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5684 ` delegate_registry.cc.o/ nnapi_plugin.cc.o/ stable_delegate_registry.cc.o/ flatbuffer_conversions.cc.o/ op_resolver.cc.o/ tensor_utils.cc.o/ async_kernel.cc.o/ async_signature_runner.cc.o/ attribute_map.cc.o/ attribute_map_internal.cc.o/ reconcile_fns.cc.o/ async_signature_runner.cc.o/ async_subgraph.cc.o/ task_internal.cc.o/ c_api_experimental.cc.o/ c_api_opaque.cc.o/ create_op_resolver_with_builtin_ops.cc.o/ interpreter.cc.o/ interpreter_builder.cc.o/ interpreter_experimental.cc.o/ model_building.cc.o/ signature_runner.cc.o/ verifier_internal.cc.o/ c_api_for_testing.cc.o/ c_api_opaque_internal.cc.o/ common_internal.cc.o/ external_delegate.cc.o/ delegate_options.cc.o/ tflite_profile.cc.o/ android_info.cc.o/ cl_arguments.cc.o/ cl_command_buffer.cc.o/ cl_command_queue.cc.o/ cl_image_format.cc.o/ cl_operation.cc.o/ environment.cc.o/ inference_context.cc.o/ opencl_wrapper.cc.o/ program_cache.cc.o/ qcom_thin_filter.cc.o/ tensor_type_util.cc.o/ recordable_queue.cc.o/ 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convolution_transposed_3x3_thin.cc.o/ convolution_transposed_4x4.cc.o/ convolution_transposed_thin.cc.o/ depthwise_conv.cc.o/ depthwise_conv_3x3.cc.o/ depthwise_conv_3x3_stride_h2.cc.o/ elementwise.cc.o/ fully_connected.cc.o/ max_unpooling.cc.o/ mean_stddev_normalization.cc.o/ quantize_and_dequantize.cc.o/ space_to_depth.cc.o/ strided_slice.cc.o/ conv_pointwise.cc.o/ dw7x7_conv2to6_concat_conv8to8.cc.o/ thin_pointwise_fuser.cc.o/ add_quant_adjustments.cc.o/ fuse_add_to_conv.cc.o/ fuse_mul_to_conv.cc.o/ global_pooling_to_reduce_op.cc.o/ make_fully_connected.cc.o/ make_padding.cc.o/ merge_densify.cc.o/ merge_padding_with.cc.o/ model_transformations.cc.o/ remove_noop.cc.o/ gpu_compatibility.cc.o/ op_signature.cc.o/ op_signature.cc.o/ nnapi_delegate_disabled.cc.o/ interpreter_utils.cc.o/ serialization.cc.o/ cache_buffer.cc.o/ initialization_status.cc.o/ resource_variable.cc.o/ static_hashtable.cc.o/ fully_connected_reference.cc.o/ neon_tensor_utils.cc.o/ sse_tensor_utils.cc.o/ comparisons.cc.o/ portable_tensor_utils.cc.o/ kernel_utils.cc.o/ mfcc_mel_filterbank.cc.o/ opaque_tensor_ctypes.cc.o/ portable_tensor_utils.cc.o/ quantization_util.cc.o/ runtime_shape.cc.o/ spectrogram.cc.o/ tensor_ctypes.cc.o/ tensor_utils.cc.o/ transpose_utils.cc.o/ activations.cc.o/ arg_min_max.cc.o/ assign_variable.cc.o/ atan2_custom.cc.o/ audio_spectrogram.cc.o/ batch_matmul.cc.o/ batch_to_space_nd.cc.o/ bidirectional_sequence_lstm.cc.o/ bidirectional_sequence_rnn.cc.o/ bitwise_xor.cc.o/ broadcast_args.cc.o/ broadcast_to.cc.o/ comparisons.cc.o/ complex_support.cc.o/ concatenation.cc.o/ control_flow_common.cc.o/ conv3d_transpose.cc.o/ cpu_backend_context.cc.o/ cpu_backend_gemm_eigen.cc.o/ deprecated_backends.cc.o/ depth_to_space.cc.o/ depthwise_conv.cc.o/ detection_postprocess.cc.o/ dynamic_update_slice.cc.o/ eigen_support.cc.o/ elementwise.cc.o/ embedding_lookup.cc.o/ embedding_lookup_sparse.cc.o/ expand_dims.cc.o/ fully_connected.cc.o/ hashtable_find.cc.o/ hashtable_import.cc.o/ hashtable_lookup.cc.o/ hashtable_size.cc.o/ kernel_util.cc.o/ local_response_norm.cc.o/ lsh_projection.cc.o/ matrix_diag.cc.o/ matrix_set_diag.cc.o/ maximum_minimum.cc.o/ multinomial.cc.o/ non_max_suppression.cc.o/ numeric_verify.cc.o/ random_standard_normal_custom.cc.o/ random_uniform_custom.cc.o/ read_variable.cc.o/ register_ref.cc.o/ resize_bilinear.cc.o/ resize_nearest_neighbor.cc.o/ reverse_sequence.cc.o/ right_shift.cc.o/ rng_bit_generator.cc.o/ segment_sum.cc.o/ sign_custom.cc.o/ space_to_batch_nd.cc.o/ space_to_depth.cc.o/ sparse_to_dense.cc.o/ squared_difference.cc.o/ stablehlo_add.cc.o/ stablehlo_and.cc.o/ stablehlo_case.cc.o/ stablehlo_composite.cc.o/ stablehlo_elementwise.cc.o/ stablehlo_gather.cc.o/ stablehlo_min_max.cc.o/ stablehlo_multiply.cc.o/ stablehlo_pad.cc.o/ stablehlo_reduce_window.cc.o/ stablehlo_scatter.cc.o/ stablehlo_shift_left.cc.o/ strided_slice.cc.o/ tensor_slice_util.cc.o/ transpose_conv.cc.o/ unidirectional_sequence_gru.cc.o/ 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Are you using old TFLite binary with newer model?Didn't find op for builtin opcode '%s' version '%d'. An older version of this builtin might be supported. Are you using an old TFLite binary with a newer model? Operator with CUSTOM builtin_code has no