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LIĺH5Hs$LIĺH5Hs(LH0H@H9tI_IIGAGHHHpH9H0HWH0HjHHxHI?H0H@H95H9IWIH8IGH@IGHH0H@HDž8H0H0H@H9tHHPHPH@@HHH@HXHHH9tHH@HXHPH{@HHPHPHRH@HPHH@HH{pLHMdH3 %(He[A\A]A^A_]H8HtHu @H8IGIH@HHGHHjHxHI?HH H9tsH90IWIHIGH IGH#HH HDžHHH H9NDHHtHu HIGIH HLII?H9tLHPHHH0H@H9tHIH8IGH@IGH@H0QIHIGH IGH HAWAVAUATUSHHHt$XHHT$`dH%(H$1G(D$ D0)ljAD$ D$Dk C,D$k4D)ljD$D$(Ds$CHD$LcfHDŽ$HDŽ$HDŽ$MH?I9%JHD$HH$H|$H8H$HI9uH$HH)H|$D$D$LD$(D$PDAƉD$DD|$TD$D$t$ t$hl$DEAl$HD$Et9ExqxmExht$A 4A;NZANIcI6HHD{C KD uH$Ht$H|$(NH "H5H=H )H5H=HHH$H;$tH "H5H=H )H5H=HA\$D9t$(HD$`D$hD$lD$pA܋D$LHDŽ$DŽ$DŽ$DŽ$EADžEC;|$,0L$9T$HHcHL$@HH$D$$D$P$Ht$@HT$8H|$0H|$@H$dH3%(uHĨ[]A\A]A^A_HHH=HH5H=Hkaldi::KaldiFatalErrorHøYG GGG?GG G økøCøøøHHinput_x_dim_ > 0nnet-combined-component.ccinput_y_dim_ > 0input_z_dim_ > 0pool_x_size_ > 0pool_y_size_ > 0pool_z_size_ > 0pool_x_step_ > 0pool_y_step_ > 0pool_z_step_ > 0input_x_dim_ >= pool_x_size_input_y_dim_ >= pool_y_size_input_z_dim_ >= pool_z_size_pool_x_size_ >= pool_x_step_pool_y_size_ >= pool_y_step_pool_z_size_ >= pool_z_step_other != NULLto_update != NULL../matrix/kaldi-vector.h../cudamatrix/cu-matrix-inl.htok == ""w_h_.Dim() == cell_dim_../cudamatrix/cu-vector.hSameDim(h_t, *h_t_deriv), input-x-dim=, input-y-dim=, input-z-dim=, filt-x-dim=, filt-y-dim=, filt-x-step=, filt-y-step=, input-vectorization=, num-filters=filter-paramsbias-paramscell-dimself-repair-thresholdself-repair-scaleparam-meanparam-stddevalpharankupdate-period, cell-dim=w_h, self-repair-threshold=, self-repair-scale=, count=, self-repaired-proportion=, value-avg=, deriv-avg=, alpha=, rank=, update-period=, recurrent-dim=, rank-in=, rank-out=recurrent-dimrank-inrank-outfalsetrue, use-dropout=../cudamatrix/cu-matrix.hw_icw_fcw_oc, ={ self-repair-lower-threshold= }input-x-diminput-y-diminput-z-dimpool-x-sizepool-y-sizepool-z-sizepool-x-steppool-y-steppool-z-stepBad initializer tanh-self-repair-thresholdsigmoid-self-repair-thresholduse-dropout: ""zyxfilt-x-dimfilt-y-dimfilt-x-stepfilt-y-stepinput-vectorization-orderyzxmatrixnum-filtersbias-stddev, pool-x-size=, pool-y-size=, pool-z-size=, pool-x-step=, pool-y-step=, pool-z-step=index < column_map_sizeinput_vectorization_ == kYzxi_t_sigmoidf_t_sigmoidc_t_tanho_t_sigmoidm_t_tanh(input_x_dim_ - pool_x_size_) % pool_x_step_ == 0(input_y_dim_ - pool_y_size_) % pool_y_step_ == 0(input_z_dim_ - pool_z_size_) % pool_z_step_ == 0params.Dim() == NumParameters()params->Dim() == NumParameters()params.Dim() == this->NumParameters()static_cast(origin)+ static_cast(length) <= static_cast(t.Dim())num_rows == 0 && num_cols == 0row_offset >= 0 && col_offset >= 0 && num_rows >= 0 && num_cols >= 0 && row_offset + num_rows <= mat.num_rows_ && col_offset + num_cols <= mat.num_cols_in.NumRows() == out->NumRows() && in.NumCols() == InputDim() && out->NumCols() == OutputDim()params->Dim() == this->NumParameters()filter_params.NumRows() == bias_params.Dim() && bias_params.Dim() != 