
    uki<                       d dl mZ d dlmZmZ d dlmZmZ d dlm	Z	  ed      Z
ddddZ	 d	 	 	 dd	Z	 d	 	 	 dd
Zdd	 	 	 	 	 	 	 ddZ e	j                         df	 	 	 	 	 	 	 ddZ e	j                         dd	 	 	 	 	 	 	 	 	 ddZ	 d	 	 	 ddZ	 	 	 	 	 	 d dZ	 	 	 	 d!dZ	 	 d"	 	 	 	 	 	 	 d#dZ	 	 d"	 	 	 	 	 	 	 d$dZddd	 	 	 	 	 	 	 	 	 	 	 d%dZ	 d	 	 	 d&dZy)'    )annotations)CallableIterable)AnyTypeVar)	tree_utilTNis_leafc               0    t        j                  | |      S )a  Call all() over the leaves of a tree.

  Args:
    tree: the pytree to evaluate
    is_leaf : an optionally specified function that will be called at each
      flattening step. It should return a boolean, which indicates whether the
      flattening should traverse the current object, or if it should be stopped
      immediately, with the whole subtree being treated as a leaf.

  Returns:
    result: boolean True or False

  Examples:
    >>> import jax
    >>> jax.tree.all([True, {'a': True, 'b': (True, True)}])
    True
    >>> jax.tree.all([False, (True, False)])
    False

  See Also:
    - :func:`jax.tree.reduce`
    - :func:`jax.tree.leaves`
  r
   )r   tree_alltreer   s     H/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/jax/_src/tree.pyallr      s    0 
		D'	22    c                .    t        j                  | |      S )a  Flattens a pytree.

  The flattening order (i.e. the order of elements in the output list)
  is deterministic, corresponding to a left-to-right depth-first tree
  traversal.

  Args:
    tree: a pytree to flatten.
    is_leaf: an optionally specified function that will be called at each
      flattening step. It should return a boolean, with true stopping the
      traversal and the whole subtree being treated as a leaf, and false
      indicating the flattening should traverse the current object.

  Returns:
    A pair where the first element is a list of leaf values and the second
    element is a treedef representing the structure of the flattened tree.

  Examples:
    >>> import jax
    >>> vals, treedef = jax.tree.flatten([1, (2, 3), [4, 5]])
    >>> vals
    [1, 2, 3, 4, 5]
    >>> treedef
    PyTreeDef([*, (*, *), [*, *]])

  See Also:
    - :func:`jax.tree.leaves`
    - :func:`jax.tree.structure`
    - :func:`jax.tree.unflatten`
  )r   tree_flattenr   s     r   flattenr   3   s    B 
		g	..r   c                .    t        j                  | |      S )a  Gets the leaves of a pytree.

  Args:
    tree: the pytree for which to get the leaves
    is_leaf : an optionally specified function that will be called at each
      flattening step. It should return a boolean, which indicates whether the
      flattening should traverse the current object, or if it should be stopped
      immediately, with the whole subtree being treated as a leaf.

  Returns:
    leaves: a list of tree leaves.

  Examples:
    >>> import jax
    >>> jax.tree.leaves([1, (2, 3), [4, 5]])
    [1, 2, 3, 4, 5]

  See Also:
    - :func:`jax.tree.flatten`
    - :func:`jax.tree.structure`
    - :func:`jax.tree.unflatten`
  )r   tree_leavesr   s     r   leavesr   W   s    2 
		tW	--r   c               6    t        j                  | |g|d|iS )a  Maps a multi-input function over pytree args to produce a new pytree.

  Args:
    f: function that takes ``1 + len(rest)`` arguments, to be applied at the
      corresponding leaves of the pytrees.
    tree: a pytree to be mapped over, with each leaf providing the first
      positional argument to ``f``.
    rest: a tuple of pytrees, each of which has the same structure as ``tree``
      or has ``tree`` as a prefix.
    is_leaf: an optionally specified function that will be called at each
      flattening step. It should return a boolean, which indicates whether the
      flattening should traverse the current object, or if it should be stopped
      immediately, with the whole subtree being treated as a leaf.