custom_code. ADDAVERAGE_POOL_2DCONCATENATIONCONV_2DDEPTHWISE_CONV_2DDEPTH_TO_SPACEDEQUANTIZEEMBEDDING_LOOKUPFLOORFULLY_CONNECTEDHASHTABLE_LOOKUPL2_NORMALIZATIONL2_POOL_2DLOCAL_RESPONSE_NORMALIZATIONLOGISTICLSH_PROJECTIONLSTMMAX_POOL_2DMULRELURELU_N1_TO_1RELU6RESHAPERESIZE_BILINEARRNNSOFTMAXSPACE_TO_DEPTHSVDFTANHCONCAT_EMBEDDINGSSKIP_GRAMCALLCUSTOMEMBEDDING_LOOKUP_SPARSEPADUNIDIRECTIONAL_SEQUENCE_RNNGATHERBATCH_TO_SPACE_NDSPACE_TO_BATCH_NDTRANSPOSEMEANSUBDIVSQUEEZEUNIDIRECTIONAL_SEQUENCE_LSTMSTRIDED_SLICEBIDIRECTIONAL_SEQUENCE_RNNEXPTOPK_V2SPLITLOG_SOFTMAXDELEGATEBIDIRECTIONAL_SEQUENCE_LSTMCASTPRELUMAXIMUMARG_MAXMINIMUMLESSNEGPADV2GREATERGREATER_EQUALLESS_EQUALSELECTSLICESINTRANSPOSE_CONVSPARSE_TO_DENSETILEEXPAND_DIMSEQUALNOT_EQUALLOGSUMSQRTRSQRTSHAPEPOWARG_MINFAKE_QUANTREDUCE_PRODREDUCE_MAXPACKLOGICAL_ORONE_HOTLOGICAL_ANDLOGICAL_NOTUNPACKREDUCE_MINFLOOR_DIVREDUCE_ANYSQUAREZEROS_LIKEFILLFLOOR_MODRANGERESIZE_NEAREST_NEIGHBORLEAKY_RELUSQUARED_DIFFERENCEMIRROR_PADABSSPLIT_VUNIQUECEILREVERSE_V2ADD_NGATHER_NDCOSWHERERANKELUREVERSE_SEQUENCEMATRIX_DIAGQUANTIZEMATRIX_SET_DIAGROUNDHARD_SWISHIFWHILENON_MAX_SUPPRESSION_V4NON_MAX_SUPPRESSION_V5SCATTER_NDSELECT_V2DENSIFYSEGMENT_SUMBATCH_MATMULPLACEHOLDER_FOR_GREATER_OP_CODESCUMSUMCALL_ONCEBROADCAST_TORFFT2DCONV_3DIMAGREALCOMPLEX_ABSHASHTABLEHASHTABLE_FINDHASHTABLE_IMPORTHASHTABLE_SIZEREDUCE_ALLCONV_3D_TRANSPOSEVAR_HANDLEREAD_VARIABLEASSIGN_VARIABLEBROADCAST_ARGSRANDOM_STANDARD_NORMALBUCKETIZERANDOM_UNIFORMMULTINOMIALGELUDYNAMIC_UPDATE_SLICERELU_0_TO_1UNSORTED_SEGMENT_PRODUNSORTED_SEGMENT_MAXUNSORTED_SEGMENT_SUMATAN2UNSORTED_SEGMENT_MINSIGNBITCASTBITWISE_XORRIGHT_SHIFTSTABLEHLO_LOGISTICSTABLEHLO_ADDSTABLEHLO_DIVIDESTABLEHLO_MULTIPLYSTABLEHLO_MAXIMUMSTABLEHLO_RESHAPESTABLEHLO_CLAMPSTABLEHLO_CONCATENATESTABLEHLO_BROADCAST_IN_DIMSTABLEHLO_CONVOLUTIONSTABLEHLO_SLICESTABLEHLO_CUSTOM_CALLSTABLEHLO_REDUCESTABLEHLO_ABSSTABLEHLO_ANDSTABLEHLO_COSINESTABLEHLO_EXPONENTIALSTABLEHLO_FLOORSTABLEHLO_LOGSTABLEHLO_MINIMUMSTABLEHLO_NEGATESTABLEHLO_ORSTABLEHLO_POWERSTABLEHLO_REMAINDERSTABLEHLO_RSQRTSTABLEHLO_SELECTSTABLEHLO_SUBTRACTSTABLEHLO_TANHSTABLEHLO_SCATTERSTABLEHLO_COMPARESTABLEHLO_CONVERTSTABLEHLO_DYNAMIC_SLICESTABLEHLO_DYNAMIC_UPDATE_SLICESTABLEHLO_PADSTABLEHLO_IOTASTABLEHLO_DOT_GENERALSTABLEHLO_REDUCE_WINDOWSTABLEHLO_SORTSTABLEHLO_WHILESTABLEHLO_GATHERSTABLEHLO_TRANSPOSEDILATESTABLEHLO_RNG_BIT_GENERATORREDUCE_WINDOWSTABLEHLO_COMPOSITESTABLEHLO_SHIFT_LEFTSTABLEHLO_CBRTSTABLEHLO_CASE.2BPXjy 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ZR|: PPv  2 Q: RP%  0P  2Q : R 0S:p 0C BS : 0P @ KKFO-M`p 0@RXH"^!*KBP@@ T B U PC@/o@  R HR:  XR: 7R:@T @^:@OoB @ R : R  ^: /o" KFO-M 0`@SZJ"\!*KBpP@@T B UPF?op@0S0JS:000ZS:@0@3T%:0S" `\:@OoB@ PU@PJU:00 C\:porp p0S*p10ZS: KFO-Mp @@W^ N"R!* K 0؀$P  `0R S"?o`D  r R NR: 00^S: 0㲀9Xn:PU% `R: /o" 0S 0NS: 0` PFR: /o"  `V* !0^S:X0B:PU' `R: /o" 0S 0NS: 0` PFR: /o"  0Q* ^Q: X0:`V @Rw: /o" r 0So 0NSk: 0@Pa  @ KFO-P`0@^\@L"T!* $ @ pR Y$o C@@r@T@LT:@PP\U: 6R : R  ^ \0L"S!: FO-Mp @W@T D" R!*K 0؀$P  `0R S"?o`J  r R DR: 00TS: 0㲀9Xr:PU% `R: /o" 0S 0DS: 0` PFR: /o"  `V* !0TS:X0F:PU) `R: /o" 0S 0DS: 0` PFR: o 0P*TP: X0:`V 0Ru: /o" p pWm 0DSh:00p`P4  @PPU 0 Q:PP  @PP> 0 Q:PP @ KKFO- Mp@@WZ J"R!* K 0؀$P  `0R S"0D _o b R JR: ppZW: P9 Up:pW$ 0X: /o"  R 0JS: 0p0GX: /o"  pW* !pZW:U E:pW( 0X: /o"  R 0JS: 0p0GX: o P*ZP: U :pW  0Rw: /o" r `Vo 0JSj:0 @pP<  P`PW 0 Q:PP%  P`P@ 0 Q:PP  0@P @  K KFO-MP@p@TZJ"^!*K"`0  R " S 0G oo   R JR: PPZU: P0U :0S 0T Z J"R!:U:@T  0JS: U : R  ^:o  KFO-M`p 0@RXH"^!*KBP@@ T B U PC@/o@  R HR:  XR: 7R:@T @^:@OoB @ R : R  ^: /o" KFO-M@p @W\ L"R!*K 0؀$P  `0R S"_o N00R0S0LS:000\S: 09Sn:pW$  X:`oob` `V `LV: `p GX:`oob` `pW*`ap\W:S C:pW'  X:`oob` `V `LV: `p GX:`oob` `P[*\WP: S :pW 0 Sx:0?o20s 0Sp LR=:  PP4  0P-  `PT 0 Q:PP 1P :Q  R0%  B"A R!4: @ KKFO-M 0`@SZJ"\!*KBpP@@T B UPF?op@0S0JS:000ZS:@0@3T%:0S" `\:@OoB@ PU@PJU:00 C\:porp p0S*p10ZS: KFO-M` @0@TPUE"^!*K $pp P W$p pCOo  PEP:@@UT:2P : R  ^:o  KFO-MP 0@U\@L"T!*K $ ` pR Y$_o`C  R R LR: pp\W:`ᶀ9Xm:pW+ `T: /o"  R` LR:`p` pFT:pporp `pV*p`pR`\  pV: RX<:`V `T: /o" X/:pW# `T: /o"  R `LV: ` FT%: /o" @ T* @\Tt: X: R  0LSk: 0@Q @ KKFO-M 0`@SZJ"\!*KBpP@@T B UPF?op@0S0JS:000ZS:@0@3T%:0S" `\:@OoB@ PU@PJU:00 C\:porp p0'S*0Z1JS: KFO-MP@@^\pL" W!*K"؀0  `R S"?o`J  ᣂ R LR: 00\S: `9V@:0S# ``W: /o"  R `LV: ` FW:o PU*0\`S:V: R  ^ \L"P!: V : R  ^ \L"P!:@ KFO-Mp @W`VF" ^!*K"@0  PR " S?oPJ  B R FR: 00VS: PᲐ5Y6:0S& p^: /o"  R pFW:  0B^:o R* W V R:PY : R  ^:o  KFO-M0p@S`VF"Y!*K $P P @R U$P?o @G  2 R FR: PPVU: @4\u: bX: @Y:P_oRP PU@PFU: @Pp@GY:P_oR0 P0%S*0V1FS: @00S `pPPj p`W: `\3: `V/ p J0 RPU E"R!: R 0ES: 0Pp G0S=0QPA"U!7:Pp%W3*pQ0AQ-:@P#  P`PS 0 Q:PP  0P @ KKFH-QP@Q`pP p`W:CO-Mp @W`VF" ^!*K"@0  PR " S?oPJ  B R FR: 00VS: PᲐ5Y6:0S& p^: /o"  R pFW:  0B^:o R* W V R:PY : R  ^:o  KFH-M`P@R`  `P 1/P  1/PK1/p pQ  2/ 0`P``2/PKP 1/\CLLPH- HL- @T P 1/LA 00R / /2.19.0vectorbasic_stringThe model allocation is null/emptyThe model is not a valid Flatbuffer bufferTFL3Model provided must have at least 7 bytes to hold identifier. 