class_docstr: Jax pytree representing a lazy dot operation.
class_docstr_tok: ["Jax","pytree","representing","a","lazy","dot","operation","."]
docstr: Function used by ``jax`` to unflatten the ``JaxLazyDot`` pytree.
  
  Args:
      aux_data (None): empty argument
      children (tuple): tuple containing the coefficients and the matrices of the operation
  
  Returns:
      JaxLazyDot: JaxLazyDot instance
docstr_tok: ["Function","used","by","``","jax","``","to","unflatten","the","``","JaxLazyDot","``","pytree",".","Args",":","aux_data","(","None",")",":","empty","argument","children","(","tuple",")",":","tuple","containing","the","coefficients","and","the","matrices","of","the","operation","Returns",":","JaxLazyDot",":","JaxLazyDot","instance"]
code: def tree_unflatten(cls, aux_data, children):
      """Function used by ``jax`` to unflatten the ``JaxLazyDot`` pytree.
  
      Args:
          aux_data (None): empty argument
          children (tuple): tuple containing the coefficients and the matrices of the operation
  
      Returns:
          JaxLazyDot: JaxLazyDot instance
      """
      return cls(*children)
  
file_path: pennylane/pennylane/pulse/parametrized_hamiltonian_pytree.py
imports: from dataclasses import dataclass
  from typing import Callable, Optional, Tuple, Union
  import jax
  import jax.numpy
  from jax.experimental import sparse
  from jax.tree_util import register_pytree_node_class
  import pennylane
  from .parametrized_hamiltonian import ParametrizedHamiltonian
  from .hardware_hamiltonian import HardwareHamiltonian
label_desc: Use image node_id 4 for calling the LazyDotPytree obj's underlying member method code with example usage: obj.tree_unflatten(cls, aux_data, children) and returns: cls