ó àÆ÷Xc@`s*dZddlmZmZmZddlmZddlZddlj j Z ddl Z ddl Z ddl mZddlmZmZddlmZddlZd"d„Zd ejfd „ƒYZeƒZd efd „ƒYZeƒZd#d „Zdejfd„ƒYZeƒZd$d„Zdejfd„ƒYZ e ƒZ!e!Z"dejfd„ƒYZ#dd„Z%d„Z&ie&_'d%d„Z(d&Z)d„Z*dejfd„ƒYZ+dd„Z,d'd„Z-dejfd„ƒYZ.d(dd„Z/d ejfd!„ƒYZ0e0ƒZ1dS()sº This file contains auxiliary Ops, used during the compilation phase and Ops building class (:class:`FromFunctionOp`) and decorator (:func:`as_op`) that help make new Ops more rapidly. i(tabsolute_importtprint_functiontdivision(t OrderedDictN(tgof(t iteritemst integer_types(txrangecC`s||ftj|sc C`s~|\}|\}|d}|jdjj} | |jkr\|j| \} } | tƒStt|ƒj|||||ƒS(Ntfaili(tinputsR RR tlocalstsuperRtc_code( RRtnodenameRRtsubtinametonameRtitypeR R ((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRAs    cC`sg}xltt|jƒdd„ƒD]L\}\}}|sXtjd|ddƒdS|jt|ƒ|fƒq%Wt|ƒS(NtkeycS`st|dƒS(Ni(tstr(tpair((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pytSss‚Type %s has C code for ViewOp, but it has no version. You should add a 'version' keyword arg when calling register_view_op_c_code.t stackleveli((tsortedRR twarningstwarntappendR%ttuple(RR tttctv((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pytc_code_cache_versionNs cC`s|S(N((RRt input_shapes((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyt infer_shape^scC`s|S(N((Rtargstg_outs((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pytgradas(( Rt __module__t__doc__tview_mapR t __props__RRRRR1R3R6(((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR)s     t OutputGuardcB`s$eZdZidgd6ZeZRS(sm This op is used only internally by Theano. Only the AddDestroyHandler optimizer tries to insert them in the graph. This Op is declared as destructive while it is not destroying anything. It returns a view. This is used to prevent destruction of the output variables of a Theano function. There is a mechanism in Theano that should prevent this, but the use of OutputGuard adds a safeguard: it may be possible for some optimization run before the add_destroy_handler phase to bypass this mechanism, by making in-place optimizations. TODO: find a current full explanation. i(RR7R8t destroy_maptFalset check_input(((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR;gscC`s||ftj|R:RBRRR1R(((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR?’s   cC`s||ftj|R:RRR3RYR6R_RR1(((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRJâs       tShape_icB`sweZdZeZiZeZd Zd„Z d„Z d„Z d„Z d„Z d„Zd„Zd „Zd „ZRS( s^ L{Op} to return the shape of a matrix. Notes ----- Non-differentiable. ticC`sat|tjƒr0|jtjjks0t‚n|t|ƒksHt‚t|ƒ}||_ dS(N( RLtnptndarrayRRRMROtinteger_dtypestAssertionErrortintRc(RRc((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRBRs  cC`sd|jj|jfS(Ns%s{%i}(RRRc(R((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR[scC`sst|tjƒs$td|ƒ‚n|j|jkrQtd||jfƒ‚ntj||gtjjƒgƒS(Ns&x must be Variable with ndim attributes$x has too few dimensions for Shape_i( RLRMRNt TypeErrortndimRcRROtlscalar(RR((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR^s cC`sd|\}|\}|ddkrHtj|j|jddƒ|dR ((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR„s    cC`sdgS(N(((RRR2((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR3’scC`s tggS(N(R=(RR((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRY•sc C`s,tjjd|ddd|dddƒgS(Ntoptx_posiRtcomments5No gradient for the shape of a matrix is implemented.