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Base class for all MCMC Reducer
s.
This class defines the minimal requirements to implement a Markov chain Monte
Carlo (MCMC) reducer. A reducer updates a streaming computation by reducing
new samples to a summary statistic. Reducer
s can be defined to return "side
information" if desired, but they do not remember state. Hence, reducers
should be seen as objects that hold metadata (i.e. shape and dtype of
incoming samples) and all reducer method calls must be coupled with a state
object, as first returned by the initialize
method.
Methods
finalize
finalize(
final_reducer_state
)
Finalizes target statistic calculation from the final_state
.
This is an identity function of the final_state
by default. Subclasses
can override it for streaming calculations whose running state is not the
same as the desired result.
Args | |
---|---|
final_reducer_state
|
A tuple , namedtuple or list of Tensor s
representing the final state of the reduced statistic.
|
Returns | |
---|---|
statistic
|
An estimate of the target statistic |
initialize
@abc.abstractmethod
initialize( initial_chain_state, initial_inner_kernel_results )
Initializes a reducer state corresponding to the stream of no samples.
This is an abstract method and must be overridden by subclasses.
Args | |
---|---|
initial_chain_state
|
Tensor or Python list of Tensor s representing
the current state(s) of the Markov chain(s). This is to be used for
any needed (shape, dtype, etc.) information, but should not be
considered part of the stream being reduced.
|
initial_inner_kernel_results
|
A (possibly nested) tuple , namedtuple or
list of Tensor s representing internal calculations made in a related
TransitionKernel . This allows for introspection of deeper layers of
TransitionKernel s that have bearing to the nature of the initial
reducer state.
|
Returns | |
---|---|
init_reducer_state
|
tuple , namedtuple or list of Tensor s
representing the stream of no samples.
|
one_step
@abc.abstractmethod
one_step( new_chain_state, current_reducer_state, previous_kernel_results )
Takes one step of the Reducer
.
This is an abstract method and must be overridden by subclasses.
Args | |
---|---|
new_chain_state
|
Incoming chain state(s) with shape and dtype compatible
with the initial_chain_state with which the current_reducer_state
was produced by initialize .
|
current_reducer_state
|
A tuple , namedtuple or list of Tensor s
representing the current state of reduced statistics.
|
previous_kernel_results
|
A (possibly nested) tuple , namedtuple or
list of Tensor s representing internal calculations made in a related
TransitionKernel . This allows for introspection of deeper layers of
TransitionKernel s that have bearing to the nature of the updated
reducer state (i.e. updating based on a value in the kernel results of
some TransitionKernel ).
|
Returns | |
---|---|
new_state
|
The new reducer state after updates. This has the same type and
structure as current_reducer_state .
|