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Missing registration for opcode_index %d Skipping op for opcode_index %d Found builtin operator %s with custom options. Custom Option Offset for opcode_index %d is out of bound Quantization parameters has non-null scale but null zero_point.QuantizationParam has %d zero_point values and %d scale values. Must have same number.quantized_dimension must be in range [0, %d). Was %d.num_scales must be 1 for per-layer quantization, or %d for per-axis quantization, but got %d.Invalid sparsity parameter.The %dth dimension has unknown type: %d.The %dth sparse dimension has invalid parameters.Missing exported method name for SignatureDefNULL SignatureDef inputs for exported method %sNULL SignatureDef outputs for exported method %sTensor %d has invalid quantization parameters.Tensor %d is a variable tensor with buffer. It's not supported now. Tensor %d has invalid sparsity parameters.Tensor %d is invalidly specified in schema. num_threads should be >= 0 or just -1 to let TFLite runtime set the value.Null output pointer passed to InterpreterBuilder.Null pointer passed in as model.Model provided is schema version %d not equal to supported version %d. Registration failed. No subgraph in the model. No buffers in the model. Did not get tensors in subgraph %d. 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Constant buffer %d specified an out of range offset. InterpreterBuilder::operator()N6tflite12_GLOBAL__N_119MallocDataAllocatorECONVERSION_METADATA +6S\kp|5<N`josw #+04:BP[bhl{  # * 5 ? J Q \ a k q   . 4 ? 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The subgraph has %d tensors Tensor %d is both input %d and output %d AllocateTensors() called on inconsistent model.%s:%d %s != %s (%d != %d)tensor_at_index->allocation_typekTfLiteCustomAllocateTensorstensor.data.raw != nullptrtensor.allocation_typeAddNodeWithParameters is disallowed when graph is immutable.node inputsnode outputsResizeInputTensor was given a NULL shape.ResizeInputTensor is disallowed when graph is immutable.tensor_index < context_.tensors_size && tensor_index >= 0tensor->dims->sizedims.size()Attempting to resize dimension %d of tensor %d with value %d to %d. ResizeInputTensorStrict only allows mutating unknown dimensions identified by -1.Encountered unresolved custom op: %s. See instructions: https://www.tensorflow.org/lite/guide/ops_custom UnknownOpSelect TensorFlow op(s), included in the given model, is(are) not supported by this interpreter. Make sure you apply/link the Flex delegate before inference. For the Android, it can be resolved by adding "org.tensorflow:tensorflow-lite-select-tf-ops" dependency. 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TT=\`TK : dTQ p:M tT=p`TE: (T;$ TUp;Q T=`TG?; ąT5p<  p|< ԅT=`TF< T?p<; T=`TLL<`  TB= p= T=`T[=W ,Tp0= <T=`T 8= LTpP= \T=`TX=d lXT> Xp>T ĆT=aT D>C ܆HTCp@,C $TCp@C ,T=,aTD@hD <TD8C@D T5DpxC1D ćT=HaT Chw ԇ TC pC T=`aTC  @TE( LTp8E TT=|aTM>@E>> dHT>(F(> T=pPF= T=aTO2XFX2 ĈT2F 91pF51 ԈT=aTP+Flg+ T+0G *p-8\ k,pD\>g, TA=cT* L\ TD] pd\DY ,TF=cT+ l\ <TI1 p\I- LTKJ2\pM2]Lo]0]]p]@$Lo\Tv(,ccl_event.cc.o/ 1749669028 1000 1000 100644 8568 ` ELF(4(1  / P   *A/P/M-@Q p P 2/`p P  M/dL-@P 1/H- M00 dK-M`@0 P5/0p P `7/ UKHP/0   /PH-0@`0` PH  /L-@P 01/ ,8 T4$08<E߄AEEAA $LH- M-P@ R `U   PUp `aE߄K-@P R pUP  pE`0FpS:B:qU` P `3pU   EH- 0H-P@  A 8 ,H- basic_stringclang version 18.1.8A?aeabi5C2.09 A   "$&  !"#$&'()K      Ps Th ] R (E 4   4 8 2 H m b W L ,  *  D!x !& & &{ 2$83t 8 HTH\4xp"t":98T" *#J|"^L">$"&W,uS$W8T-`.`.P`2`2 50`2`2 894`;x-=`.****/**/** * *(*(*0/0*4*8/8*<*@/@*D*H*H*P*T*<*>? @**4AlB|CD/**8ABC-D/**E **FG4H<I@JD`KH`L*>*!*$M `N**&>JKmemcpy.rel.ARM.exidx__cxa_throw_ZSt9terminatev_ZdlPv_ZNK6tflite3gpu2cl7CLEvent4WaitEv_ZNK6tflite3gpu2cl7CLEvent14GetEventTimeNsEv_ZNK6tflite3gpu2cl7CLEvent16GetStartedTimeNsEv_ZNK6tflite3gpu2cl7CLEvent17GetFinishedTimeNsEv_ZNK6tflite3gpu2cl7CLEvent14GetEventTimeMsEv_ZN6tflite3gpu2cl7CLEvent7ReleaseEv_ZN6tflite3gpu2cl7CLEventD2Ev_ZN6tflite3gpu2cl7CLEventD1Ev_ZNSt12length_errorD1Ev.rel.ARM.exidx.text._ZNKSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE20__throw_length_errorB8ne180100Ev.rel.text._ZNKSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE20__throw_length_errorB8ne180100Ev.rel.text_ZN6tflite3gpu2cl7CLEventC2EP9_cl_event_ZN6tflite3gpu2cl7CLEventC1EP9_cl_event.comment.linker-options.ARM.attributes.L.str_ZTVSt12length_error_ZTISt12length_error.group__cxa_end_cleanup__cxa_allocate_exception__cxa_free_exception.note.GNU-stack_Znwj.rel.ARM.exidx.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE17__assign_no_aliasILb1EEERS5_PKcj.rel.