jax-ml/jax · error · TypeError

array() got multiple values for argument

Error message

array() got multiple values for argument '{name}'

What it means

When copy/order/ndmin are supplied positionally as *args, jnp.array checks whether the same option was ALSO given as a keyword. If both positional and keyword values are present, it raises this 'multiple values' TypeError like a normal Python signature would.

Solutions

1. Use keyword arguments exclusively for copy, order, ndmin
2. Audit call sites mixing positional and keyword forms of these three options

Example fix

# before
a = jnp.array(x, True, ndmin=1)
# after
a = jnp.array(x, copy=True, ndmin=1)

# ensure copy/order/ndmin passed only once, as keywords
assert not positional_copy_order_ndmin, 'use keywords'

null

null

When it happens

Trigger: jnp.array(x, True, ndmin=1) — copy passed positionally and ndmin also as keyword — where the positional slot conflicts with a non-default keyword value.

Common situations: Migrating old NumPy-style positional calls while partially modernizing some arguments to keywords; positional use is deprecated anyway.

Related errors

• array() takes at most 5 positional arguments but
• a_scale and b_scale must both be present or absent.
• args argument to jax.scipy.optimize.minimize must be a…
• Argument ' ' of type is not a valid JAX type.
• Argument ' ' of type ' ' is not a valid JAX type

AI-assisted analysis of jax-ml/jax@1e1c6a8fc0 (2026-08-27). Data as JSON: /api/errors/5b5133face47cd37. Report an issue: GitHub.

Appendix: source

Thrown at jax/_src/numpy/array_constructors.py:188

    Array([0. , 0.5, 1. , 1.5, 2. ], dtype=float32)

    Constructing a JAX array via the Python buffer interface, using Python's
    built-in :mod:`array` module.

    >>> from array import array
    >>> pybuffer = array('i', [2, 3, 5, 7])
    >>> jnp.array(pybuffer)
    Array([2, 3, 5, 7], dtype=int32)

  .. _explicit sharding: https://docs.jax.dev/en/latest/parallel.html
  """
  if args:
    if len(args) > 3:
      raise TypeError(f"array() takes at most 5 positional arguments but {len(args) + 2} were given")

    for i, name in enumerate(["copy", "order", "ndmin"]):
      if i < len(args) and [copy, order, ndmin][i] != [True, "K", 0][i]:
        raise TypeError(f"array() got multiple values for argument '{name}'")
    copy, order, ndmin = (list(args) + [copy, order, ndmin][len(args):])[:3]

    deprecations.warn(
        "jax-array-positional-args",
        "Passing the copy, order, and ndmin arguments to jnp.array positionally "
        "is deprecated. Use keyword arguments instead.",
        stacklevel=2)

  if order is not None and order != "K":
    raise NotImplementedError("Only implemented for order='K'")

  # Fast path: if we're not actually doing any conversion, in many cases we
  # can call lax.stage to lift the value into the trace.
  if dtype is None and device is None and out_sharding is None and ndmin == 0:
    if isinstance(object, core.Tracer) and not core.is_concrete(object):
      return lax._array_copy(object) if copy else object
    if isinstance(object, (int, float, complex, np.number)):
      return lax.stage(object)

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