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75b4dd18
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75b4dd18
authored
4月 29, 2022
作者:
Brandon T. Willard
提交者:
Brandon T. Willard
4月 29, 2022
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Update RandomStream documentation
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utils.rst
doc/library/tensor/random/utils.rst
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doc/library/tensor/random/utils.rst
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@@ -12,16 +12,20 @@
Guide
=====
Since Aesara uses a functional design, producing pseudo-random numbers in a
graph is not quite as straightforward as it is in numpy.
Aesara assignes NumPy RNG states (e.g. `Generator` or `RandomState` objects) to
each `RandomVariable`. The combination of an RNG state, a specific
`RandomVariable` type (e.g. `NormalRV`), and a set of distribution parameters
uniquely defines the `RandomVariable` instances in a graph.
The way to think about putting randomness into Aesara's computations is to
put random variables in your graph. Aesara will allocate a numpy RandomState
object for each such variable, and draw from it as necessary. We will call this sort of sequence of
random numbers a *random stream*.
This means that a "stream" of distinct RNG states is required in order to
produce distinct random variables of the same kind. `RandomStream` provides a
means of generating distinct random variables in a fully reproducible way.
For an example of how to use random numbers, see
:ref:`Using Random Numbers <using_random_numbers>`.
`RandomStream` is also designed to produce simpler graphs and work with more
sophisticated `Op`\s like `Scan`, which makes it the de facto random variable
interface in Aesara.
For an example of how to use random numbers, see :ref:`Using Random Numbers <using_random_numbers>`.
Reference
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@@ -29,7 +33,7 @@ Reference
.. class:: RandomStream()
This is a symbolic stand-in for `
`numpy.random.RandomState`
`.
This is a symbolic stand-in for `
numpy.random.Generator
`.
.. method:: updates()
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@@ -37,7 +41,8 @@ Reference
random variables created by this object
This can be a convenient shortcut to enumerating all the random
variables in a large graph in the ``update`` parameter of function.
variables in a large graph in the ``update`` argument to
`aesara.function`.
.. method:: seed(meta_seed)
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@@ -49,9 +54,7 @@ Reference
.. method:: gen(op, *args, **kwargs)
Return the random variable from `op(*args, **kwargs)`, but
also install special attributes (``.rng`` and ``update``, see
:class:`RandomVariable` ) into it.
Return the random variable from ``op(*args, **kwargs)``.
This function also adds the returned variable to an internal list so
that it can be seeded later by a call to `seed`.
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