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE17__assign_no_aliasILb1EEERS5_PKcj.ARM.extab.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE17__assign_no_aliasILb1EEERS5_PKcj.rel.ARM.exidx.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE17__assign_no_aliasILb0EEERS5_PKcj.rel.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE17__assign_no_aliasILb0EEERS5_PKcj.ARM.extab.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE17__assign_no_aliasILb0EEERS5_PKcj__cxa_begin_catch.llvm_addrsigmemmove.rel.ARM.exidx.text.__clang_call_terminate.rel.text.__clang_call_terminate__aeabi_ul2dcl_event.cc_ZNSt11logic_errorC2EPKc.rel.ARM.exidx.text._ZNSt3__120__throw_length_errorB8ne180100EPKc.rel.text._ZNSt3__120__throw_length_errorB8ne180100EPKc.rel.ARM.extab.text._ZNSt3__120__throw_length_errorB8ne180100EPKc.rel.ARM.exidx.text._ZNSt12length_errorC2B8ne180100EPKc.rel.text._ZNSt12length_errorC2B8ne180100EPKc.rel.ARM.extab.strtab.symtab_ZN6tflite3gpu2cl7CLEventaSEOS2__ZN6tflite3gpu2cl7CLEventC2EOS2__ZN6tflite3gpu2cl7CLEventC1EOS2__ZN6tflite3gpu2cl14clReleaseEventE_ZN6tflite3gpu2cl15clWaitForEventsE_ZN6tflite3gpu2cl23clGetEventProfilingInfoE_ZN6tflite3gpu2cl7CLEvent7SetNameERKNSt3__112basic_stringIcNS3_11char_traitsIcEENS3_9allocatorIcEEEE$a.19$d.9$a.18$a.8$a.17$d.7$a.16$a.6GCC_except_table15$d.15$d.5$d.24$a.14$a.4$a.23$d.13$d.3$d.22$a.12$a.2__aeabi_unwind_cpp_pr1$a.21$d.11$d.1.rodata.str1.1__gxx_personality_v0__aeabi_unwind_cpp_pr0$d.20GCC_except_table10$a.10$a.0P u8q @ p0 pX @t 0X @L0%\0=t} T0 Vp R d0 %p09n t 0d, p8 0%08@L (0( p4 0%0D< 0pT 0%0EX\L  80NJ D0!p L0#%0G$ \0&p& l0( 2 Lo0lp@<Lo|0  )/783 1749669029 1000 1000 100644 1432 ` ELF(4( @Q/ @ R/0!0\\@`p8P\\X//Q///Q/Q/Q/ clang version 18.1.8A?aeabi5C2.09 A   "$&) S <lb   * *.rel.ARM.exidx.rel.text.comment.linker-options.ARM.attributes.note.GNU-stack.Lswitch.table._ZN6tflite3gpu2cl14ToChannelOrderEi.llvm_addrsigcl_image_format.cc.strtab.symtab_ZN6tflite3gpu2cl21DataTypeToChannelTypeENS0_8DataTypeEb.rodata.cst16$a.4$d.3$a.2$d.1__aeabi_unwind_cpp_pr0$a.0`.4 @8 p @@ #Lo 0 C63p6@Lo` x cl_kernel.cc.o/ 1749669030 1000 1000 100644 12124 ` ELF('4(1       0   0 /H-@P+ PP 1/1/` p       L-@P (1/1/$L-@P D1/81/  @4pI-M@P1/ ` Kl0 3/P QKp   D H 0PP<0800   PKHK8 0 [0   [ Kp Kp [   hO-M p`PP    @0  @ 0< 3/<P> Q<|1/p!X0p@4/P\ 0@p. 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L0 <0. ,0 0 0 0 0 0$ 0" 0$ $@0$ C09 0. 0 0/ 0 0 p0 `0 P0 @0% 00# 0% %@ 0% 0 0& 0( < M<09 ,0 0/ 0 0 0 0 0 0% 0# 0% 0% |0% l0' \0) L= 00 p0 `0 (K P$(P,U pD ($, pP~ Pu㨠@th* T *$#eF(`ZLieBD`#LeFH@ieBD`  8D  `X  0  P @  KHK  0  K8[004 80K 08[ H[ P D 0H[ @P XD~ L{(PU $@T@DT TT T ($P D0LpH E 00 `@P000p< D L0< E`DPF L@ 8 PD 0 PP` A@Qc|Pv{F AcP Q EQ P P@p PІ X-*\ P @pP   b @ $ B(  \0(0 D (0KB ([K K\@pHGaVD*IV`1pa#V V<*G 0!X GQ:HP* 2 R\T  ``PpH!,`C!H0C gQ C,QD([7 4/.*D&P H[ @P XD 8[ H[PD L0H[ (K0 8P 0  p ` P @ 0  h X H 8 (   8 (   xhXD | l \ L < ,   |l\,K-M @P` a@A     0  P Kp P  T X`0 p0PK  O-DM@ p$ `( P(K 0($X @PPTX' zꫪ ᪪J 40,VUA p`Ps*`@Ap D` ,p4 a 0p  ($,@      ($ A 0 0 00   P:$ @00P,  0P , PTX pW $p,P 0(P $ K, pW,P(P$p,P ,P ,P 0(P (P $ F< LxCCFS8  L0Ehh F40xHhH- 0H-P@  A 8 ,H- H-    pL-P@U `V`FV VV V PpCDŽH- H- N6tflite3gpu16GpuSpatialTensorEExpected CLSpatialTensor.No dispatch parameters to launch kernelbasic_string#define GLOBAL_ID_0 get_global_id(0) #define GLOBAL_ID_1 get_global_id(1) #define GLOBAL_ID_2 get_global_id(2) #define LOCAL_ID_0 get_local_id(0) #define LOCAL_ID_1 get_local_id(1) #define LOCAL_ID_2 get_local_id(2) #define GROUP_ID_0 get_group_id(0) #define GROUP_ID_1 get_group_id(1) #define GROUP_ID_2 get_group_id(2) #define GROUP_SIZE_0 get_local_size(0) #define GROUP_SIZE_1 get_local_size(1) #define GROUP_SIZE_2 get_local_size(2) #define SUB_GROUP_LOCAL_ID get_sub_group_local_id() #define SUB_GROUP_BROADCAST(V, ID) sub_group_broadcast(V, ID) #define SIMD_LOCAL_MEM_BARRIER barrier(CLK_LOCAL_MEM_FENCE) #define LOCAL_MEM_BARRIER barrier(CLK_LOCAL_MEM_FENCE) #define MAIN_FUNCTION __kernel void main_function #define INIT_FLOAT(value) (float)(value) #define INIT_FLOAT2(value) (float2)(value) #define INIT_FLOAT2v2(v0, v1) (float2)(v0, v1) #define INIT_FLOAT3(value) (float3)(value) #define INIT_FLOAT3v3(v0, v1, v2) (float3)(v0, v1, v2) #define INIT_FLOAT4(value) (float4)(value) #define INIT_FLOAT4v4(v0, v1, v2, v3) (float4)(v0, v1, v2, v3) #define INIT_INT(value) (int)(value) #define INIT_INT2v2(v0, v1) (int2)(v0, v1) #define INIT_INT4v4(v0, v1, v2, v3) (int4)(v0, v1, v2, v3) #define CONVERT_TO_INT4(value) convert_int4(value) #pragma OPENCL EXTENSION cl_khr_3d_image_writes : enable #define ACCUM_FLT4 float4 #define