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This is an optimization that saves time in the backprop phase for recurrent frameworksYou can set this to the maximum t value that you want derivatives to be computed at when updating the model. This is an optimization that saves time in the backprop phase for recurrent frameworksAn alternative mechanism for setting the --max-deriv-time, suitable for situations where the length of the egs is variable. If set, it is equivalent to setting the --max-deriv-time to this value plus the largest 't' value in any 'output' node of the computation request.Set this to false to disable an optimization that reduces the size of certain per-row operationsThis is only relevant to training, not decoding. Set this to 0,1,2; higher levels are more aggressive at reducing memory by compressing quantities needed for backprop, potentially at the expense of speed and the accuracy of derivatives. 0 means no compression at all; 1 means compression that shouldn't affect results at all.optimizeconsolidate-model-updatepropagate-in-placebackprop-in-placeextend-matricesoptimize-row-opssplit-row-opsconvert-additionremove-assignmentsallow-left-mergeallow-right-mergeinitialize-undefinedmove-sizing-commandsallocate-from-othermin-deriv-timemax-deriv-timemax-deriv-time-relativesnip-row-opsmemory-compression-levelIf true, turn on debug for the actual computation (very verbose!)If true, word probabilities will be correctly normalized (otherwise the sum-to-one normalization is approximate)Index in wordlist representing the begin-of-sentence symbolIndex in wordlist representing the end-of-sentence symbolIndex in wordlist representing the break symbol. It is not needed in the computation and we are including it for ease of scriptingIf true, turn on debug for the neural net computation (very verbose!) Will be turned on regardless if --verbose >= 5debug-computationnormalize-probsbos-symboleos-symbolbrk-symboloptimizationdebugnouse-gpubatchnorm-test-modedropout-test-modernnlm-sentence-probs.ccIsSimpleNnet(rnnlm) This program takes input of a text corpus (with words represented by symbol-id's), and an already trained RNNLM model, and prints the log -probabilities of each word in the corpus. The RNNLM resets its hidden state for each new line. This is used in n-best rescoring with RNNLMs An example the n-best rescoring usage is at egs/swbd/s5c$ vi local/rnnlm/run_tdnn_lstm.sh Usage: rnnlm-sentence-probs [options] e.g.: rnnlm-sentence-probs rnnlm/final.raw rnnlm/final.word_embedding dev_corpus.txt > output_logprobs.txt yes|no|optional|wait, only has effect if compiled with CUDAIf true, set test-mode to true on any BatchNormComponents.If true, set test-mode to true on any DropoutComponents and DropoutMaskComponents.You must set --bos-symbol and --eos-symbol optionsInput file should contain only integers.SplitStringToIntegersmainN5kaldi15KaldiFatalErrorE;D4Ե\ ,t\tdJH4`b<:hH|zRx ش+zRx $FJ w?;*3$"Dp\pDW!A_zPLRxm   $AADP0HBBAA  ABA ( BBAA ^ ABA (H"HBAA L ABA (t>HBAA L ABA (ZHBAA L ABA (vHBAA L ABA (HBAA L ABA ($HBAA L ABA (PlBAA L ABA ,| BAA  ABA , BAA  ABA PM~BB B(A0A8D@ 8A0A(B BBBA k<BBA A(D`H (A ABBA 0pVBAA D0c  AABA HLAC K.~.F.~.F.~.F.{.H A PlWAC KT.Z.n.W.n.W.n.W.n.W.n.W.q.W.n.W.n.W.n.W.n.W.n.W.n.W.n.W.r.W.r.W.r.W.n.W.u.W.F A `AC N`.`..]..]..]..]..Z.J.N." 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