ó àÆ÷Xc@`s‘ddlmZmZmZddlZddljjZddl m Z ddl Z ddl m Z ddlZd„Zd„Zd„ZdS(i(tabsolute_importtprint_functiontdivisionN(txrange(ttensorcC`sœtjƒ}tjƒ}tj||g||ƒ}|tjdddƒtjdddƒƒy|tjdƒƒWntk rŠdSXd s˜t‚dS(Ni tdtypetint64sshould not get here(tTtlvectorttheanotfunctiontnumpytonest TypeErrortAssertionError(txtytf((s;/tmp/pip-build-X4mzal/theano/theano/tensor/tests/test_gc.pyt test_no_reuse s  + c C`s›tjƒ}x1tdƒD]#}|r6||d}q|}qWd}d}xHtjdtƒtjdtƒftjdtƒtjdtƒfgD]þ\}}tj |g|dtj d|d|ƒƒ}tj |g|dtj d|d|ƒƒ}t j |ƒ}t j |ƒ} t |ƒ} t | ƒ} d„} | |ƒ| |ƒksXt‚| |ƒ| |ƒksvt‚d „} | |ƒ| |ƒkst‚d „}||ƒ||ƒksÄt‚||ƒ||ƒksât‚|tjd d d ƒƒ|tjd d d ƒƒt j |ƒ}t j |ƒ}t |ƒ}t |ƒ}| |ksht| |fƒ‚t||ƒdks•t|||fƒ‚q•WdS(Nii tfast_runtallow_gctmodet optimizertlinkercS`sttj|jƒƒS(N(tlentpickletdumpstmaker(tfn((s;/tmp/pip-build-X4mzal/theano/theano/tensor/tests/test_gc.pyta>scS`s"ttjtjjj|ƒƒƒS(N(RRRR tcompiletfunction_modulet_pickle_Function(R((s;/tmp/pip-build-X4mzal/theano/theano/tensor/tests/test_gc.pytbCs cS`sttj|ƒƒS(N(RRR(R((s;/tmp/pip-build-X4mzal/theano/theano/tensor/tests/test_gc.pytcJsidRtfloat64i(RtdvectorRtNoneR t PerformLinkertTruetFalset OpWiseCLinkerR tModeRRRRR R tabs(RtitrRtf_linkertg_linkerRtgtpre_ftpre_gt len_pre_ft len_pre_gRR!R"tpost_ftpost_gt len_post_ft len_post_g((s;/tmp/pip-build-X4mzal/theano/theano/tensor/tests/test_gc.pyt!test_gc_never_pickles_temporariessJ  "! !        cC`s“tjƒ}x1tdƒD]#}|r6||d}q|}qWtjƒ}tj|g|ddƒ}tjƒ|}|dkst|ƒ‚dS(séIn the original merge optimization, the following graph took like caused the MERGE optimizer to exhibit really bad performance (quadratic? exponential?) Ironically, there is actually no merging to do in this graph. i2i Rt FAST_COMPILEg@N(RR$RttimeR R R(RR,R-ttRtdt((s;/tmp/pip-build-X4mzal/theano/theano/tensor/tests/test_gc.pyttest_merge_opt_runtimefs   (t __future__RRRR tsix.moves.cPickletmovestcPickleRt six.movesRR RRR;RR9R>(((s;/tmp/pip-build-X4mzal/theano/theano/tensor/tests/test_gc.pyts     M