INIT_ACCUM_FLT4(value) (float4)(value) #define FLT float #define FLT2 float2 #define FLT3 float3 #define FLT4 float4 #define TO_FLT4 convert_float4 #define TO_ACCUM_TYPE convert_float4 #define TO_ACCUM_FLT convert_float #define TO_ACCUM_FLT2 convert_float2 #define TO_ACCUM_FLT3 convert_float3 #define TO_ACCUM_FLT4 convert_float4 #define INIT_FLT(value) (float)(value) #define INIT_FLT4(value) (float4)(value) #define INIT_FLT4v4(v0, v1, v2, v3) (float4)(v0, v1, v2, v3) #pragma OPENCL EXTENSION cl_khr_fp16 : enable #define ACCUM_FLT4 half4 #define INIT_ACCUM_FLT4(value) (half4)(value) #define FLT half #define FLT2 half2 #define FLT3 half3 #define FLT4 half4 #define TO_FLT4 convert_half4 #define TO_ACCUM_TYPE convert_half4 #define TO_ACCUM_FLT convert_half #define TO_ACCUM_FLT2 convert_half2 #define TO_ACCUM_FLT3 convert_half3 #define TO_ACCUM_FLT4 convert_half4 #define INIT_FLT(value) (half)(value) #define INIT_FLT4(value) (half4)(value) #define INIT_FLT4v4(v0, v1, v2, v3) (half4)(v0, v1, v2, v3) #define bool2 uchar2 #define bool3 uchar3 #define bool4 uchar4 clvkvectormain_functionclang version 18.1.8A?aeabi5C2.09 A   "$&  !"#%&'(*+,-/12q 3cO&3u&3&3O$3$3 $3-$3vQ$3u$3(3S(3(353?F?3=38333l-*3W,303I,383,35C@3&3~,3<3b43E:3/3j3/3N33&3+:3N3gm%3#3%3`%3%33?033{3+33t 3<&3Xb$3&3&35&3(3q *3!J>3D$ '3K )3t =3! 3 3] 3 3V 34q lL X(3   B 3D  ](!%I%%: 3***; d  !1" P # <P ji F" d"%0""To L@  P)"*( L"f $"1 > q !/^ \mxnmnop`q`r`q`ru4ndxnzzzzz0zDzXzlzzzzzzzz z z4zHz\zpzzzzzzzz(z<zPzdzxzzzzzzzz(z<zPzdzxzzzzzzzzz0zDzXz|zzzzzzzzz0zDzXzlzzzzzzz{ | } zP z z z ~ ~$ ~8 ~ ~ ~ ~ z ~P ~t   H |  ~$|~ h~|~~~~      $(,048<@DHLPTX\`d h!l"p#t$x%|&'()*+,-./012%3456789:;<=>?@A%&34)*+ ,-:;< =$>(B,C0D4E8F<G@HDIHJt|~(pD\~Jp0||xp ~ 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v74 @8.`:p0 @5p: @ @6:M|#:  6: %p0 ! 06: M#:" 8L @68:  x6: p 6:M#: $ 6:Z pV 6:M#:0 6(:VpR 6:M#: R 6: p 7:"M#:^Z 7:%p% (7:'M$:{w 87:* p* H7:,M$:i  M$ :r  X7:12 2#Lo&#0&#<#p<#@[ Loh7: ($ lcl_program.cc.o/1749669031 1000 1000 100644 14816 ` ELF((34(+O-lM`@P@V@@!  t8p`V   ⴁ Qyp AcPr c,v+FQi GQh8? @ a'a A'A<8@ a@A<8 q pQ_@ AcPX c,v+FQO DQN8 @a@ A <8_ZPI @ a+ A'A<!8LP@pu drpP PPN 0 @ a'a A'A<8(P@pU q@pP PP0  8@ reF@ <8 @< @0  0H D0pD 8 @   a*a   a*a<!@ @8 *@8 pp 8@ppK8 @  `$ 440 / /P/0H-@Q D P 2/    0H/8L-@P 1/L-P @ 1/O-M 0@ pe@7/P( $P$ P L $(0,  40 (PKPK0 ([ 0$   ([ $ P K@ $ ,P@` p ER#*@Q%*x ` @`X`1pa# U Y D P#* 'Hrp3 rp*rp`0 EPE@`@p epW FPqPp`qNp`0r0@RPU   0p@Af @7/P) ,$@ P L $(0,  40 (PKPK0 ([ 0$   ([ $Y ,K@K$ ([$  $ $ ,< K-xM@` p  K K07/P) Q' @D @`8`K@ 8[004  8[S 0P Q&  P @D 0   8PK@ 8[004  8[ 0 ) &"@p `W P 1/@D@D@@0 @ HK@@ H8[ 0  8[0(F  , AAA (@F)E#FFH<$ E8`d8P`t(4@d\ hH- H- 0H-P@  A 8 ,H- H-  Failed to get program binary - Failed to create compute program - Something wrong with binary after clCreateProgramWithBinary - Failed to create program - clvkFailed to get program binary size - vectorFailed to build program executable - Failed to GetProgramBuildInfo - basic_string-qcom-accelerate-16-bit-qcom-accelerate-16-bit=trueunsupported-qcom-accelerate-16-bit=false-cl-fast-relaxed-math-fregister-allocation=64-cl-opt-disable-cl-std=CL2.0-cl-std=CL3.0clang version 18.1.8A?aeabi5C2.09 A   "$&  !"]  | f # $ $ 8 $_ H$M h$ $ $M $) $ B P    h ` L W d d  %#  # dW 6 3 t  "$#m   T &#O !#=  h ] F?#9 #: (Y 4  # k Dq G #   *  # P'^3@,5  P @`tp 8H "  d  "K ]P Hb Y"(hL"G$"`c`ABB\BABXBCDEB(BDC`DpEBFG BDBHGGH $( , 04 8< @ DHL`N`N\R``NVW X\GpGBYPY Gh V W X G G Z0 H8 G\ G` Hd `[h l `[p `[t `[x `[| `[  ]X ^l " V W X G( G8 ^< HP Gd Hl Gp Ht `_x $| `N Vx V W G `X\GpGGBY\VWGGaGG4GLGPHT`bX(\`c`)d)eW8XxVWXG]d^"G^HGHGGHHG H`f-.`N*I@*I\*I*I*I*I**K*K*O** O *$*(*,*0*4*8*<*@*D*H*L*S TK*g3K*0hi4j<k@HD`lH`m*I*4*7n 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G@P0`@`@``0C P@@ F PPPP`W pGW W pW  KW FH- H-@P P`V pW`pGW WW W `CpL-M` @V00 P  `V@@      !Kp   C <pL-@ P p`P`FV V V CDŽO-M@P @@p@`` `` : :J @ F@ $ @B@@004 , pR w   @048@4@K P 44F!@ ,PO-4M0 @S 0  DL  @P 000p0Y @T Q`0PA *P  P GQXHx Z * 0` @ FPp<  J <@B, ,LPsAAf&f&@P1Q!PgpP `@@  0aa0 `Z JAZ 0 c0 B0 V    L0J@Q&  p$0P`@S00V``3`V0B ` c( BAP F*b f*C BPP``0P pRP0 pLK P F\ (H- _linkin_valueout_value ; Can not apply ResolveSecondElementwiseInput for non 2 input elementwise, B_COORD::type second_value = args..Read(); in2_valuesecond_valueREAD_SECOND_VALUE0X_COORDY_COORDS_COORD, B_COORDargs.src_tensor_1::type in2_value = args.src_tensor_1.Read( in2_value.y = in2_value.x; in2_value.z = in2_value.x; in2_value.w = in2_value.x; $0{}src_tensor_1src_tensor_LINK_VALUEvectorbasic_stringMAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.dst_tensor.SetBatchRef(B); args.src_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int Y = GLOBAL_ID_1; int Z = GLOBAL_ID_2; if (X >= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) return; args.src_tensor::type src = args.src_tensor.Read(X, Y, Z); args.dst_tensor.Write(src, X, Y, Z); } args.Expected ( after . callWrite_; }_final output: } Z_COORDNo implementation of perform const expressionNo implementation of perform selectorinterm_valueX_COORD, Y_COORD, S_COORDsrc_tensordst_tensor$0{READ_SECOND_VALUE{ // elementwise code with input:N6tflite3gpu12GPUOperationEN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$&  !"