rohitg00/ai-engineering-from-scratch · error · ValueError

step must be non-negative, got {step}

Error message

step must be non-negative, got {step}

What it means

Error "step must be non-negative, got {step}" thrown in rohitg00/ai-engineering-from-scratch.

Source

Thrown at phases/19-capstone-projects/44-cosine-lr-warmup/code/main.py:70

    lr_min: float = 0.0

    def __post_init__(self) -> None:
        if self.warmup_steps < 0:
            raise ValueError("warmup_steps must be non-negative")
        if self.total_steps <= 0:
            raise ValueError("total_steps must be positive")
        if self.warmup_steps >= self.total_steps:
            raise ValueError("warmup_steps must be less than total_steps")
        if self.lr_max <= 0:
            raise ValueError("lr_max must be positive")
        if self.lr_min < 0:
            raise ValueError("lr_min must be non-negative")
        if self.lr_min > self.lr_max:
            raise ValueError("lr_min must not exceed lr_max")

    def lr(self, step: int) -> float:
        if step < 0:
            raise ValueError(f"step must be non-negative, got {step}")
        if self.warmup_steps > 0 and step <= self.warmup_steps:
            return self.lr_max * (step / self.warmup_steps)
        if step >= self.total_steps:
            return self.lr_min
        decay_span = max(1, self.total_steps - self.warmup_steps)
        progress = (step - self.warmup_steps) / decay_span
        cosine = 0.5 * (1.0 + math.cos(math.pi * progress))
        return self.lr_min + (self.lr_max - self.lr_min) * cosine

    def points(self, num_steps: int | None = None) -> list[tuple[int, float]]:
        upper = self.total_steps if num_steps is None else num_steps
        if upper <= 0:
            return []
        return [(step, self.lr(step)) for step in range(upper + 1)]


@dataclass
class StepLog:

View on GitHub (pinned to 39ea8a1c6d)

When it happens

Trigger: Thrown at phases/19-capstone-projects/44-cosine-lr-warmup/code/main.py:70 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of rohitg00/ai-engineering-from-scratch@39ea8a1c6d (2026-08-26). Data as JSON: /api/errors/6e93d6740695a89c. Report an issue: GitHub.