0filter_params.NumCols() == filt_x_dim * filt_y_dim * input_z_dim(input_x_dim_ - filt_x_dim_) % filt_x_step_ == 0(input_y_dim_ - filt_y_dim_) % filt_y_step_ == 0param_stddev >= 0.0 && bias_stddev >= 0.0mat.NumCols() == (filter_dim + 1)bias_params_.Dim() == filter_params_.NumRows()cell_dim_ > 0 && recurrent_dim_ > 0 && recurrent_dim_ <= cell_dim_ && self_repair_threshold_ >= 0.0 && self_repair_scale_ >= 0.0w_h_.NumRows() == cell_dim_ && w_h_.NumCols() == recurrent_dim_value_sum_.Dim() == cell_dim_ && deriv_sum_.Dim() == cell_dim_cell_dim_ > 0 && self_repair_threshold_ >= 0.0 && self_repair_scale_ >= 0.0tok == ""cell_dim > 0 && param_stddev >= 0.0 && tanh_self_repair_threshold >= 0.0 && tanh_self_repair_threshold <= 1.0 && sigmoid_self_repair_threshold >= 0.0 && sigmoid_self_repair_threshold <= 0.25 && self_repair_scale >= 0.0 && self_repair_scale <= 0.1SameDim(out_value, out_deriv) && in_value.NumRows() == out_value.NumRows() && in_value.NumCols() == InputDim() && out_value.NumCols() == OutputDim() && (in_deriv == NULL || SameDim(in_value, *in_deriv)) && memo == NULLin_deriv != NULL || to_update != NULLcell-dim > 0 is required for GruNonlinearityComponent.Invalid values for cell-dim and recurrent-dimstatic_cast(i) < static_cast(num_rows_)cudaMemcpyAsync(&value, data_, sizeof(Real), cudaMemcpyDeviceToHost, cudaStreamPerThread)Could not process these elements in initializer: Invalid initializer for layer of type Unknown or unsupported input vectorization order accepted candidates are 'yzx' and 'zyx'out_deriv.NumRows() == num_frames && out_deriv.NumCols() == (num_filters * num_x_steps * num_y_steps)(*out).NumRows() == num_frames && (*out).NumCols() == (num_filters * num_x_steps * num_y_steps)vector_index < rev_col_map_sizememo == NULL../nnet3/nnet-component-itf.hHuHH xH5H=SHHH@HHXH{@[SHHH@HHXH{@H[HHH@HHSHHH@HH[YaYa@H!"-+ #._z5=Q <   5@}x+Y #1 #1%-Xm #15M,>g|R&4` #11<e}( Ht #1%-L+ddN3,4'd17d)p'ep%x+x7}\s)} $O   7}\s){  8=]vA       b9-tA  e'  0  0  m fI 0   0  y@-{ K           t!&"&"& "  i&$#P#/##TGZ j         -.    p'b       0 ? ' -2,  E      /,*   Fx ynQ2x+x>$$  G   $ $  s0V#"A  $ $  #"V]ESHHH@HHHH{@H{0H{ [SHHH@HHHHHH{PH{@H{([SHHH@HHHHH{pH{XH{@H{ [SHHH@HHHH{@H{0H{ H[SHHH@HHHHHH{PH{@H{(H[SHHH@HHHHH{pH{XH{@H{ H[USH8HdH%(HD$(1HHHHs(HHHH@HEH<$HD$H9tHH5HHH<$HD$H9tHHHUSHH0HHHHHHHH[]USHH(HHHHHHHH[]USHHHHHHHHHH[]SHHH@HHHHCXH9tHH@HH{8[SHHH@HHHHCXH9tHH@HH{8H[HHGG GtREtMxrExmxiExd;F \C;FSHcFHcHMcIHJHDOO FGD uHH "H5H=H )H5H=ATUSHHGHH9tIHSH)HH HHH!HD@L$ HL9tH;HtH}Ht[]A\../base/io-funcs-inl.h vs. read it later, if needed., next char is ReadBasicType: encountered end of stream.ReadBasicType: did not get expected integer type, . You can change this code to successfullyRead failure in ReadBasicType, file position is ATUSHHHdH%(H$1@*Aăt<uoHH