  Returns:
    A new pytree with the same structure as ``tree`` but with the value at each
    leaf given by ``f(x, *xs)`` where ``x`` is the value at the corresponding
    leaf in ``tree`` and ``xs`` is the tuple of values at corresponding nodes in
    ``rest``.

  Examples:

    >>> import jax
    >>> jax.tree.map(lambda x: x + 1, {"x": 7, "y": 42})
    {'x': 8, 'y': 43}

    If multiple inputs are passed, the structure of the tree is taken from the
    first input; subsequent inputs need only have ``tree`` as a prefix:

    >>> jax.tree.map(lambda x, y: [x] + y, [5, 6], [[7, 9], [1, 2]])
    [[5, 7, 9], [6, 1, 2]]

  See Also:
    - :func:`jax.tree.leaves`
    - :func:`jax.tree.reduce`
  r   )r   tree_map)fr   r   rests       r   mapr   s   s"    P 
		At	<d	<G	<<r   c                4    t        j                  | |||      S )a  Call reduce() over the leaves of a tree.

  Args:
    function: the reduction function
    tree: the pytree to reduce over
    initializer: the optional initial value
    is_leaf : an optionally specified function that will be called at each
      flattening step. It should return a boolean, which indicates whether the
      flattening should traverse the current object, or if it should be stopped
      immediately, with the whole subtree being treated as a leaf.

  Returns:
    result: the reduced value.

  Examples:
    >>> import jax
    >>> import operator
    >>> jax.tree.reduce(operator.add, [1, (2, 3), [4, 5, 6]])
    21

  Notes:
    **Tip**: You can exclude leaves from the reduction by first mapping them to
    ``None`` using :func:`jax.tree.map`. This causes them to not be counted as
    leaves after that.

  See Also:
    - :func:`jax.tree.reduce_associative`
    - :func:`jax.tree.leaves`
    - :func:`jax.tree.map`
  r
   )r   tree_reduce)functionr   initializerr   s       r   reducer"      s    D 
		x{G	LLr   identityr   c               4    t        j                  | |||      S )a  Perform a reduction over a pytree with an associative binary operation.

  This function exploits the fact that the operation is associative to perform
  the reduction in parallel (logarithmic depth).

  Args:
    operation: the associative binary operation
    tree: the pytree to reduce
    identity: the identity element of the associative binary operation.
      This is used only when the tree is empty. It is optional otherwise.
    is_leaf: an optionally specified function that will be called at each
      flattening step. It should return a boolean, which indicates whether the
      flattening should traverse the current object, or if it should be stopped
      immediately, with the whole subtree being treated as a leaf.

  Returns:
    result: the reduced value

  Examples:
    >>> import jax
    >>> import operator
    >>> jax.tree.reduce_associative(operator.add, [1, (2, 3), [4, 5, 6]])
    21

  Notes:
    **Tip**: You can exclude leaves from the reduction by first mapping them to
    ``None`` using :func:`jax.tree.map`. This causes them to not be counted as
    leaves after that.

  See Also:
    - :func:`jax.tree.reduce`
  r#   )r   tree_reduce_associative)	operationr   r$   r   s       r   reduce_associativer(      s$    N 
	*	*
	
 r   c                .    t        j                  | |      S )a  Gets the treedef for a pytree.

  Args:
    tree: the pytree for which to get the leaves
    is_leaf : an optionally specified function that will be called at each
      flattening step. It should return a boolean, which indicates whether the
      flattening should traverse the current object, or if it should be stopped
      immediately, with the whole subtree being treated as a leaf.

  Returns:
    pytreedef: a PyTreeDef representing the structure of the tree.

  Examples:
    >>> import jax
    >>> jax.tree.structure([1, (2, 3), [4, 5]])
    PyTreeDef([*, (*, *), [*, *]])

  See Also:
    - :func:`jax.tree.flatten`
    - :func:`jax.tree.leaves`
    - :func:`jax.tree.unflatten`
  )r   tree_structurer   s     r   	structurer+      s    0 
	!	!$	00r   c                0    t        j                  | ||      S )aQ  Transform a tree having tree structure (outer, inner) into one having structure (inner, outer).

