VpfkHdZddlmZddlmZmZddlZddlZddlZddl m Z ddl Z ddl m Z ddl mZddl mZdd l mZdd l mZdd l mZdd l mZdd lmZddlmZddlmZddlmZddlmZddlmZddl Z!ej"e#Z$e j%dZ&de&_'ej()e&ej*ecZZ+ej,dGddZ-d=dZ.e&/ej0ej1e&e&j2d=dZ3dZ4e4ej5e&<d Z6e6ej7e&<d>d%Z8ej0e8e&ej9e&<d?d&Z:d@d'Z;ej<e&e;d(Z=dd)d*dAd.Z>e j%d/Z?de?_'ej()e?Gd0d1ej@ZAGd2d3ej@ZBeAZCeBZDejEFeAejEFeBejGFeAejGFeBejHFeBejIFeBdBd5ZJe?/ej0ej1e?e?jKdBd6ZLd7ZMeMej5e?<d8ZNeNej7e?<d9ZOeOej9e?<d:ZPej<e?ePdd)d;dCd<ZQdS)DzModule for JAX callbacks.) annotations)CallableSequenceN)Any)core)dispatch)dtypes)effects)sharding_impls) tree_util)util)ad)batching)mlir)map) xla_client)SingleDeviceSharding pure_callbackT)frozenc0eZdZUdZded<ded<d d Zd S) _FlatCallbacka/A Python function callable with flat arguments and results. An instance of this class is used as a parameter for the callback primitives. We prefer it to an anonymous flattened function because it produces equal objects when we call the same Python function with the same argument structure. Callable[..., Any] callback_funcztree_util.PyTreeDefin_tree flat_args jax.ArrayreturnSequence[jax.Array]cztj|j|\}}tj|j|i|SN)r tree_unflattenr tree_leavesr)selfrargskwargss Q/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/jax/_src/callback.py__call__z_FlatCallback.__call__>s>+DL)DDLD&  !3!3T!DV!D!D E EEN)rrrr)__name__ __module__ __qualname____doc____annotations__r'r(r&rr2sT$###FFFFFFr(rcallbackshardingSingleDeviceSharding | None vectorizedboolc~~~ tjd^}}n"#t$r}td|d}~wwxYwtj||}tj|5 t jtj||cdddS#t$rt dwxYw#1swxYwYdS)Ncpubackendzjax.pure_callback failed to find a local CPU device to place the inputs on. Make sure "cpu" is listed in --jax_platforms or the JAX_PLATFORMS environment variable.zjax.pure_callback failed jax local_devices RuntimeError device_putdefault_devicer tree_mapnpasarray BaseExceptionlogger exception) result_avalsr/r0r2r$ cpu_device_es r&pure_callback_implrHCs> L &u555NJ     /     j ) )$ *%%     HHdO < <             1222            4 <7<(C*!B&B>>CCCc~~~~|Sr r.)r/rDr0r2avalss r&pure_callback_abstract_evalrL`s Xx r(c$~~td)NzgPure callbacks do not support JVP. Please use `jax.custom_jvp` to use callbacks while taking gradients. ValueErrorr$r%s r&pure_callback_jvp_rulerQl" FM N NNr(c$~~td)NzmPure callbacks do not support transpose. Please use `jax.custom_vjp` to use callbacks while taking gradients.rNrPs r&pure_callback_transpose_rulerTvrRr(rDSequence[core.ShapedArray]r%rc  tdt||D dt||D}r,t fdDj|d}n>d|D t j |\ }  fd} t | |}t|dt|zfS)Nc3RK|]"\}}|tju|j|V#dSr )r not_mappedshape).0ads r& z)callback_batching_rule..sE44$!Qx22271:222244r(c`g|]+\}}|tjur|ntj||d,SrrrXmoveaxisrZargdims r& z*callback_batching_rule..SNNN19cH///ccS!,,NNNr(c3ZK|]%}tjtjd|V&dS)rN)r unmapped_aval no_axis_name)rZaval axis_sizes r&r]z)callback_batching_rule..sK""  9d&7DAA""""""r()r2rDc*g|]}|tjuSr.rrXrZr\s r&rez*callback_batching_rule..s ===1!8..