tensorflow/models · error · ValueError
positive_fraction should be in range [0,1]. Received: %s.
Error message
positive_fraction should be in range [0,1]. Received: %s.
What it means
Error "positive_fraction should be in range [0,1]. Received: %s." thrown in tensorflow/models.
Source
Thrown at official/vision/ops/sampling_ops.py:134
tf.stack(indices_shape + params_shape[1:]))
class BalancedPositiveNegativeSampler:
"""Subsamples minibatches to a desired balance of positives and negatives."""
def __init__(self, positive_fraction=0.5, is_static=False):
"""Constructs a minibatch sampler.
Args:
positive_fraction: desired fraction of positive examples (scalar in [0,1])
in the batch.
is_static: If True, uses an implementation with static shape guarantees.
Raises:
ValueError: if positive_fraction < 0, or positive_fraction > 1
"""
if positive_fraction < 0 or positive_fraction > 1:
raise ValueError('positive_fraction should be in range [0,1]. '
'Received: %s.' % positive_fraction)
self._positive_fraction = positive_fraction
self._is_static = is_static
@staticmethod
def subsample_indicator(indicator, num_samples):
"""Subsample indicator vector.
Given a boolean indicator vector with M elements set to `True`, the function
assigns all but `num_samples` of these previously `True` elements to
`False`. If `num_samples` is greater than M, the original indicator vector
is returned.
Args:
indicator: a 1-dimensional boolean tensor indicating which elements
are allowed to be sampled and which are not.
num_samples: int32 scalar tensor
View on GitHub (pinned to e006f5f0d5)
Solutions
- Set positive_fraction to a value within [0, 1].
- Fix the sampler config; typical values are around 0.5.
When it happens
Trigger: Thrown at official/vision/ops/sampling_ops.py:134 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24).
Data as JSON: /api/errors/b5dbe6c289c8c31a.
Report an issue: GitHub.