmetic operations on keys.

Inadvertent transposing of key buffers#

With “raw” old-style key arrays, it’s easy to accidentally swap batch (leading) dimensions and key buffer (trailing) dimensions. Again this possibly results in keys that produce correlated pseudorandomness. A pattern that we’ve seen over time boils down to this:

# Incorrect
keys = random.split(random.PRNGKey(0))
data = jax.vmap(random.uniform, in_axes=1)(keys)
# Correct
keys = random.split(random.PRNGKey(0))
data = jax.vmap(random.uniform, in_axes=0)(keys)

The bug here is subtle. By mapping over in_axes=1, this code makes new keys by combining a single element from each key buffer in the batch. The resulting keys are different from one another, but are effectively “derived” in a non-standard way. Again, the PRNG is not designed or tested to produce independent random streams from such a key batch.

New-style typed keys created with random.key(0) address this by hiding the buffer representation of individual keys, instead treating keys as opaque elements of a key array. Key arrays have no trailing “buffer” dimension to index, transpose, or map over.

Key reuse#

Unlike state-based PRNG APIs like numpy.random, JAX’s functional PRNG does not implicitly update a key when it has been used.

# Incorrect
key = random.PRNGKey(0)
x = random.uniform(key, (100,))
y = random.uniform(key, (100,))  # Identical values!
# Correct
key = random.PRNGKey(0)
key1, key2 = random.split(random.key(0))
x = random.uniform(key1, (100,))
y = random.uniform(key2, (100,))

We’re actively working on tools to detect and prevent unintended key reuse. This is still work in progress, but it relies on typed key arrays. Upgrading to typed keys now sets us up to introduce these safety features as we build them out.

Design of typed PRNG keys#

Typed PRNG keys are implemented as an instance of extended dtypes within JAX, of which the new PRNG dtypes are a sub-dtype.

Extended dtypes#

From the user perspective, an extended dtype dt has the following user-visible properties:

  • jax.dtypes.issubdtype(dt, jax.dtypes.extended) returns True: this is the public API that should be used to detect whether a dtype is an extended dtype.

  • It has a class-level attribute dt.type, which returns a typeclass in the hierarchy of numpy.generic. This is analogous to how np.dtype('int32').type returns numpy.int32, which is not a dtype but rather a scalar type, and a subclass of numpy.generic.

  • Unlike numpy scalar types, we do not allow instantiation of dt.type scalar objects: this is in accordance with JAX’s decision to represent scalar values as zero-dimensional arrays.

From a non-public implementation perspective, an extended dtype has the following properties:

  • Its type is a subclass of the private base class jax._src.dtypes.ExtendedDtype, the non-public base class used for extended dtypes. An instance of ExtendedDtype is analogous to an instance of np.dtype, like np.dtype('int32').

  • It has a private _rules attribute which allows the dtype to define how it behaves under particular operations. For example, jax.lax.full(shape, fill_value, dtype) will delegate to dtype._rules.full(shape, fill_value, dtype) when dtype is an extended dtype.

Why introduce extended dtypes in generality, beyond PRNGs? We reuse this same extended dtype mechanism elsewhere internally. For example, the jax._src.core.bint object, a bounded integer type used for experimental work on dynamic shapes, is another extended dtype. In recent JAX versions it satisfies the properties above (See jax/_src/

PRNG dtypes#

PRNG dtypes are defined as a particular case of extended dtypes. Specifically, this change introduces a new public scalar type class jax.dtypes.prng_key, which has the following property:

>>> jax.dtypes.issubdtype(jax.dtypes.prng_key, jax.dtypes.extended)

PRNG key arrays then have a dtype with the following properties:

>>> key = jax.random.key(0)
>>> jax.dtypes.issubdtype(key.dtype, jax.dtypes.extended)
>>> jax.dtypes.issubdtype(key.dtype, jax.dtypes.prng_key)

And in addition to key.dtype._rules as outlined for extended dtypes in general, PRNG dtypes define key.dtype._impl, which contains the metadata that defines the PRNG implementation. The PRNG implementation is currently defined by the non-public jax._src.prng.PRNGImpl class. For now, PRNGImpl isn’t meant to be a public API, but we might revisit this soon to allow for fully custom PRNG implementations.


Following is a non-comprehensive list of key Pull Requests implementing the above design. The main tracking issue is #9263.

  • Implement pluggable PRNG via PRNGImpl: #6899

  • Implement PRNGKeyArray, without dtype: #11952

  • Add a “custom element” dtype property to PRNGKeyArray with _rules attribute: #12167

  • Rename “custom element type” to “opaque dtype”: #12170

  • Refactor bint to use the opaque dtype infrastructure: #12707

  • Add jax.random.key to create typed keys directly: #16086

  • Add impl argument to key and PRNGKey: #16589

  • Rename “opaque dtype” to “extended dtype” & define jax.dtypes.extended: #16824

  • Introduce jax.dtypes.prng_key and unify PRNG dtype with Extended dtype: #16781

  • Add a jax_legacy_prng_key flag to support warning or erroring when using legacy (raw) PRNG keys: #17225