  Args:
    outer_treedef: PyTreeDef representing the outer tree.
    inner_treedef: PyTreeDef representing the inner tree.
      If None, then it will be inferred from outer_treedef and the structure of
      pytree_to_transpose.
    pytree_to_transpose: the pytree to be transposed.

  Returns:
    transposed_pytree: the transposed pytree.

  Examples:
    >>> import jax
    >>> tree = [(1, 2, 3), (4, 5, 6)]
    >>> inner_structure = jax.tree.structure(('*', '*', '*'))
    >>> outer_structure = jax.tree.structure(['*', '*'])
    >>> jax.tree.transpose(outer_structure, inner_structure, tree)
    ([1, 4], [2, 5], [3, 6])

    Inferring the inner structure:

    >>> jax.tree.transpose(outer_structure, None, tree)
    ([1, 4], [2, 5], [3, 6])
  )r   tree_transpose)outer_treedefinner_treedefpytree_to_transposes      r   	transposer1     s    8 
	!	!-@S	TTr   c                .    t        j                  | |      S )a  Reconstructs a pytree from the treedef and the leaves.

  The inverse of :func:`tree_flatten`.

  Args:
    treedef: the treedef to reconstruct
    leaves: the iterable of leaves to use for reconstruction. The iterable must
      match the leaves of the treedef.

  Returns:
    The reconstructed pytree, containing the ``leaves`` placed in the structure
    described by ``treedef``.

  Examples:
    >>> import jax
    >>> vals, treedef = jax.tree.flatten([1, (2, 3), [4, 5]])
    >>> newvals = [100, 200, 300, 400, 500]
    >>> jax.tree.unflatten(treedef, newvals)
    [100, (200, 300), [400, 500]]

  See Also:
    - :func:`jax.tree.flatten`
    - :func:`jax.tree.leaves`
    - :func:`jax.tree.structure`
  )r   tree_unflatten)treedefr   s     r   	unflattenr5   ,  s    6 
	!	!'6	22r   Fc                0    t        j                  | ||      S )a6  Flattens a pytree like ``tree_flatten``, but also returns each leaf's key path.

  Args:
    tree: a pytree to flatten. If it contains a custom type, it is recommended
      to be registered with ``register_pytree_with_keys``.

  Returns:
    A pair which the first element is a list of key-leaf pairs, each of
    which contains a leaf and its key path. The second element is a treedef
    representing the structure of the flattened tree.

  Examples:
    >>> import jax
    >>> path_vals, treedef = jax.tree.flatten_with_path([1, {'x': 3}])
    >>> path_vals
    [((SequenceKey(idx=0),), 1), ((SequenceKey(idx=1), DictKey(key='x')), 3)]
    >>> treedef
    PyTreeDef([*, {'x': *}])

  See Also:
    - :func:`jax.tree.flatten`
    - :func:`jax.tree.map_with_path`
    - :func:`jax.tree_util.register_pytree_with_keys`
  )r   tree_flatten_with_pathr   r   is_leaf_takes_paths      r   flatten_with_pathr:   J  s    8 
	)	)$9K	LLr   c                0    t        j                  | ||      S )a`  Gets the leaves of a pytree like ``tree_leaves`` and returns each leaf's key path.

  Args:
    tree: a pytree. If it contains a custom type, it is recommended to be
      registered with ``register_pytree_with_keys``.

  Returns:
    A list of key-leaf pairs, each of which contains a leaf and its key path.

  Examples:
    >>> import jax
    >>> jax.tree.leaves_with_path([1, {'x': 3}])
    [((SequenceKey(idx=0),), 1), ((SequenceKey(idx=1), DictKey(key='x')), 3)]

  See Also:
    - :func:`jax.tree.leaves`
    - :func:`jax.tree.flatten_with_path`
    - :func:`jax.tree_util.register_pytree_with_keys`
  )r   tree_leaves_with_pathr8   s      r   leaves_with_pathr=   i  s    . 
	(	(w8J	KKr   r   r9   c               8    t        j                  | |g|||dS )a  Maps a multi-input function over pytree key path and args to produce a new pytree.

  This is a more powerful alternative of ``tree_map`` that can take the key path
  of each leaf as input argument as well.