===r(cPtj|}j|dS)N)rDr2)r merge_listsbind) batched_args merged_args is_batchedr%primrDunbatched_argsr2s r& _batch_funz*callback_batching_rule.._batch_funsE$ZNNk TY #  r(r_)nextziptuplerqr partition_listlax_maplen) rur$dimsr2rDr%new_argsoutvalsrrrwrkrtrvs ` ``` @@@r&callback_batching_rulers_44#dD//44444)NN=@t__NNN(0"""" """""Ldi !  GG>====J#'#6z8#L#L NLj,//G wG , ,,r(c4t|tjrr|jt |jjkrtd|tdtj }tj j j |_ |St|tj r|t|tstdt|tt!|j}|j}|t'd ||}n+#t*$r}t-d|d|d|d}~wwxYwd}tj }tj j j|_ d g|_|g|_|SdS) Nz~callbacks are only supported in spmd computations when all mesh axes are partitioned manually (no partial automatic sharding).zEcallbacks do not support specifying sharding inside spmd computationsz:pure_callback only supports SingleDeviceSharding, but got z9Please file a bug at https://github.com/google/jax/issuesz6Sharding provided to pure_callback specifies a device z' that is not in the device assignment ()r) isinstancer SPMDAxisContext manual_axes frozensetmesh axis_namesNotImplementedErrorxc OpShardingTypeMANUALtypeShardingContextrrxiter device_setdevice_assignmentAssertionErrorindex IndexErrorrOMAXIMALtile_assignment_dimensionstile_assignment_devices) axis_contextr0 op_shardingdevicer device_indexrGs r&_callback_op_shardingrs n<==9\->-I#J#JJJ  L      -//K})0K  n<== "6 7 7 ! !X ! !   D,--..f&8  " GII I.(..v66 ... & & &" & & &''-. .. l -//K})1K./SK*+7.K'  sD-- E7EEc fd}t|jj|}tj||dt ||j|jd|\}}}|S)Nc<tt|ddS)N)r/r0)rzrH)rr/paramss r& _callbackz)pure_callback_lowering.._callbacks:         r(Fhas_side_effectr0)rmodule_contextrremit_python_callbacklistavals_in avals_out) ctxr/r0r$rrrresultrFs ` ` r&pure_callback_loweringrs&c&8&ExPP+*   4jj l m   ,&!Q -r(ctj|j}tj||krt ddS)NzQresult_shape_dtypes cannot specify 64-bit types when `jax_enable_x64` is disabled)r?dtyper canonicalize_dtyperO) shape_dtypedts r&_check_shape_dtypersJ x !""" r""b(( [ ] ]])(r(F)r0r2rresult_shape_dtypesr$cJtj||f\}}tjt|tjd|}tj|\} } t j|t ||t| ||d} tj| | S)a Calls a pure Python callback. Works under :func:`jit`/:func:`~vmap`/etc. For more explanation, see `External Callbacks`_. ``pure_callback`` enables calling a Python function in JIT-ed JAX functions. The input ``callback`` will be passed JAX arrays placed on a local CPU, and it should also return JAX arrays on CPU. The callback is treated as functionally pure, meaning it has no side-effects and its output value depends only on its argument values. As a consequence, it is safe to be called multiple times (e.g. when transformed by :func:`~vmap` or :func:`~pmap`), or not to be called at all when e.g. the output of a `jit`-decorated function has no data dependence on its value. Pure callbacks may also be reordered if data-dependence allows. When `vmap`-ed the behavior will depend on the value of the ``vectorized`` keyword argument. When ``vectorized`` is ``True``, the callback is assumed to obey ``jax.vmap(callback)(xs) == callback(xs) == jnp.stack([callback(x) for x in xs])``. Therefore, the callback will be called directly on batched inputs (where the batch axes are the leading dimensions). Additionally, the callbacks should return outputs