jax-ml/jax · error · ValueError

Unknown boundary option '{boundary}', must be one of: {list(

Error message

Unknown boundary option '{boundary}', must be one of: {list(boundary_funcs.keys())}

What it means

The boundary argument of the spectral functions selects how each segment is extended before windowing; JAX implements only 'even', 'odd', 'zeros', and None (None skips extension). Any other string is rejected with the list of valid keys.

Source

Thrown at jax/_src/scipy/signal.py:650

  def make_pad(mode, **kwargs):
    def pad(x, n, axis=-1):
      pad_width = [(0, 0) for unused_n in range(x.ndim)]
      pad_width[axis] = (n, n)
      return jnp.pad(x, pad_width, mode, **kwargs)
    return pad

  boundary_funcs = {
      'even': make_pad('reflect'),
      'odd': odd_ext,
      'constant': make_pad('edge'),
      'zeros': make_pad('constant', constant_values=0.0),
      None: lambda x, *args, **kwargs: x
  }

  # Check/ normalize inputs
  if boundary not in boundary_funcs:
    raise ValueError(
        f"Unknown boundary option '{boundary}', "
        f"must be one of: {list(boundary_funcs.keys())}")

  axis = core.concrete_or_error(operator.index, axis, "axis of windowed-FFT")
  axis = canonicalize_axis(axis, x.ndim)

  if y is None:
    check_arraylike('spectral_helper', x)
    x, = promote_dtypes_inexact(x)
    y_arr = x  # place-holder for type checking
    outershape = tuple_delete(x.shape, axis)
  else:
    if mode != 'psd':
      raise ValueError("two-argument mode is available only when mode=='psd'")
    check_arraylike('spectral_helper', x, y)
    x, y_arr = promote_dtypes_inexact(x, y)
    if x.ndim != y_arr.ndim:
      raise ValueError("two-arguments must have the same rank ({x.ndim} vs {y.ndim}).")

View on GitHub (pinned to 1e1c6a8fc0)

Solutions

1. Use one of 'even', 'odd', 'zeros', or None
2. Pass boundary=None and pre-pad manually if you need other extension semantics

Example fix

// before
jax.scipy.signal.stft(x, boundary='symmetric')
// after
jax.scipy.signal.stft(x, boundary='even')
# or pre-pad: jax.scipy.signal.stft(jnp.pad(x,(k,k)), boundary=None)

BOUNDARIES = ('even', 'odd', 'zeros', None)
assert boundary in BOUNDARIES, f'boundary must be one of {BOUNDARIES}'

def is_valid_boundary(b) -> bool:
    return b in ('even', 'odd', 'zeros', None)

When it happens

Trigger: jax.scipy.signal.stft(x, boundary='reflect') or 'constant' (scipy pad-style names); boundary='' from an unset config.

Common situations: Confusing jnp.pad mode names ('wrap', 'symmetric') with the boundary vocabulary; porting code from other STFT implementations.

Related errors

• unsupported mode: {mode}
• Got {method=}; expected 'auto', 'fft', or 'direct'.
• convolve2d() only supports boundary='fill', fillvalue=0
• correlate2d() only supports boundary='fill', fillvalue=0
• Trend type must be 'linear' or 'constant'.

AI-assisted analysis of jax-ml/jax@1e1c6a8fc0 (2026-08-27). Data as JSON: /api/errors/daa0e3bc33225325. Report an issue: GitHub.