  Args:
    f: function that takes ``2 + len(rest)`` arguments, aka. the key path and
      each corresponding leaves of the pytrees.
    tree: a pytree to be mapped over, with each leaf's key path as the first
      positional argument and the leaf itself as the second argument to ``f``.
    *rest: a tuple of pytrees, each of which has the same structure as ``tree``
      or has ``tree`` as a prefix.

  Returns:
    A new pytree with the same structure as ``tree`` but with the value at each
    leaf given by ``f(kp, x, *xs)`` where ``kp`` is the key path of the leaf at
    the corresponding leaf in ``tree``, ``x`` is the leaf value and ``xs`` is
    the tuple of values at corresponding nodes in ``rest``.

  Examples:
    >>> import jax
    >>> jax.tree.map_with_path(lambda path, x: x + path[0].idx, [1, 2, 3])
    [1, 3, 5]

  See Also:
    - :func:`jax.tree.map`
    - :func:`jax.tree.flatten_with_path`
    - :func:`jax.tree.leaves_with_path`
    - :func:`jax.tree_util.register_pytree_with_keys`
  r>   )r   tree_map_with_path)r   r   r   r9   r   s        r   map_with_pathrA     s0    J 
	%	%

%:L
 r   c                2    t        j                  | ||      S )a  Broadcasts a tree prefix into the full structure of a given tree.

    Args:
      prefix_tree: a pytree that is a tree prefix of full_tree.
      full_tree: a pytree with the structure to broadcast the prefix leaves into.
      is_leaf: an optionally specified function that will be called at each
        flattening step. It should return a boolean, with true stopping the
        traversal and the whole subtree being treated as a leaf, and false
        indicating the flattening should traverse the current object.

    Returns:
      A pytree matching the structure of full_tree where the leaves of prefix_tree have been
      broadcasted into the leaves of each corresponding subtree.

    Examples:
      >>> import jax
      >>> prefix = (1, 2, 3)
      >>> full = (0, {'a': 0, 'b': 0}, (0, 0))
      >>> jax.tree.broadcast(prefix, full)
      (1, {'a': 2, 'b': 2}, (3, 3))

    See Also:
      - :func:`jax.tree.leaves`
      - :func:`jax.tree.structure`
  r
   )r   tree_broadcast)prefix_tree	full_treer   s      r   	broadcastrF     s    8 
	!	!+y'	JJr   )r   r   r   Callable[[Any], bool] | Nonereturnbool)N)r   r   r   rG   rH   z0tuple[list[tree_util.Leaf], tree_util.PyTreeDef])r   r   r   rG   rH   zlist[tree_util.Leaf])
r   Callable[..., Any]r   r   r   r   r   rG   rH   r   )
r    zCallable[[T, Any], T]r   r   r!   T | tree_util.Unspecifiedr   rG   rH   r	   )
r'   zCallable[[T, T], T]r   r   r$   rK   r   rG   rH   r	   )r   r   r   zNone | Callable[[Any], bool]rH   tree_util.PyTreeDef)r.   rL   r/   ztree_util.PyTreeDef | Noner0   r   rH   r   )r4   rL   r   zIterable[tree_util.Leaf]rH   r   )NF)r   r   r   Callable[..., bool] | Noner9   rI   rH   z?tuple[list[tuple[tree_util.KeyPath, Any]], tree_util.PyTreeDef])r   r   r   rM   r9   rI   rH   z#list[tuple[tree_util.KeyPath, Any]])r   rJ   r   r   r   r   r   rM   r9   rI   rH   r   )rD   r   rE   r   r   rG   rH   r   )
__future__r   collections.abcr   r   typingr   r   jax._srcr   r	   r   r   r   r   Unspecifiedr"   r(   r+   r1   r5   r:   r=   rA   rF    r   r   <module>rT      s3   # .  CL ?C 38 59!/1!/A!/J 48.0.$.> 15(=(=(= .(= :=(=Z 5JI4I4I4K37"M"M1"M 1"M =>"MR +@)*?*?*A,0,",
, (	,
 *, ,` 9=151AT16U7U#&U+.U>3.3363> 6:$M
M2MM EM@ 6:$L
L2LL )L< +/$''
' ' (	'
 ' 	'V 7;K3KKr   