jax-ml/jax · error · ValueError

Expected kind to be on of

Error message

Expected kind to be on of: {valid_kind}; got {kind}

What it means

Raised by jax.scipy.linalg.lesp... actually the matrix-generation helper (e.g. hadamard/pascal-family) when the `kind` argument is not one of 'symmetric', 'lower', 'upper'. JAX validates the string up front because downstream code branches on it. It mirrors scipy's parameter but with eager checking.

Solutions

1. Set kind to one of the exact strings 'symmetric', 'lower', or 'upper'
2. Check for leading/trailing whitespace or wrong case in the string
3. If kind came from config/CLI input, normalize and validate it before passing

Example fix

# before
linalg.pascal(n, kind='Lower')
# after
linalg.pascal(n, kind='lower')

if kind not in ('symmetric','lower','upper'): raise ValueError(kind)

def is_valid_kind(k: str) -> bool: return k in ('symmetric', 'lower', 'upper')

When it happens

Trigger: Calling the public linalg routine with kind='Low', kind='diag', or any misspelled/unsupported string; default is 'symmetric' when kind is None.

Common situations: Porting scipy code that used a different spelling, passing kind positionally with the wrong argument order, or typos/case mismatches.

Understand the failure class

Background: "invalid argument", "unknown mode", "not supported": invalid enum-like argument errors explained — this error's family across 19 libraries.

Related errors

• Expected kind to be one of
• ind must be a positive integer; got
• n must be a positive power of 2; got
• scale must be None, 'sqrtn', or 'n'; got
• Unrecognized method . The two valid methods are either…

AI-assisted analysis of jax-ml/jax@1e1c6a8fc0 (2026-08-27). Data as JSON: /api/errors/7708adbbcf38bf90. Report an issue: GitHub.

Appendix: source

Thrown at jax/_src/scipy/linalg.py:3008

     [1. 1. 0.]
     [1. 2. 1.]]
    [[1. 1. 1. 1.]
     [0. 1. 2. 3.]
     [0. 0. 1. 3.]
     [0. 0. 0. 1.]]
    [[ 1.  1.  1.  1.  1.]
     [ 1.  2.  3.  4.  5.]
     [ 1.  3.  6. 10. 15.]
     [ 1.  4. 10. 20. 35.]
     [ 1.  5. 15. 35. 70.]]
  """
  if kind is None:
    kind = "symmetric"

  valid_kind = ["symmetric", "lower", "upper"]

  if kind not in valid_kind:
    raise ValueError(f"Expected kind to be on of: {valid_kind}; got {kind}")

  a = jnp.arange(n, dtype=np.float32)

  L_n = _binom(a[:, None], a[None, :])

  if kind == "lower":
    return L_n

  if kind == "upper":
    return L_n.T

  return jnp.dot(L_n, L_n.T)

@jit
def _binom(n, k):
  a = lax.lgamma(n + 1.0)
  b = lax.lgamma(n - k + 1.0)
  c = lax.lgamma(k + 1.0)

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