parameters: (self, x, adjoint=False, name="matvec")
docstring: Transform [batch] vector `x` with left multiplication:  `x --> Ax`.
  
      ```python
      # Make an operator acting like batch matric A.  Assume A.shape = [..., M, N]
      operator = LinearOperator(...)
  
      X = ... # shape [..., N], batch vector
  
      Y = operator.matvec(X)
      Y.shape
      ==> [..., M]
  
      Y[..., :] = sum_j A[..., :, j] X[..., j]
      ```
  
      Args:
        x: `Tensor` with compatible shape and same `dtype` as `self`.
          `x` is treated as a [batch] vector meaning for every set of leading
          dimensions, the last dimension defines a vector.
          See class docstring for definition of compatibility.
        adjoint: Python `bool`.  If `True`, left multiply by the adjoint: `A^H x`.
        name:  A name for this `Op.
  
      Returns:
        A `Tensor` with shape `[..., M]` and same `dtype` as `self`.
docstring_summary: Transform [batch] vector `x` with left multiplication:  `x --> Ax`.
docstring_tokens: Transform [ batch ] vector x with left multiplication : x -- > Ax .
function: def matvec(self, x, adjoint=False, name="matvec"):
      """Transform [batch] vector `x` with left multiplication:  `x --> Ax`.
  
      ```python
      # Make an operator acting like batch matric A.  Assume A.shape = [..., M, N]
      operator = LinearOperator(...)
  
      X = ... # shape [..., N], batch vector
  
      Y = operator.matvec(X)
      Y.shape
      ==> [..., M]
  
      Y[..., :] = sum_j A[..., :, j] X[..., j]
      ```
  
      Args:
        x: `Tensor` with compatible shape and same `dtype` as `self`.
          `x` is treated as a [batch] vector meaning for every set of leading
          dimensions, the last dimension defines a vector.
          See class docstring for definition of compatibility.
        adjoint: Python `bool`.  If `True`, left multiply by the adjoint: `A^H x`.
        name:  A name for this `Op.
  
      Returns:
        A `Tensor` with shape `[..., M]` and same `dtype` as `self`.
      """
      with self._name_scope(name, values=[x]):
        x = ops.convert_to_tensor(x, name="x")
        self._check_input_dtype(x)
        self_dim = -2 if adjoint else -1
        self.shape[self_dim].assert_is_compatible_with(x.get_shape()[-1])
        return self._matvec(x, adjoint=adjoint)
function_tokens: def matvec ( self , x , adjoint = False , name = "matvec" ) : with self . _name_scope ( name , values = [ x ] ) : x = ops . convert_to_tensor ( x , name = "x" ) self . _check_input_dtype ( x ) self_dim = - 2 if adjoint else - 1 self . shape [ self_dim ] . assert_is_compatible_with ( x . get_shape ( ) [ - 1 ] ) return self . _matvec ( x , adjoint = adjoint )