def __init__(self, samples_per_insert: float, min_size_to_sample: int,
error_buffer: Union[float, Tuple[float, float]]):
"""Constructor of SampleToInsertRatio.
Args:
samples_per_insert: The average number of times the learner should sample
each item in the replay error_buffer during the item's entire lifetime.
min_size_to_sample: The minimum number of items that the table must
contain before transitioning into stage 2.
error_buffer: Maximum size of the "error" before calls should be blocked.
When a single value is provided then inferred range is
(
min_size_to_sample * samples_per_insert - error_buffer,
min_size_to_sample * samples_per_insert + error_buffer
)
The offset is added so that the error tracked is for the insert/sample
ratio only takes into account operatons occurring AFTER stage 1. If a
range (two float tuple) then the values are used without any offset.
Raises:
ValueError: If error_buffer is smaller than max(1.0, samples_per_inserts).
"""
if isinstance(error_buffer, float) or isinstance(error_buffer, int):
offset = samples_per_insert * min_size_to_sample
min_diff = offset - error_buffer
max_diff = offset + error_buffer
else:
min_diff, max_diff = error_buffer
if max_diff - min_diff < 2 * max(1.0, samples_per_insert):
raise ValueError(
'The size of error_buffer must be >= 2 * max(1.0, samples_per_insert) '
'as smaller values could completely block samples and/or insert calls.'
)
if max_diff < samples_per_insert * min_size_to_sample:
logging.warning(
'The range covered by error_buffer is below '
'samples_per_insert * min_size_to_sample. If the sampler cannot '
'sample concurrently, this will result in a deadlock as soon as '
'min_size_to_sample items have been inserted.')
if min_diff > samples_per_insert * min_size_to_sample:
raise ValueError(
'The range covered by error_buffer is above '
'samples_per_insert * min_size_to_sample. This will result in a '
'deadlock as soon as min_size_to_sample items have been inserted.'
)
if min_size_to_sample < 1:
raise ValueError(
f'min_size_to_sample ({min_size_to_sample}) must be a positive '
f'integer')
super().__init__(
pybind.RateLimiter(samples_per_insert=samples_per_insert,
min_size_to_sample=min_size_to_sample,
min_diff=min_diff,
max_diff=max_diff))
def __init__(self, size: int):
"""Constructor of Stack (do not use directly).
Args:
size: Maximum size of the stack.
"""
super().__init__(
pybind.RateLimiter(samples_per_insert=1.0,
min_size_to_sample=1,
min_diff=0.0,
max_diff=size))
def __init__(self, min_size_to_sample: int):
if min_size_to_sample < 1:
raise ValueError(
f'min_size_to_sample ({min_size_to_sample}) must be a positive '
f'integer')
super().__init__(
pybind.RateLimiter(samples_per_insert=1.0,
min_size_to_sample=min_size_to_sample,
min_diff=-sys.float_info.max,
max_diff=sys.float_info.max))
def __init__(self, samples_per_insert: float, min_size_to_sample: int,
min_diff: float, max_diff: float):
self._samples_per_insert = samples_per_insert
self._min_size_to_sample = min_size_to_sample
self._min_diff = min_diff
self._max_diff = max_diff
self.internal_limiter = pybind.RateLimiter(
samples_per_insert=samples_per_insert,
min_size_to_sample=min_size_to_sample,
min_diff=min_diff,
max_diff=max_diff)