(RMRZtgrad_not_implemented(RRR\((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR6s (Rc(RR7R8R`RaR R=R>R:RBRRRR1RR3RYR6(((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRb=s      c`s™ˆdkr't|dƒr'|j‰nˆrŽtˆdƒrŽˆj‰ˆj‰‡‡‡‡fd†‰|ˆkr‚ˆ|jƒnˆ||S|j|S(si Equivalent of var.shape[i], but apply if possible the shape feature optimization. This is useful in optimization that need to get the shape. This remove the need of the following shape_feature optimization that convert it. So this speed up optimization and remove Equilibrium max iteration problems. Parameters ---------- var The variable we want to take the shape of. i The shape dimensions we want fgraph : optional If var.fgraph do not exist, the fgraph that have the shape_feature to introduce var in to get the optimized shape. tfgrapht shape_featurec`sZ|jdˆkrVx*|jD]}|jrˆ|jƒqqWˆjˆ|dƒndS(Nisgof.ops.shape_i(toutputsRtownert on_import(RR(RqtrecurRrtshape_of(s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRv¿s   N(R]RDRqRrRwRtRU(tvarRcRq((RqRvRrRws2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pytshape_i¤s     cC`s6|}|tjkr+t|ƒtj|R ((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pytregister_shape_i_c_codeÚscC`s6t|ƒddl}|j|}t||ƒ}|S(Ni(t __import__tsystmodulestgetattr(tmodRGR~tmoduletobj((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyt load_backòs    tFromFunctionOpcB`sMeZdZd„Zd„Zd„Zd„Zd„Zd„Zd„Z RS(sç Build a basic Theano Op around a function. Since the resulting Op is very basic and is missing most of the optional functionalities, some optimizations may not apply. If you want to help, you can supply an infer_shape function that computes the shapes of the output given the shapes of the inputs. Also the gradient is undefined in the resulting op and Theano will raise an error if you attempt to get the gradient of a graph containing this op. cC`sF||_||_||_||_|jdk rB|j|_ndS(N(t_FromFunctionOp__fntitypestotypest_FromFunctionOp__infer_shapeR]t _infer_shapeR3(RtfnR‡RˆR3((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRB s     cC`s(t|ƒt|ƒko'|j|jkS(N(R R†(Rtother((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyt__eq__scC`stt|ƒƒt|jƒAS(N(thashR R†(R((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyt__hash__scC`sd|jjS(NsFromFunctionOp{%s}(R†R(R((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRscC`s|j|Œ}t|ttfƒs0|f}nt|ƒt|ƒksNt‚x,tt|ƒƒD]}||||dSss'itypes has to be a list of Theano typescs`s"|]}t|tjƒ VqdS(N(RLRMR˜(R™R.((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pys Wss'otypes has to be a list of Theano typess"infer_shape needs to be a callablec`st|ˆˆˆƒS(N(R…(R‹(R3R‡Rˆ(s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pytmake_opasN(RLRR-tanyRiR]tcallable(R‡RˆR3Rš((R3R‡Rˆs2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pytas_op7s    cC`s||ftj| addbroadcast patternbroadcast Notes ----- Works inplace and works for CudaNdarrayType. Example ------- `Rebroadcast((0, True), (1, False))(x)` would make `x` broadcastable in axis 0 and not broadcastable in axis 1. itaxiscG`sŸt|ƒ}t|ƒ|_x}t|jƒD]l\}}t|tjtfƒsgtdj |ƒƒ‚nt|tj t fƒs+tdj |ƒƒ‚q+q+WdS(Ns&Rebroadcast needs integer axes. Got {}s8Rebroadcast needs bool for new broadcast pattern. Got {}( R)RR RRLRdtintegerRRitformattbool_tbool(RR titemstbroad((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRB—s   cC`s1tt|jƒƒ}tt|ƒt|ƒfƒS(N(R)RR RŽR R-(RR¥((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyR¤scC`s£t|jƒdkrg}n2gtdt|jjƒƒƒD] }d^q>}x3t|jƒD]"\}}tt|ƒƒ||R:RBRRRRR6R3R_RR1(((s2/tmp/pip-build-X4mzal/theano/theano/compile/ops.pyRžxs      cC`s|||ftj|sJ     ;   :  W g .    = / Ž w