#$&'()*+-./012456789;<=>?ABCDEGHIJKLNOPQRSUVWXY[\]^_`bcdefhijklnopqrsuvwxyz|}~     !"$%&')*+,-/012356789:<=>?@BCDEFHIJKLNOPQSTUVWXZ[\]_`abcefghijlmnoprstuvwyz{|}=$ 0Q   =:L`oHPh "-  4 1Cfx' &$&(5 (6!h rO,   HZpY!f(.f2hO}p)H~d~-t0 @ ,ӝ pO>K(nb 0!0{Q#t#X--//.2؟ߡ2٠BBDdj D/JTJ`LyLNN,Oߛҟ0OОQ(h#^ ZT٢աdϠ֞ LQlRp<HXU=hU6d<%#JAV_P ȟ l4l4(466;;T;=AA\ACݝdrƞ ,GGI IN NP PUUUWxrt`t~[n[]z ]bbdhhjhtĜv0nnp puuwʜ w2vhx`|d|~ ~^xn0}@}}8ƛ"t XTN^oD̛  ʚ(RNHXizĚ3 LК5BRct     $$$))+/-/15*57; 7<<<>B_BDHHJNNNSSU UZZ_ߠ_aeeg gllnr%rt" tyHy{m?yҢΡȠ04Cu.Or3&,%[ t}d̝ݜy5 X  |t yk")`""d".:>ys n(h" "B~l"ЇL"L")L";Ho";rX@ql"2h"qwq" p< W"#9 "=`p.<g3AXhtpp1"/0").<.:4r0"4}K"5Ix"Bj"u L("&7<"v!YH"S^Nw"sl"v#y$d uj@"-&.l"6>h"Z"Nm-0"Q `"H.-.7.zeT"e"l~bsLQQ@ÖSf7"!U e0Uw W$DW z<+p3"ax"d"A\";juTt$!T " "$nd F" S"G}{"N!d"UxP"a"y&`"_LnrU_$"[Xf"$"h P"bT"q.mht\$"nZ$"umva$"|'mx "?x "<*"<x"=L"C.g>$"\.- P=- p< """0A" T"D"m,d" P"< 6"r:""-"N4" 8"w "d "x "*" "3M""+#h"*w"~y^yxt!t#!=rX@Dpp| @`D`( (<Ddhp`,L  @ P     T p  d   LPt0`x8TL(<Pp`X ` (08@X$8H` !"(,<l< ( 8 L ` t    !0!T!x!!!!*!+!,!-!.!/!0!1!2 " "4"@"\""""""##0#<#X######$$,$8$P$$$$$$$P%d%%%%%(&<&d&p&&&&&''0'H'l''''''''\((<)t))*D*|**8*9+@+,,D,h,-:-;(-:,-8-:<---:--:---:----=->-?-@-A-B-C-D.E.F.G .H.I.J.Kx.../00h0000,111@2222222S2S2SD3\3H444X55D6l66666t7777@89H8:888L:::;H;\;;<0= >$>T>>>?0?`???? @@@@@0AABBSB CXCpCCCDdDDDDDYDZD[DSE@EEEF8FFFF*@\p(l|/$4x*B*DD **E*Gdx*I*K<l**L*N4*P*R0$01*S*U$0`*X*[$04`*\*_5c*`5g*d*h*j*lP:**nxP@$*p *rl;*t*vD|*y*{<<**|*~L`**H-(,@H\`d`h`=***`p>t|>****? 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H0`V`,p1***"`qqV``j:j6f`0S)8n `^ H0Y !4qT****"0qS0U0[:::V60PUY"(> 1P8^0@<嶠1PD^4<@@ P8@^@04`}p(HQ4***" qR  *:*f& `V !.4^ HQ***" qR  *:*f& `V !.H $R0e***" qR k*:*f& `Vi!.0^ H RE***" qR K*:*F& @TI!.`,@p@$( uFpL-@0P 4 PU $Q `V v  $P pCDŽOpenCL 2.0 QUALCOMM build: commit #7ff4f54 changeid #I4460aa6217 Date: 12/30/18padding_xpadding_ydilation_xdilation_ysrc_tensordst_tensor int y_c = start_y + * args.dilation_y; int x_c = start_x + * args.dilation_x; bool inside_x = x_c >= 0 && x_c < args.src_tensor.Width(); x_c = clamp(x_c, 0, args.src_tensor.Width() - 1); src = args.src_tensor.Read(x_c, y_c, src *= INIT_FLT( FLT4 res = TO_FLT4(r args.dst_tensor.Write(res, X, Y, , args.weights.Read( * args.weights.Read( += TO_ACCUM_FLTweightsbiasesbasic_string.xyMAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int Y = GLOBAL_ID_1; if (X >= args.dst_tensor.Width() || Y >= args.dst_tensor.Height()) return; int start_x = X * args.stride_x + args.padding_x; int start_y = Y * args.stride_y + args.padding_y; ACCUM_FLT4 r = INIT_ACCUM_FLT4(0.0f); FLT(start_y + * args.dilation_y) { bool inside_y = y_c >= 0 && y_c < args.src_tensor.Height(); y_c = clamp(y_c, 0, args.src_tensor.Height() - 1); { ); rsrc } } ) + args.biases.Read(} No implementation of perform const expressionNo implementation of perform selectorvector + N6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%&()*+-./02345679:;<=?@ABCEFGHJKLMOPQSTUWXY[\]^`abcefghijlmnoprstuwxyz{}~ B>_= P< yH< ?<P ;` 5;p : < ; >;  M< : /:<9 +> ;9H9L:- :M05>TR=s9}08#>#;=< <#N;q5;5r::< 2< $=; (;!<  :!": "<}9$"8#: >#E=<$<@$%<%b:;%;\(9.AV9o8|:d( :*=f9*84+=8+.=l,=<t,</}< B{;/:81;h9l:<191`9183:'=3=x<F9<|<;A=k;A:H:0\:H9IP9I8U9H=U=bw<b;de;d:`o&9`V:ho9 }q;)@9}8}[;=}=}:q<};D~8U;H~:|L:&F:9`;909p8;==Tk<;\O;:9 !@:!9D!#9 #( 9(8 (-=-<(-2e<2;(24>49I;9:09;?::?94?AE9E8E69.J=J<J8&O_<OS;SWC;W[:[`4:`e9eg= gl9lnr8rsw;>wy}X=}<}=88<;.;:(:98$>K=8<<+<;;`:d:ll98@=H4=<H<P;;??r  / #U*="!" u 57B0x"wr"o 0"-<d"  \"L$!s=  4"1"4 "L3p""}"~\0"2p_  x ~ h"I"<%l"-L"*L" (L"sL"!4 s$"(M  ]\  u "[j4"938"?P7 "E-6 "J- "Oz"S "W"`*"e"r( o d"l%!#!(<P($h  Th H` Hl  $ ( 0 4 < @ l                        ` ` @            4 H \ p     P     \Lx$l X  T d   Pl | DXl <@D\  0LP  !"#$%&'( Hd t <Pd <  P `   +T!p! !!. 