parameters: (a, dtype=None, order=None)
return_statement: return a
docstring: Convert the input to an array, checking for NaNs or Infs.
  
      Parameters
      ----------
      a : array_like
          Input data, in any form that can be converted to an array.  This
          includes lists, lists of tuples, tuples, tuples of tuples, tuples
          of lists and ndarrays.  Success requires no NaNs or Infs.
      dtype : data-type, optional
          By default, the data-type is inferred from the input data.
      order : {'C', 'F'}, optional
           Whether to use row-major (C-style) or
           column-major (Fortran-style) memory representation.
           Defaults to 'C'.
  
      Returns
      -------
      out : ndarray
          Array interpretation of `a`.  No copy is performed if the input
          is already an ndarray.  If `a` is a subclass of ndarray, a base
          class ndarray is returned.
  
      Raises
      ------
      ValueError
          Raises ValueError if `a` contains NaN (Not a Number) or Inf (Infinity).
  
      See Also
      --------
      asarray : Create and array.
      asanyarray : Similar function which passes through subclasses.
      ascontiguousarray : Convert input to a contiguous array.
      asfarray : Convert input to a floating point ndarray.
      asfortranarray : Convert input to an ndarray with column-major
                       memory order.
      fromiter : Create an array from an iterator.
      fromfunction : Construct an array by executing a function on grid
                     positions.
  
      Examples
      --------
      Convert a list into an array.  If all elements are finite
      ``asarray_chkfinite`` is identical to ``asarray``.
  
      >>> a = [1, 2]
      >>> np.asarray_chkfinite(a, dtype=float)
      array([1., 2.])
  
      Raises ValueError if array_like contains Nans or Infs.
  
      >>> a = [1, 2, np.inf]
      >>> try:
      ...     np.asarray_chkfinite(a)
      ... except ValueError:
      ...     print('ValueError')
      ...
      ValueError
docstring_summary: Convert the input to an array, checking for NaNs or Infs.
docstring_tokens: Convert the input to an array checking for NaNs or Infs .
function: def asarray_chkfinite(a, dtype=None, order=None):
      """Convert the input to an array, checking for NaNs or Infs.
  
      Parameters
      ----------
      a : array_like
          Input data, in any form that can be converted to an array.  This
          includes lists, lists of tuples, tuples, tuples of tuples, tuples
          of lists and ndarrays.  Success requires no NaNs or Infs.
      dtype : data-type, optional
          By default, the data-type is inferred from the input data.
      order : {'C', 'F'}, optional
           Whether to use row-major (C-style) or
           column-major (Fortran-style) memory representation.
           Defaults to 'C'.
  
      Returns
      -------
      out : ndarray
          Array interpretation of `a`.  No copy is performed if the input
          is already an ndarray.  If `a` is a subclass of ndarray, a base
          class ndarray is returned.
  
      Raises
      ------
      ValueError
          Raises ValueError if `a` contains NaN (Not a Number) or Inf (Infinity).
  
      See Also
      --------
      asarray : Create and array.
      asanyarray : Similar function which passes through subclasses.
      ascontiguousarray : Convert input to a contiguous array.
      asfarray : Convert input to a floating point ndarray.
      asfortranarray : Convert input to an ndarray with column-major
                       memory order.
      fromiter : Create an array from an iterator.
      fromfunction : Construct an array by executing a function on grid
                     positions.
  
      Examples
      --------
      Convert a list into an array.  If all elements are finite
      ``asarray_chkfinite`` is identical to ``asarray``.
  
      >>> a = [1, 2]
      >>> np.asarray_chkfinite(a, dtype=float)
      array([1., 2.])
  
      Raises ValueError if array_like contains Nans or Infs.
  
      >>> a = [1, 2, np.inf]
      >>> try:
      ...     np.asarray_chkfinite(a)
      ... except ValueError:
      ...     print('ValueError')
      ...
      ValueError
  
      """
      a = asarray(a, dtype=dtype, order=order)
      if a.dtype.char in typecodes['AllFloat'] and not np.isfinite(a).all():
          raise ValueError(
              "array must not contain infs or NaNs")
      return a
function_tokens: def asarray_chkfinite ( a , dtype = None , order = None ) : a = asarray ( a , dtype = dtype , order = order ) if a . dtype . char in typecodes [ 'AllFloat' ] and not np . isfinite ( a ) . all ( ) : raise ValueError ( "array must not contain infs or NaNs" ) return a