docstr: ivy.Array instance method variant of ivy.linear. This method simply
  wraps the function, and so the docstring for ivy.linear also applies to
  this method with minimal changes.
  
  Parameters
  ----------
  self
      The input array to compute linear transformation on.
      *[outer_batch_shape,inner_batch_shape,in_features]*
  weight
      The weight matrix. *[outer_batch_shape,out_features,in_features]*
  bias
      The bias vector, default is ``None``. *[outer_batch_shape,out_features]*
  out
      optional output array, for writing the result to. It must have a shape
      that the inputs broadcast to.
  
  Returns
  -------
  ret
      Result array of the linear transformation.
      *[outer_batch_shape,inner_batch_shape,out_features]*
  
  Examples
  --------
  >>> x = ivy.array([[1.1, 2.2, 3.3],                            [4.4, 5.5, 6.6],                            [7.7, 8.8, 9.9]])
  >>> w = ivy.array([[1., 2., 3.],                            [4., 5., 6.],                            [7., 8., 9.]])
  >>> b = ivy.array([1., 0., -1.])
  >>> y = x.linear(w, bias=b)
  >>> print(y)
  ivy.array([[ 16.4,  35.2,  54. ],
             [ 36.2,  84.7, 133. ],
             [ 56. , 134. , 212. ]])
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code: def linear(
      self: ivy.Array,
      weight: Union[ivy.Array, ivy.NativeArray],
      /,
      *,
      bias: Optional[Union[ivy.Array, ivy.NativeArray]] = None,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """ivy.Array instance method variant of ivy.linear. This method simply
          wraps the function, and so the docstring for ivy.linear also applies to
          this method with minimal changes.
  
          Parameters
          ----------
          self
              The input array to compute linear transformation on.
              *[outer_batch_shape,inner_batch_shape,in_features]*
          weight
              The weight matrix. *[outer_batch_shape,out_features,in_features]*
          bias
              The bias vector, default is ``None``. *[outer_batch_shape,out_features]*
          out
              optional output array, for writing the result to. It must have a shape
              that the inputs broadcast to.
  
          Returns
          -------
          ret
              Result array of the linear transformation.
              *[outer_batch_shape,inner_batch_shape,out_features]*
  
          Examples
          --------
          >>> x = ivy.array([[1.1, 2.2, 3.3], \
                             [4.4, 5.5, 6.6], \
                             [7.7, 8.8, 9.9]])
          >>> w = ivy.array([[1., 2., 3.], \
                             [4., 5., 6.], \
                             [7., 8., 9.]])
          >>> b = ivy.array([1., 0., -1.])
          >>> y = x.linear(w, bias=b)
          >>> print(y)
          ivy.array([[ 16.4,  35.2,  54. ],
                     [ 36.2,  84.7, 133. ],
                     [ 56. , 134. , 212. ]])
          """
      return ivy.linear(
          self._data,
          weight,
          bias=bias,
          out=out,
      )
  
file_path: ivy/ivy/data_classes/array/layers.py
imports: import abc
  from typing import Optional, Tuple, Union, List, Sequence
  import ivy
label_desc: Use image node_id 1 for calling the _ArrayWithLayers obj's underlying member method code with example usage: obj.linear() and returns: ivy