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(DST_X + (DST_Y + (DST_Z + DST_S * 4 * int filters_offset = int addr = args.src_tensor.GetAddress( = select(-1, addr = select(0, args.src_tensor.SliceStride(), ( int s = weights_cachefilters_locargs.weightsfilters_offsetargs.weights.Read(filters_offset + filter_offset } while (s < args.biases.GetPtr()args.biases if (DST_S + FLT4 bias_val = TO_FLT4(weights_cache[ FLT4 bias_val = args.biases.Read(DST_S + , DST_Y + , DST_Z + , DST_S + FLT4 res = TO_FLT4(r) + bias_val; args.dst_tensor.Write(res, int linear_id_1 = int DST_Y = async_work_group_copy( src = args.src_tensor.Read< ? args.src_tensor.Read<) : INIT_FLT4(0.0f); ) * INIT_FLT(SUB_GROUP_BROADCAST(simd_wweights_cache[ = fma( += TO_ACCUM_TYPE(.x += dot(.y += dot(.z += dot(.w += dot(Width()Depth() < args.dst_tensor.SIMD_LOCAL_MEM_BARRIERLOCAL_MEM_BARRIER__constant__global#pragma OPENCL EXTENSION cl_khr_subgroups : enable #pragma OPENCL EXTENSION cl_intel_subgroups : enable __attribute__((reqd_work_group_size(, ))) __attribute__((intel_reqd_sub_group_size(DST_S >= args.dst_tensor.Slices()DST_Z >= args.dst_tensor.Depth() || DST_S >= args.dst_tensor.Slices()DST_X >= args.dst_tensor.Width() || DST_Z >= args.dst_tensor.Depth() || DST_S >= args.dst_tensor.Slices()DST_Y >= args.dst_tensor.Height() || DST_S >= args.dst_tensor.Slices()DST_X >= args.dst_tensor.Width() || DST_Y >= args.dst_tensor.Height() || DST_S >= args.dst_tensor.Slices()MAIN_FUNCTION($0) { args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); DST_S = 0; if (DST_S >= args.dst_tensor.Slices()) return; if () { return; } int conv_group_id = DST_S / args.dst_group_size; int src_start_slice = conv_group_id * args.src_group_size; int src_end_slice = src_start_slice + args.src_group_size; src_start_slice0src_end_sliceargs.src_tensor.Slices()args.src_group_size int lid = LOCAL_ID_0; int lid = LOCAL_ID_1 * + LOCAL_ID_0; int simd_id = SUB_GROUP_LOCAL_ID; ) = * args.stride_x + args.padding_x; = DST_X + ; = clamp(xc, 0, args.src_tensor.Width() - 1); * args.stride_y + args.padding_y; = DST_Y + = clamp(yc, 0, args.src_tensor.Height() - 1); * args.stride_z + args.padding_z; = DST_Z + = clamp(zc, 0, args.src_tensor.Depth() - 1); * __local weights_cache[]; weights_cache; int filter_offset = 0; (DST_S * args.src_tensor.Height() + DST_Y * ) * 4 * args.src_tensor.Slices() * args.kernel_size_x * args.kernel_size_y * args.kernel_size_z filters_loc = args.weights.GetPtr() + for (int kz = 0; kz < args.kernel_size_z; ++kz) { zck int zck = kz * args.dilation_z + zc bool in_z >= 0 && < args.src_tensor.Depth(); = clamp( for (int ky = 0; ky < args.kernel_size_y; ++ky) { yck int = ky * args.dilation_y + yc bool in_y < args.src_tensor.Height(); for (int kx = 0; kx < args.kernel_size_x; ++kx) { xck int xck = kx * args.dilation_x + xc bool in_x < args.src_tensor.Width(); ); addr, ( int ds = args.src_tensor.SliceStride(); do { SIMDGROUP_BARRIER(mem_flags::mem_none); lidfilters_loc[simd_id + FLT4 simd_w if (simd_id < simd_w } weights_cache = filters_loc; s - src_start_sliceDST_Y * args.src_tensor.Slices() + s FLT4 f$2 = args.weights0.Read(DST_S + $0, $1); FLT4 f$3 = args.weights1.Read(DST_S + $0, $1); FLT4 f$4 = args.weights2.Read(DST_S + $0, $1); FLT4 f$5 = args.weights3.Read(DST_S + $0, $1); filter_offset++; s += 1; filters_loc += filters_offset += }; DST_S weights_cache = args.biases.GetPtr() + DST_S; >= args.dst_tensor.Slices()) return; { ]); DST_X + } basic_stringNo implementation of perform const expressionNo implementation of perform selectorvectorclvk int linear_all = GLOBAL_ID_0; int B = linear_all % args.task_size_b; linear_all = linear_all / args.task_size_b; int DST_X = linear_all % args.task_size_x; linear_all = linear_all / args.task_size_x; int DST_Y = linear_all % args.task_size_y; linear_all = linear_all / args.task_size_y; int DST_Z = linear_all % args.task_size_z; linear_all = linear_all / args.task_size_z; int DST_S = linear_all; int linear_spatial = GLOBAL_ID_0; int linear_spatial = GROUP_ID_ * GROUP_SIZE_0 + LOCAL_ID_0; int B = linear_spatial % args.task_size_b; linear_spatial = linear_spatial / args.task_size_b; int DST_X = linear_spatial % args.task_size_x; linear_spatial = linear_spatial / args.task_size_x; int DST_Y = linear_spatial % args.task_size_y; linear_spatial = linear_spatial / args.task_size_y; int DST_Z = linear_spatial; int DST_S = GLOBAL_ID_1; int DST_S = GROUP_ID_ * GROUP_SIZE_1 + LOCAL_ID_1; int DST_X = GLOBAL_ID_0; int DST_X = GROUP_ID_ int B = DST_X % args.task_size_b; DST_X = DST_X / args.task_size_b; GLOBAL_ID_1GROUP_ID_ * GROUP_SIZE_1 + LOCAL_ID_1 int DST_Y = linear_id_1 % args.task_size_y; int DST_Z = linear_id_1 / args.task_size_y; int DST_S = GLOBAL_ID_2; * GROUP_SIZE_2 + LOCAL_ID_2; DST_X *= DST_Y *= DST_Z *= DST_S *= _s && + , 0); [.Read(] = < , srsrc.x += * .y += .z += .w += .x * .y * .z * .w * DST_Y + DST_Z + biasesN6tflite3gpu11ConvGenericEN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%'()*+,./01345679:;<=?