docstr: ivy.Array instance method variant of ivy.vector_norm. This method
  computes the vector norm of a vector (or batch of vectors).
  
  Parameters
  ----------
  self
      Input array. Should have a floating-point data type.
  axis
      If an integer, ``axis`` specifies the axis (dimension) along which to
      compute vector norms. If an n-tuple, ``axis`` specifies the axes
      (dimensions) along which to compute batched vector norms. If ``None``,
      the vector norm must be computed over all array values (i.e., equivalent
      to computing the vector norm of a flattened array). Negative indices are
      also supported. Default: ``None``.
  keepdims
      If ``True``, the axes (dimensions) specified by ``axis`` must be included
      in the result as singleton dimensions, and, accordingly, the result must be
      compatible with the input array (see :ref:`broadcasting`). Otherwise, if
      ``False``, the axes (dimensions) specified by ``axis`` must not be included
      in the result.
      Default: ``False``.
  ord
      order of the norm. The following mathematical norms are supported:
  
      +------------------+----------------------------+
      | ord              | description                |
      +==================+============================+
      | 1                | L1-norm (Manhattan)        |
      +------------------+----------------------------+
      | 2                | L2-norm (Euclidean)        |
      +------------------+----------------------------+
      | inf              | infinity norm              |
      +------------------+----------------------------+
      | (int,float >= 1) | p-norm                     |
      +------------------+----------------------------+
  
      The following non-mathematical "norms" are also supported:
  
      +------------------+--------------------------------+
      | ord              | description                    |
      +==================+================================+
      | 0                | sum(a != 0)                    |
      +------------------+--------------------------------+
      | -inf             | min(abs(a))                    |
      +------------------+--------------------------------+
      | (int,float < 1)  | sum(abs(a)**ord)**(1./ord)     |
      +------------------+--------------------------------+
  
      Default: ``2``.
  dtype
      data type that may be used to perform the computation more precisely.
      The input array ``self`` gets cast to ``dtype`` before the function's
      computations.
  out
      optional output array, for writing the result to. It must have a shape
      that the inputs broadcast to.
  
  Returns
  -------
  ret
      an array containing the vector norms. If ``axis`` is ``None``, the returned
      array must be a zero-dimensional array containing a vector norm. If ``axis``
      is a scalar value (``int`` or ``float``), the returned array must have a
      rank which is one less than the rank of ``self``. If ``axis`` is a
      ``n``-tuple, the returned array must have a rank which is ``n`` less than
      the rank of ``self``. The returned array must have a floating-point data
      type determined by :ref:`type-promotion`.
  
  Examples
  --------
  >>> x = ivy.array([1., 2., 3.])
  >>> y = x.vector_norm()
  >>> print(y)
  ivy.array([3.7416575])
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code: def vector_norm(
      self: ivy.Array,
      /,
      *,
      axis: Optional[Union[int, Sequence[int]]] = None,
      keepdims: bool = False,
      ord: Union[int, float, Literal[inf, -inf]] = 2,
      dtype: Optional[Union[ivy.Dtype, ivy.NativeDtype]] = None,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """ivy.Array instance method variant of ivy.vector_norm. This method
      computes the vector norm of a vector (or batch of vectors).
  
      Parameters
      ----------
      self
          Input array. Should have a floating-point data type.
      axis
          If an integer, ``axis`` specifies the axis (dimension) along which to
          compute vector norms. If an n-tuple, ``axis`` specifies the axes
          (dimensions) along which to compute batched vector norms. If ``None``,
          the vector norm must be computed over all array values (i.e., equivalent
          to computing the vector norm of a flattened array). Negative indices are
          also supported. Default: ``None``.
      keepdims
          If ``True``, the axes (dimensions) specified by ``axis`` must be included
          in the result as singleton dimensions, and, accordingly, the result must be
          compatible with the input array (see :ref:`broadcasting`). Otherwise, if
          ``False``, the axes (dimensions) specified by ``axis`` must not be included
          in the result.
          Default: ``False``.
      ord
          order of the norm. The following mathematical norms are supported:
  
          +------------------+----------------------------+
          | ord              | description                |
          +==================+============================+
          | 1                | L1-norm (Manhattan)        |
          +------------------+----------------------------+
          | 2                | L2-norm (Euclidean)        |
          +------------------+----------------------------+
          | inf              | infinity norm              |
          +------------------+----------------------------+
          | (int,float >= 1) | p-norm                     |
          +------------------+----------------------------+
  
          The following non-mathematical "norms" are also supported:
  
          +------------------+--------------------------------+
          | ord              | description                    |
          +==================+================================+
          | 0                | sum(a != 0)                    |
          +------------------+--------------------------------+
          | -inf             | min(abs(a))                    |
          +------------------+--------------------------------+
          | (int,float < 1)  | sum(abs(a)**ord)**(1./ord)     |
          +------------------+--------------------------------+
  
          Default: ``2``.
      dtype
          data type that may be used to perform the computation more precisely.
          The input array ``self`` gets cast to ``dtype`` before the function's
          computations.
      out
          optional output array, for writing the result to. It must have a shape
          that the inputs broadcast to.
  
      Returns
      -------
      ret
          an array containing the vector norms. If ``axis`` is ``None``, the returned
          array must be a zero-dimensional array containing a vector norm. If ``axis``
          is a scalar value (``int`` or ``float``), the returned array must have a
          rank which is one less than the rank of ``self``. If ``axis`` is a
          ``n``-tuple, the returned array must have a rank which is ``n`` less than
          the rank of ``self``. The returned array must have a floating-point data
          type determined by :ref:`type-promotion`.
  
      Examples
      --------
      >>> x = ivy.array([1., 2., 3.])
      >>> y = x.vector_norm()
      >>> print(y)
      ivy.array([3.7416575])
      """
      return ivy.vector_norm(
          self._data,
          axis=axis,
          keepdims=keepdims,
          ord=ord,
          dtype=dtype,
          out=out,
      )
  
imports: import abc
  from typing import Union, Optional, Literal, Tuple, List, Sequence
  import ivy
label_desc: Use image node_id 27 for calling the _ArrayWithLinearAlgebra obj's underlying member method code with example usage: obj.vector_norm() and returns: ivy