Unity-Technologies/ml-agents · error · TrainerConfigError

The sampling interval {interval} must contain exactly two va

Error message

The sampling interval {interval} must contain exactly two values.

What it means

MultiRangeUniformSamplerSettings validates its `intervals` via an attrs validator requiring every interval to be exactly a two-element [min, max] pair. An interval with any other length cannot be interpreted as a range and raises this error.

Source

Thrown at ml-agents/mlagents/trainers/settings.py:433

@attr.s(auto_attribs=True)
class MultiRangeUniformSettings(ParameterRandomizationSettings):
    intervals: List[Tuple[float, float]] = attr.ib()

    def __str__(self) -> str:
        """
        Helper method to output sampler stats to console.
        """
        return f"MultiRangeUniform sampler: intervals={self.intervals}"

    @intervals.default
    def _intervals_default(self):
        return [[0.0, 1.0]]

    @intervals.validator
    def _check_intervals(self, attribute, value):
        for interval in self.intervals:
            if len(interval) != 2:
                raise TrainerConfigError(
                    f"The sampling interval {interval} must contain exactly two values."
                )
            min_value, max_value = interval
            if min_value > max_value:
                raise TrainerConfigError(
                    f"Minimum value is greater than maximum value in interval {interval}."
                )

    def apply(self, key: str, env_channel: EnvironmentParametersChannel) -> None:
        """
        Helper method to send sampler settings over EnvironmentParametersChannel
        Calls the multirangeuniform sampler type set method.
        :param key: environment parameter to be sampled
        :param env_channel: The EnvironmentParametersChannel to communicate sampler settings to environment
        """
        env_channel.set_multirangeuniform_sampler_parameters(
            key, self.intervals, self.seed
        )

View on GitHub (pinned to 3ecb446f75)

Solutions

1. Ensure each interval has exactly two numbers: [min_value, max_value].
2. Remove extra elements or split multi-point entries into separate intervals.
3. Print/parse the YAML to confirm the intervals structure is a list of 2-element lists.

Example fix

# before
intervals: [[0.0, 1.0, 2.0]]

# after
intervals: [[0.0, 1.0], [1.5, 2.0]]

for iv in spec['sampler_parameters']['intervals']:
    if len(iv) != 2:
        raise ValueError(f'interval {iv} must contain exactly two values')

def are_valid_intervals(intervals) -> bool:
    return isinstance(intervals, list) and all(isinstance(i, (list, tuple)) and len(i) == 2 for i in intervals)

try:
    sampler = MultiRangeUniformSamplerSettings(**sp)
except TrainerConfigError as e:
    print(f'Fix intervals: {e}')
    raise

When it happens

Trigger: Providing intervals like [[0.0, 1.0, 2.0]] or [[1.0]] in a multirangeuniform sampler configuration.

Common situations: Adding a third element (e.g. a weight or step) to an interval, or a YAML list accidentally flattened/nested incorrectly.

Related errors

• Minimum value is greater than maximum value in uniform sampl
• Minimum value is greater than maximum value in interval {int
• Unsupported parameter randomization configuration {d}.
• When using a recurrent network, memory size must be divisibl
• Unsupported reward signal configuration {d}.

AI-assisted analysis of Unity-Technologies/ml-agents@3ecb446f75 (2026-09-02). Data as JSON: /api/errors/0c800b6359446207. Report an issue: GitHub.