$Shx"UdZddlmZddlZddlZddlZddlmZmZddl m Z ddl Z ddl mZddlmZmZddlmZmZdd lmZgd Zed eZd ed <ed e jZd ed < d1dddd2dZeZd3d!Zd4d%Zd5d&Z d6d+Z!d7d0Z"dS)8zIntegration with NumPy.) annotationsN)AnyCallable) TypeAlias) ArrayLike) tree_flattentree_unflatten) PyTreeSpec PyTreeTypeVar)safe_zip) ArrayLikeTree ArrayTree tree_ravelr rrF) none_is_leaf namespaceis_leafCallable[[Any], bool] | Nonetreerboolrstrreturn4tuple[np.ndarray, Callable[[np.ndarray], ArrayTree]]ct||||\}}t|\}}|tjt||fS)a' Ravel (flatten) a pytree of arrays down to a 1D array. >>> tree = { ... 'layer1': { ... 'weight': np.arange(0, 6, dtype=np.float32).reshape((2, 3)), ... 'bias': np.arange(6, 8, dtype=np.float32).reshape((2,)), ... }, ... 'layer2': { ... 'weight': np.arange(8, 10, dtype=np.float32).reshape((1, 2)), ... 'bias': np.arange(10, 11, dtype=np.float32).reshape((1,)), ... }, ... } >>> tree # doctest: +IGNORE_WHITESPACE { 'layer1': { 'weight': array([[0., 1., 2.], [3., 4., 5.]], dtype=float32), 'bias': array([6., 7.], dtype=float32) }, 'layer2': { 'weight': array([[8., 9.]], dtype=float32), 'bias': array([10.], dtype=float32) } } >>> flat, unravel_func = tree_ravel(tree) >>> flat array([ 6., 7., 0., 1., 2., 3., 4., 5., 10., 8., 9.], dtype=float32) >>> unravel_func(flat) # doctest: +IGNORE_WHITESPACE { 'layer1': { 'weight': array([[0., 1., 2.], [3., 4., 5.]], dtype=float32), 'bias': array([6., 7.], dtype=float32) }, 'layer2': { 'weight': array([[8., 9.]], dtype=float32), 'bias': array([10.], dtype=float32) } } Args: tree (pytree): a pytree of arrays and scalars to ravel. is_leaf (callable, optional): An optionally specified function that will be called at each flattening step. It should return a boolean, with :data:`True` stopping the traversal and the whole subtree being treated as a leaf, and :data:`False` indicating the flattening should traverse the current object. none_is_leaf (bool, optional): Whether to treat :data:`None` as a leaf. If :data:`False`, :data:`None` is a non-leaf node with arity 0. Thus :data:`None` is contained in the treespec rather than in the leaves list and :data:`None` will be remain in the result pytree. (default: :data:`False`) namespace (str, optional): The registry namespace used for custom pytree node types. (default: :const:`''`, i.e., the global namespace) Returns: A pair ``(array, unravel_func)`` where the first element is a 1D array representing the flattened and concatenated leaf values, with ``dtype`` determined by promoting the ``dtype``\s of leaf values, and the second element is a callable for unflattening a 1D array of the same length back to a pytree of the same structure as the input ``tree``. If the input pytree is empty (i.e. has no leaves) then as a convention a 1D empty array of the default dtype is returned in the first component of the output. )rrr)r _ravel_leaves functoolspartial _tree_unravel)rrrrleavestreespecflat unravel_flats _/var/www/html/movieo_spanner_bot/venv/lib/python3.11/site-packages/optree/integrations/numpy.pyrr*sXJ$ ! FH 'v..D, "=(LII IIr r r"(Callable[[np.ndarray], list[np.ndarray]]r! np.ndarrayc4t|||SN)r )r r"r!s r#rr|s (LL$6$6 7 77r$rlist[np.ndarray];tuple[np.ndarray, Callable[[np.ndarray], list[np.ndarray]]]c\|stjdtfStd|D}tj|td|D}td|D}tt j|}tfd|Dr;tjd|D}|tj t||fStjfd|D}|tj t|||fS)Nrc3>K|]}tj|VdSr()np result_type.0leafs r# z _ravel_leaves..s,@@t,,@@@@@@r$c3>K|]}tj|VdSr()r-sizer/s r#r2z _ravel_leaves..s*33D"'$--333333r$c3>K|]}tj|VdSr()r-shaper/s r#r2z _ravel_leaves..s*55d28D>>555555r$c3$K|] }|kV dSr()r0dtto_dtypes r#r2z _ravel_leaves..s' 0 0b2> 0 0 0 0 0 0r$c6g|]}tj|Sr8)r-ravelr/s r# z!_ravel_leaves..s !D!D!DT"(4..!D!D!Dr$c^g|])}tj|*Sr8)r-r<astype)r0r1r:s r#r=z!_ravel_leaves..s/QQQ$bhtnn33H==QQQr$) r-zeros_unravel_emptytupler. itertools accumulateall concatenaterr_unravel_leaves_single_dtype_unravel_leaves)r from_dtypessizesshapesindicesraveledr:s @r#rrsD - ^,,@@@@@@@K~v&H 33F333 3 3E 55f555 5 5FI(//00G 0 0 0 0K 0 0 000 .!D!DV!D!D!DEE   :GV L L  nQQQQ&QQQRRG/7FKRR r$ctj|dkr(tdddtj|dgS)N)r0The unravel function expected an array of shape , got shape .)r-r6 ValueError)r!s r#rArAsQ x~~ bt b bQSQYZ^Q_Q_ b b b    Ir$rLtuple[int, ...]rKtuple[tuple[int, ...], ...]c tj||dfkr/td|dfdtj|dtj||dd}dt ||DS)NrOrPrQc>g|]\}}||Sr8)reshape)r0chunkr6s r#r=z0_unravel_leaves_single_dtype..s( N N N\UEEMM% N N Nr$)r-r6rRsplitr )rLrKr!chunkss r#rGrGs  x~~'"+'' + ~ + +$ + + +   XdGCRCL ) )F N NXff5M5M N N NNr$rItuple[np.dtype, ...]r:np.dtypectj||dfkr/td|dfdtj|dtj|}||krtd|d|dtj||dd}t j5t jddt|||DcdddS#1swxYwYdS) NrVrOrPrQz0The unravel function expected an array of dtype z , got dtype ignorecfg|].\}}}|||/Sr8)rXr?)r0rYr6dtypes r#r=z#_unravel_leaves..sH   #ue MM% ' ' . .   r$) r-r6rRr.rZwarningscatch_warnings simplefilterr )rLrKrIr:r! array_dtyper[s r#rHrHsl x~~'"+'' + ~ + +$ + + +   .&&Kh cx c cU` c c c   XdGCRCL ) )F  " "  h'''  '/ 'L'L                     s//C++C/2C/r() rrrr rrrrrr)r r r"r%r!r&rr)rr)rr*)r!r&rr))rLrSrKrTr!r&rr)) rLrSrKrTrIr\r:r]r!r&rr))#__doc__ __future__rrrCrbtypingrrtyping_extensionsrnumpyr- numpy.typingr optree.opsrr optree.typingr r optree.utilsr __all__r __annotations__ndarrayrr ravel_pytreerrrArGrHr8r$r#rss#""""" ''''''""""""3333333333333333!!!!!! 7 6 6)=)DD DDDD$}["*== ==== -1LJ  LJLJLJLJLJLJ^ 8888B O O O O       r$