uki dZddlmZmZmZddlZddlmZddlmZddlm Z ddlm Z ddlm Z dd lm Zdd lmZddlmcmZdd lmZddlm Zdd lmZdd lmZddlmZej:ej<Zej:defdZ dedejBfdZ"de#ejHzdeegdfgegdfffdZ%ddddejHdejHdejHde&e#zdzdeeejBgdfgdff dZ'e jPdddZ)e)Z*de#fd Z+d!Z, d0d#ed$ejZd%ej\d&e/dzfd'Z0ejbdfd"ddddddd(d)eejbzd#edzd$ejZd%ej\d*ejddzd+e#d,ejfdzd-e#d&e/dzd.e4e/e/fdzfd/Z5y)1zPallas helper functions.)CallableMappingSequenceN)api)checkify)config)core) tree_util)typing)util) conditionals) primitives)utils)numpyxc0tjd|S)a'Create an empty PyTree of possibly uninitialized values. Args: x: A PyTree with leaves specifying the shape and dtype of the uninitialized object. Returns: A PyTree with the same structure as ``x``, but with uninitialized values. See Also: :func:`jax.lax.empty` cBt|j|jSN)emptyshapedtype)leafs R/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/jax/_src/pallas/helpers.pyzempty_like..4stzz4::)F)r tree_map)rs r empty_liker%s   F JJrreturnc |xtjdx\|j}nJtjdx\tj j }n tdt|tjt||S)zCReturns an empty array Ref with same shape/dtype/memory space as x.z empty_ref_like does not support  memory_space) pl_core MemoryRefr"jax_coreShapeDtypeStruct MemorySpaceANY ValueErrortypenew_refr)rr"s rempty_ref_liker,7st    ^^l   " " $((,,l % 9$q'C DD   *Q-l CCr conditioncfd}|S)aCalls the decorated function when the condition is met. Args: condition: If a boolean, this is equivalent to ``if condition: f()``. If an array, ``when`` produces a :func:`jax.lax.cond` with the decorated function as the true branch. Returns: A decorator. clttr r|yytj|dy)Ncyrr r rrrz(when.._wrapped..Usr) isinstanceboolr cond)fr-s r_wrappedzwhen.._wrappedPs.)T"    1l3rr )r-r5s` rwhenr6Cs4 /r)stepunrolllowerupperr8r9cTtttjfsqt j }t j|t j|t j|t jd|ndfd}|S)z@Returns a decorator that calls the decorated function in a loop.r)rcttjtjz fddy)Nc |zzSrr )idx_bodyr:r8s rrz)loop..decorator..ostEC$J./r)init_valr9)lax fori_looppl_utilscdiv)rAr:r8r9r;zeros`r decoratorzloop..decoratorks-MM  eemT*/ r) allmapr% is_concretejnp result_typerCconvert_element_typearray)r:r;r8r9idx_typerHrGs```` @rlooprQYs S%%ud'; < =ueT2H  $ $UH 5E  $ $UH 5E  # #D( 3D 99Qh 'D D rjax_pallas_enable_debug_checksFzTIf set, ``pl.debug_check`` calls are checked at runtime. Otherwise, they are a noop.)defaulthelpc"tjS)z#Returns runtime checks are enabled.)_ENABLE_DEBUG_CHECKSvaluer rrdebug_checks_enabledrXs  # ##rc.tj||S)zpCheck the condition if :func:`~jax.experimental.pallas.enable_debug_checks` is set, otherwise do nothing. )r debug_check)r-messages rrZrZs   i 11rr out_shapemeshscratch_shapesnamec tttf xrftjfd}|S)Nc6tjtj|tjd t j fidxst ji fd}tjd} r|dS|S)Nctjtj|j|j t |dr-t|jx}tjs|SdS)Nr"r!) r%r+rCrrrhasattrr1r"r')outmss rrz/_make_kernel..wrapper..sbH$$ IIcii +3/"***BH,@,@    rr_ctjtjggt t rndit t rSiS)Nr ) pl_primitives run_scoped functoolspartialr1rr)arg_refsrAout_refsr^srr@z(_make_kernel..wrapper.._se  % %   D 78 7h 7'A>r)ANHJrc |dS)N.r )refs rrz/_make_kernel..wrapper..s #c(rr)r rr%r+r#core_mapr fun_name) operandsr@outsrkrlrAr] mesh_kwargsr_r\r^ unwrap_outs @@rwrapperz_make_kernel..wrappers!!("2"2H=H!!   H  dLkL0K d8KLM   2H =D 47*d*r)r1tuplelistrjit)rAr\r]r^r_rsrurts`````` @r _make_kernelrysG")eT];;;Z; I77++ +8 .r)r^compiler_params interpret cost_estimatedebugr_metadatarArzr{r|r}r~c  | tdt|||||||||  t|tjr fdSt |fi S)aEntry point for creating a Pallas kernel. This is a convenience wrapper around ``core_map`` for executing a kernel over a mesh and ``run_scoped`` for allocating scratch memory. If ``body`` is provided, this function behaves as a decorator: .. code-block:: python def kernel_body(in_ref, out_ref): ... kernel = pl.kernel(kernel_body, out_shape=...) If ``body`` is omitted, this function behaves as a decorator factory and will return a decorator that can be used to annotate a kernel body: .. code-block:: python @pl.kernel(out_shape=...) def kernel(in_ref, out_ref): ... Args: body: The body of the kernel. If provided, this function behaves as a decorator, and if omitted, this function behaves as a decorator factory. out_shape: The shape of the output. Should be a PyTree of ``jax.ShapeDtypeStruct`` or ``jax.Array`` s. mesh: The mesh to run the kernel on. scratch_shapes: The shapes of the scratch arrays. compiler_params: The compiler parameters to pass to the backend. interpret: Whether to run the function in interpret mode. debug: Whether or not to out helpful debugging information. cost_estimate: The cost estimate of the function. name: The (optional) name of the kernel. metadata: Optional dictionary of information about the kernel that will be serialized as JSON in the HLO. Can be used for debugging and analysis. Returns: If ``body`` is provided, returns a function that runs the kernel. It should take any number of input operands and returns an output with the same PyTree structure as `out_shape`. If ``body`` is omitted, returns a decorator that can be used to annotate a kernel body. zout_shape must be provided.) r\r]r^rzr{r|r}r_r~ct|fiSr)ry)funkwdss rrzkernel..s|C040r)r)dictr1r NotSpecifiedry) rAr\r]r^rzr{r|r}r_r~rs @rkernelrset 2 33  #%!   $c&&' 00  % %%r)r N)6__doc__collections.abcrrrrijax._srcrrrr r%r r jax_typingr jax._src.lax_srcrCjax._src.lax.control_flowr jax._src.pallasr#rrgrrErrL named_callrobjectrArrayr,r2 ArrayLiker6intrQ bool_staterVenable_debug_checksrXrZMeshScratchShapeTreestrryrCompilerParams CostEstimaterrr rrrs77%)2+7-! syy!K&KK" Df D!1!1 Dj*** xD!"HRX$6674"# $            $J   x))*D012D89 <)v(($   +$d$ 2=?$( '"'||'")!9!9'Tz 'T0@s/?/?/A&*I&79<@"8<"-1I&C,,,I&tmI&I&#33 I& $22T9 I&  I&"..5I&I&tI&#s(^d*I&r