that have corresponding leading batch axes. If not vectorized ``callback`` will be mapped sequentially across the batched axis. For example, if ``callback = lambda x, y: np.matmul(x, y)``, then we are free to set ``vectorized=True`` because the ``np.matmul`` function handles arbitrary leading batch dimensions. Args: callback: function to execute on the host. The callback is assumed to be a pure function (i.e. one without side-effects): if an impure function is passed, it may behave in unexpected ways, particularly under transformation. The callable will be passed PyTrees of arrays as arguments, and should return a PyTree of arrays that matches ``result_shape_dtypes``. result_shape_dtypes: pytree whose leaves have ``shape`` and ``dtype`` attributes, whose structure matches the expected output of the callback function at runtime. :class:`jax.ShapeDtypeStruct` is often used to define leaf values. *args: arguments to be passed to the callback function sharding: optional sharding that specifies the device from which the callback should be invoked. vectorized: boolean specifying whether the callback function can operate in a vectorized manner. **kwargs: keyword arguments to be passed to the callback function Returns: result: a pytree of :class:`jax.Array` objects whose structure matches that of ``result_shape_dtypes``. See Also: - :func:`jax.experimental.io_callback`: callback designed for impure functions. - :func:`jax.debug.callback`: callback designed for general-purpose debugging. - :func:`jax.debug.print`: callback designed for printing. .. _External Callbacks: https://jax.readthedocs.io/en/latest/notebooks/external_callbacks.html c@tj|j|jSr r ShapedArrayrYrxs r&zpure_callback..Ds !'22r()r/rDr0r2) r tree_flattenr>rpure_callback_prqrrzr!) r/rr0r2r$r%rrrDflat_result_avalsout_treeout_flats r&rrs|!-tVn==)W ')<===#224GII, ) 6| D DX  !Xw//*++ (  !(H 5 55r( io_callbackceZdZdZdS)IOEffectcdS)NIOr.rFs r&rzIOEffect.Wsdr(Nr)r*r+__str__r.r(r&rrVs N'''r(rceZdZdZdS)OrderedIOEffectcdS)N OrderedIOr.rs r&rzOrderedIOEffect.Zskr(Nrr.r(r&rrYs ! !'''r(rorderedc~~~ tjd^}}n"#t$r}td|d}~wwxYwtj||}tj|5 t jtj||cdddS#t$rt dwxYw#1swxYwYdS)Nr5r6zjax.io_callback failed to find a local CPU device to place the inputs on. Make sure "cpu" is listed in --jax_platforms or the JAX_PLATFORMS environment variable.zjax.io_callback failedr8)rDr/r0rr$rErFrGs r&io_callback_implrfs>Hg &u555NJ     /     j ) )$ *%%     HHdO < <             /000            rIc2~~~|rtnt}||hfSr )_OrderedIOEffect _IOEffect)r/rDr0rrKeffects r&io_callback_abstract_evalrs( Xx& 5  I& x r(c$~~td)Nz IO callbacks do not support JVP.rNrPs r&io_callback_jvp_rulers F5666r(c$~~td)Nz&IO callbacks do not support transpose.rNrPs r&io_callback_transpose_rulers F;<<.s ;;;,,;;;r(c`g|]+\}}|tjur|ntj||d,Sr_r`rbs r&rez-io_callback_batching_rule..rfr(cXtj|}tj|ddS)NF)r/r0rDr)r rp io_callback_prq)rrmergedr/rtrDr0rvs r&rwz-io_callback_batching_rule.._batch_funs@  j., G GF  v8+7 H H HHr(r_)rOryr r{r|r}) r$r~r/rDr0rrrrrwout_valsrtrvs ``` @@r&io_callback_batching_rulers ; 9 : ::;;d;;;*NN=@t__NNN(!%!4Z!J!J.,HHHHHHHHHZ . .( 4#h--' ''r(c fd}t|jj|}r|jt }t j|||t||j |j d|\} }} | t j t |in7t j||dt||j |j d|\} }} | S)Nc >tt|ddS)N)r/r0r)rzr)rr/rrs r&rz'io_callback_lowering.._callbacks=          r(Tr) rrr tokens_ingetrrrrrrset_tokens_outTokenSet) rr/r0rr$rrrtokenrrFs ` ` ` r&io_callback_loweringrs        &c&8&ExPP+  M  . / /E0   T      FE1t}&6%>??@@@@0   T      FE1 -r()r0rcttj||f\}}tjt|tj|\}} t d|} t t j|}tj|t||t| ||d} tj | | S)a(Calls an impure Python callback. For more explanation, see `External Callbacks`_. Args: callback: function to execute on the host. It is assumed to be an impure function. If ``callback`` is pure, using :func:`jax.pure_callback` instead may lead to more efficient execution. result_shape_dtypes: pytree whose leaves have ``shape`` and ``dtype`` attributes, whose structure matches the expected output of the callback function at runtime. :class:`jax.ShapeDtypeStruct` is often used to define leaf values. *args: arguments to be passed to the callback function sharding: optional sharding that specifies the device from which the callback should be invoked. ordered: boolean specifying whether sequential calls to callback must be ordered. **kwargs: keyword arguments to be passed to the callback function Returns: result: a pytree of :class:`jax.Array` objects whose structure matches that of ``result_shape_dtypes``. See Also: - :func:`jax.pure_callback`: callback designed for pure functions. - :func:`jax.debug.callback`: callback designed for general-purpose debugging. - :func:`jax.debug.print`: callback designed for printing. .. _External Callbacks: https://jax.readthedocs.io/en/latest/notebooks/external_callbacks.html c@tj|j|jSr rrs r&rzio_callback..sD$4QWag$F$Fr()r/rDr0r) r rr>rrrraise_as_much_as_possiblerrqrrzr!) r/rr0rr$r%rrflat_shape_dtypesrrrs r&rrsH!-tVn==)W ')<=== ) 67J K KXFF+--$0)<<)  Xw//*++ (  !(H 5 55r()r/rr0r1r2r3)r2r3rDrUr%r)r0r1)r/rr0r1) r/rrrr$rr0r1r2r3r%r)r/rr0r1rr3) r/rrrr$rr0r1rr3r%r)Rr, __future__rcollections.abcrr dataclasses functoolsloggingtypingrr9jax._srcrrr r r r r jax._src.interpretersrrrjax._src.lax.control_flow.loopsrr| jax._src.librrjax._src.sharding_implsrnumpyr? getLoggerr)rB Primitivermultiple_results%prim_requires_devices_during_loweringaddsafe_map unsafe_map dataclassrrHdef_implpartialapply_primitivedef_abstract_evalrLrQprimitive_jvpsrTprimitive_transposesrprimitive_batchersrrregister_loweringrrrEffectrrrrlowerable_effectsadd_typecontrol_flow_allowed_effectsordered_effectsshardable_ordered_effectsrdef_effectful_abstract_evalrrrrrrr.r(r&rs """"""........ ######$$$$$$******&&&&&&::::::))))))888888  8 $ $!$.11#' .22?CCC-Zd### F F F F F F F$# F     2**8+C+:<<==="#"NNN&</"NNN ,H(#-#-#-#-L0Ay/@O00O, 2222j6(>???]]]-1 J6J6J6J6J6J6^}-- !% .22=AAAw~"""""gn""" HJJ "?$$""8,,,""?333$--h777$--o>>> 111!**?;;;    2(y()A)688999*    +*  777$8- ===*D &(((.GM*%%%P}&:;;;-1 1616161616161616r(