H\$A?H HHH{ H5Ht$H|$HH|$0HH\$ADH HHH{ H5AH|$0H|$0H5H|$0H|$0H5H|$0H5Ht$H|$HH|$0HHHH@D u#H$dH3%(Hİ[]A\Hl$AVH HHH} H5HH|$0HH|$0H5HH|$0Ht$H|$HH|$0H Write failure in WriteBasicType.SHHT$ dH%(H$1@tJHt$ HHH@D u?H$dH3%(H[Ët$ H5HH\$ A2H HHH{ H5Ht$ H|$HH|$@HUSHHHHGvHHH[]USHHHHGvHHH[]../cudamatrix/cu-value.hcudaError_t : "" returned from ''cudaMemcpyAsync(data_, &r, sizeof(Real), cudaMemcpyHostToDevice, cudaStreamPerThread)cudaStreamSynchronize(cudaStreamPerThread)USHHD$ dH%(H$1fH=ffH8t@H8yNHD$ D$ H$dH3%(H[]fH=ffHHHt$ AH;ÅuÅD$ Hl$ A:H HHH} H5H|$@H|$@H5H|$@HH|$@H5H|$@H5H|$@H5Ht$ H|$HH|$@HHl$ A;H HHH} H5H|$@H|$@H5H|$@HH|$@H5H|$@H5H|$@H5Ht$ H|$HH|$@HV 9W tËF9GSt HH?HtH=tC[ÿUSH(HdH%(HD$1fH=ffH8tWH8 H;fH=ffH8t=H+H8uHHH=fH=ffHHfH=ffHHHHH$D$H=tHHuD$HH=|$tAH<$Ht8H=t.'HÀ|$tHHH;HtCHHD$dH3%(uH([]vector::_M_realloc_insertAWAVAUATUSHHH4$IHHGH)HHt?L<L9HI9III)Mt I9v L4$MI)AJ<HItI$IL#MM)M9tLLHNt5HCHL)HL$L9tHH4$LLt$MtLH+LsJDHCH[]A\A]A^A_L4$MI)IVvector::_M_default_appendHlHOHWH)HHHH9r=HH HHtHtHH@H@HvHHGAWAVAUATUSHHt$HHH+IIHLH L)H9wHHD$L9IMBMrEH I9w6Mt=I9w'Kdata_, 0, this->dim_ * sizeof(T), cudaStreamPerThread)USHdH%(H$1u!H$dH3%(H[]HfH=ffH8H8H8HcSHH;ÅuzfH=ffH8H\$fH=ffHHH5H4fH=ffHHYH|$HwfHl$0AH HHH} H5H|$PH|$PH5H|$PHH|$PH5H|$PH5H|$PH5Ht$0H|$HH|$PHfH=ffHHHcSHH;(resize_type == kSetZero || resize_type == kUndefined) && dim >= 0Memory allocation failed when initializing CuVector CuArray::Resizewith dimension object size in bytes: AUATUSHdH%(H$1x;HAԃw.9wuOtDH$dH3%(H[]A\A]H ,H5H=tfH=ffH8H8H8fH=ffH8HcL,H8LH=ILm]EMfH=ffH8<Ll$fH=ffHLH5H]EHfH=ffHH H|$HwfH=ffHHHHH$D$H=tHHuD$LH=Iŀ|$H<$HH=HÀ|$tHHHfH=ffHHHcHHEHHl$0AGH HHH} H5H|$PH5H|$PH|$PH5H|$PHt$0H|$HH|$PHcudaMemcpyAsync(this->data_, &src.front(), src.size()*sizeof(T), cudaMemcpyHostToDevice, cudaStreamPerThread)USHHHdH%(H$1HvH+3HHCH9fH=ffH8H8{H8H3HSH)AH}ÅÅTfH=ffH8H\$fH=ffHHH5HH$dH3%(H[]fH=ffHH!H|$Hw.Hl$0AH HHH} H5H|$PH|$PH5H|$PHH|$PH5H|$PH5H|$PH5Ht$0H|$HH|$PHHl$0AH HHH} H5H|$PH|$PH5H|$PHH|$PH5H|$PH5H|$PH5Ht$0H|$HH|$PHfH=ffHHH3H}HSH)DeleteMemoUnVectorizeVectorizeDotProductCheckAddTanhStatsAndSelfRepairBackpropPropagateInitFromConfigUnVectorizeVectorizeDotProductCheckAddTanhStatsAndSelfRepairBackpropPropagateInitFromConfigInitFromConfigCuSubVectoroperator=InitBackpropUnVectorizeVectorizeDotProductAddRowoperator Realoperator RealRowReadInderivPatchesToInderivInputToInputPatchesInitFromConfigCheckUnVectorizeSubVectorVectorizeSetParamsWriteBasicTypeReadBasicTypeReadUpdateBackpropInderivPatchesToInderivAddPropagateSetZeroResizeCopyFromVecInputToInputPatchesInitFromConfigCuSubMatrixInitInitConvolutionComponentN5kaldi15KaldiFatalErrorEN5kaldi5nnet320ConvolutionComponentEN5kaldi5nnet325LstmNonlinearityComponentEN5kaldi5nnet319MaxpoolingComponentEN5kaldi5nnet324GruNonlinearityComponentEN5kaldi5nnet330OutputGruNonlinearityComponentE?zD>?@x?? 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