jax.numpy.nanprod(a, axis=None, dtype=None, out=None, keepdims=False, initial=None, where=None)[source]#

Return the product of array elements over a given axis treating Not a

LAX-backend implementation of numpy.nanprod().

Original docstring below.

Numbers (NaNs) as ones.

One is returned for slices that are all-NaN or empty.

Added in version 1.10.0.

  • a (array_like) – Array containing numbers whose product is desired. If a is not an array, a conversion is attempted.

  • axis ({int, tuple of int, None}, optional) – Axis or axes along which the product is computed. The default is to compute the product of the flattened array.

  • dtype (data-type, optional) – The type of the returned array and of the accumulator in which the elements are summed. By default, the dtype of a is used. An exception is when a has an integer type with less precision than the platform (u)intp. In that case, the default will be either (u)int32 or (u)int64 depending on whether the platform is 32 or 64 bits. For inexact inputs, dtype must be inexact.

  • keepdims (bool, optional) – If True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original arr.

  • initial (scalar, optional) – The starting value for this product. See ~numpy.ufunc.reduce for details.

  • where (array_like of bool, optional) – Elements to include in the product. See ~numpy.ufunc.reduce for details.

  • out (None)


nanprod – A new array holding the result is returned unless out is specified, in which case it is returned.

Return type: