huggingface/transformers · error · ValueError

min_value must be greater than zero

Error message

min_value must be greater than zero

What it means

Raised at the top of transformers.audio_utils.power_to_db when min_value <= 0.0. min_value is used as the clip floor before log10 (np.clip(spectrogram, a_min=min_value)) to avoid log(0); a non-positive floor would leave zeros/negatives in the array and produce -inf/NaN dB values, so it is rejected.

Source

Thrown at src/transformers/audio_utils.py:1267

        spectrogram (`np.ndarray`):
            The input power (mel) spectrogram. Note that a power spectrogram has the amplitudes squared!
        reference (`float`, *optional*, defaults to 1.0):
            Sets the input spectrogram value that corresponds to 0 dB. For example, use `np.max(spectrogram)` to set
            the loudest part to 0 dB. Must be greater than zero.
        min_value (`float`, *optional*, defaults to `1e-10`):
            The spectrogram will be clipped to this minimum value before conversion to decibels, to avoid taking
            `log(0)`. The default of `1e-10` corresponds to a minimum of -100 dB. Must be greater than zero.
        db_range (`float`, *optional*):
            Sets the maximum dynamic range in decibels. For example, if `db_range = 80`, the difference between the
            peak value and the smallest value will never be more than 80 dB. Must be greater than zero.

    Returns:
        `np.ndarray`: the spectrogram in decibels
    """
    if reference <= 0.0:
        raise ValueError("reference must be greater than zero")
    if min_value <= 0.0:
        raise ValueError("min_value must be greater than zero")

    reference = max(min_value, reference)

    spectrogram = np.clip(spectrogram, a_min=min_value, a_max=None)
    spectrogram = 10.0 * (np.log10(spectrogram) - np.log10(reference))

    if db_range is not None:
        if db_range <= 0.0:
            raise ValueError("db_range must be greater than zero")
        spectrogram = np.clip(spectrogram, a_min=spectrogram.max() - db_range, a_max=None)

    return spectrogram


def power_to_db_batch(
    spectrogram: np.ndarray,
    reference: float = 1.0,
    min_value: float = 1e-10,

View on GitHub (pinned to a597f97485)

Solutions

1. Keep min_value strictly positive; the default 1e-10 corresponds to a -100 dB floor
2. To make the floor negligible, use a tiny positive value like 1e-12 instead of 0
3. Validate serialized configs at load time and rewrite non-positive min_value to the default

Example fix

// before
db = power_to_db(spec, min_value=0.0)
// after
db = power_to_db(spec, min_value=1e-12)

min_value = min_value if min_value and min_value > 0 else 1e-10
db = power_to_db(spec, min_value=min_value)

def is_positive_floor(min_value) -> bool:
    return isinstance(min_value, (int, float)) and min_value > 0.0

try:
    db = power_to_db(spec, min_value=min_value)
except ValueError as e:
    if "min_value must be greater than zero" in str(e):
        db = power_to_db(spec)  # default floor 1e-10
    else:
        raise

When it happens

Trigger: Calling power_to_db(spec, min_value=0.0) or a negative value; happens when someone 'disables' the floor by setting 0, or when min_value is loaded from a config that stored 0/-1 as a placeholder.

Common situations: Trying to get an unclipped dB trace by setting min_value=0; copying settings between power_to_db (default 1e-10) and amplitude_to_db (default 1e-5) and zeroing the wrong field; configs generated with placeholder zeros.

Related errors

• reference must be greater than zero
• db_range must be greater than zero
• Unexpected fields in the request: {unexpected}
• PUSH_TO_HUB_TOKEN is not set, cannot push results to the Hub
• Invalid input type. Must be a single audio or a list of audi

AI-assisted analysis of huggingface/transformers@a597f97485 (2026-08-14). Data as JSON: /api/errors/04d39ec7f3205f7a. Report an issue: GitHub.