jax-ml/jax · error · ValueError

contains duplicated factors

Error message

{kind} contains duplicated factors

What it means

The check_special_factors helper verifies the reduction/need-replication/permutation factor sets: the same factor appearing twice within one such tuple is rejected because each set must contain distinct factors.

Solutions

  1. Deduplicate while preserving order, e.g. tuple(dict.fromkeys(factors))
  2. Fix the source list so each factor appears once

Example fix

# before
reduction_factors = ('m', 'm')
# after
reduction_factors = ('m',)
Defensive patterns

Strategy: validation

Validate before calling

assert len(factors) == len(set(factors)), f'duplicates: {factors}'

Type guard

def no_dup_factors(factors: tuple) -> bool:
    return len(factors) == len(set(factors))

Prevention

When it happens

Trigger: reduction_factors=('m','m') passed to def_partition.

Common situations: Concatenating factor lists programmatically and accidentally repeating an entry.

Related errors

AI-assisted analysis of jax-ml/jax@1e1c6a8fc0 (2026-08-27). Data as JSON: /api/errors/dd6521a2bf5b198b. Report an issue: GitHub.

Appendix: source

Thrown at jax/_src/custom_partitioning_sharding_rule.py:166

    # factor_sizes and factors that are never used for a whole dimension are
    # in factor_sizes.
    for factor, inferable in factors_inferrable.items():
      if factor not in factor_sizes and not inferable:
        raise ValueError(
          f"Factor {factor} is only used in compound factors; must specify"
          " its size")
      if factor in factor_sizes and inferable:
        raise ValueError(
          f"Factor {factor} represents a whole dimension; do not specify its"
          " size")

    special_factors = set()
    def check_special_factors(kind, factors):
      if not isinstance(factors, tuple):
        raise ValueError(f"{kind} must be a tuple of factors")

      if len(factors) != len(set(factors)):
        raise ValueError(f"{kind} contains duplicated factors")

      for factor in factors:
        if factor not in factors_inferrable:
          raise ValueError(
            f"Factor {factor} in {kind} is not used in the rule")
        if factor in special_factors:
          raise ValueError(f"Factor {factor} can only be in one of the "
              f"reduction, need replication, or permutation factor sets.")
        special_factors.add(factor)

    check_special_factors("reduction_factors", reduction_factors)
    check_special_factors("need_replication_factors", need_replication_factors)
    check_special_factors("permutation_factors", permutation_factors)

    self.operand_mappings = operand_mappings
    self.result_mappings = result_mappings
    self.factor_sizes = factor_sizes
    self.reduction_factors = reduction_factors

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