@ABCEFGHIKLMNOPRSTUVWYZ[\]^`abcefghjklmnoqrstvwxy{|}~    !"#$&'()*,-./12346789;<=>@ABCDEGHIJKMNOPRSTUVXYZ[\^_`acdefhijkmnopqryz|~b*vuu@$ 0  ʐϐHJ@OhDTIXhx ʗ| JP ڂےT L u'0 u@ur Tމr&xl-^ up-.u@ u uhu uh uu uH uAX uh ux uv~vR.04) vH4 v44=4v&u0uq6v%v46ڙv6F7<vH u7a09W*v899"v Fv`fjvGGvkvhv !vj9=0Q4;5 *vk /v% .vCS /vȆD;r; .vƎ /v< v .v= /v| !v| v;d=v\W %vp=5>ޗ .v^ 7v!2vS7v2v7vvv/ v v>x@  v3@TA v\A0 vjjxDjl lqq qvvh(v{{~R50t$4LJNK .vny &vЗPxx,e X6 ͋  v v6U Մ(L!!&g&(,!,,11j1666;;@@Ba BGGIM;MMRRTX9XZ^^^c6chihhmVmmooȁ$.RR}h#R*$x(@d"ERs~$)+" )z "eAK@`}DcRJX$Jy| wT Jp nJQX N)NFJqbx"[OG<"& "K0">5"(*Lx(]LG0"vN"1 "l\"NwM$!y7OCT" 6s;#"";rLK(TE(GP"3,I0"9tPYQi%D\"?r*# "h"XyT"@l"GD"!O+,,("'3$;*"{~.xetD0TuI".k"6h"eX0f.ft(M@DLD|||D gL{8 ,"^D{T` |DlQy7':-B$;r'(+zlQ$l "mq"K>Wl"_L" ]L"9ZL"QKh~l>`@\BOu " zR)"c Dn"REx ly| (p"YwRDhw )J} "`,L"j,$"qA +}y (Y (04" 8"Qs ".r? 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T BP:  DR*0 3"SU  KO U K `!G1DpG@D dP G\FH- H- O-M0X * ppKPJ JJHIUUA`Vc C: :@B!V`1R`!V VX@J JJp0X! p IR* *X2ptqpaI @PH0 @2P1:㢑0pC0`HN!00Ff0Sf0`GGGp`pY  p 2  RX pK FH- src_tensordst_tensorweights simdgroup_matrix simdgroup_matrix simdgroup_load(, f_offseted_x1 + , tmp_w_x1 + simdgroup_load(mat_src, tmp_src_x1 + , 8); // loading sp[] src_ch[, mat_src, simdgroup_store(dst_sp0_8_ simdgroup_store(dst_sp8_16_ simdgroup_store(dst_sp16_24_ simdgroup_store(dst_sp24_32_ args.dst_tensor.Write( int linear_id_1 = int DST_Y = biasesvector#define MMA simdgroup_multiply_accumulate #define SPATIAL_THREADS MAIN_FUNCTION($0) { args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); DST_S *= ; device FLT4* f_offseted = args.weights.GetPtr() + DST_S * 4 * args.src_tensor.Slices(); int spatial_id = LOCAL_ID_0; int slice_id = LOCAL_ID_1; int spatial_id = LOCAL_ID_1 * GROUP_SIZE_0 + LOCAL_ID_0; int slice_id = LOCAL_ID_2; int tid = slice_id * SPATIAL_THREADS + spatial_id; threadgroup FLT4 tmp_w[]; threadgroup FLT* tmp_w_x1 = (threadgroup FLT*)tmp_w; tmp_w_x1 += * slice_id; threadgroup FLT4* tmp_w_x4 = (threadgroup FLT4*)tmp_w_x1; device FLT* f_offseted_x1 = (device FLT*)f_offseted; threadgroup FLT4 tmp_src[SPATIAL_THREADS * threadgroup FLT* tmp_src_x1 = (threadgroup FLT*)tmp_src; // sp - spatial dimensions, ch - channels dimension // indexing relative to simdgroup dst_sp__ch int spatial_group = spatial_id / 32; tmp_src_x1 += 8 * 8 * 4 * spatial_group; int c_x = min(DST_X, args.src_tensor.Width() - 1); int c_y = min(DST_Y, args.src_tensor.Height() - 1); int src_address = args.src_tensor.GetAddress(c_x, c_y, slice_id); int tid2 = 0; if (tid < SPATIAL_THREADS) { tid2 = tid * 2 + 0; } else if (tid < SPATIAL_THREADS * 2) { tid2 = (tid - SPATIAL_THREADS) * 2 + 1; } else if (tid < SPATIAL_THREADS * ) { tid2 = (tid - SPATIAL_THREADS * ) * 2 + 0 + SPATIAL_THREADS * } else if (tid < SPATIAL_THREADS * ) * 2 + 1 + SPATIAL_THREADS * } for (int s = 0; s < args.src_tensor.Slices(); s += io threadgroup_barrier(mem_flags::mem_threadgroup); tmp_w_x4[spatial_id + ] = f_offseted[spatial_id + if (spatial_id < tmp_w_x4[spatial_id + } , 8); tmp_src[tid2] = args.src_tensor.Read(src_address); tmp_src[tid2] = args.src_tensor.Read(c_x, c_y, s + slice_id); f_offseted += 16 * f_offseted_x1 += 64 * src_address += args.src_tensor.SliceStride() * simdgroup_matrix mat_src; w_o); } FLT4 r = INIT_FLT4(0.0); // transferring from simdgroup memory to private registers. const int kSpatialGroupsCount = for (int i = 0; i < kSpatialGroupsCount; ++i) { int spatial_id = tid - i * SPATIAL_THREADS; bool current_spatial_group = spatial_id >= 0 && spatial_id < SPATIAL_THREADS; ch if (current_spatial_group) { , tmp_src_x1, 8); , tmp_src_x1 + 64, 8); , tmp_src_x1 + 64 * 2, 8); , tmp_src_x1 + 64 * 3, 8); r += tmp_src[spatial_id * 2 + 0]; += tmp_src[spatial_id * 2 + 1]; if (DST_X >= args.dst_tensor.Width() || DST_Y >= args.dst_tensor.Height()) { return; DST_S + r if ( < args.dst_tensor.Slices()) { += args.biases.Read(, DST_X, DST_Y, } basic_string int linear_spatial = GLOBAL_ID_0; int linear_spatial = GROUP_ID_ * GROUP_SIZE_0 + LOCAL_ID_0; int B = linear_spatial % args.dst_tensor.Batch(); linear_spatial = linear_spatial / args.dst_tensor.Batch(); int DST_X = linear_spatial % args.dst_tensor.Width(); linear_spatial = linear_spatial / args.dst_tensor.Width(); int DST_Y = linear_spatial % args.dst_tensor.Height(); int DST_Z = linear_spatial / args.dst_tensor.Height(); int DST_Y = linear_spatial / args.dst_tensor.Width(); int DST_S = GLOBAL_ID_1; int DST_S = GROUP_ID_ * GROUP_SIZE_1 + LOCAL_ID_1; int DST_X = GLOBAL_ID_0; int DST_X = GROUP_ID_ int B = DST_X % args.dst_tensor.Batch(); DST_X = DST_X / args.dst_tensor.Batch(); GLOBAL_ID_1GROUP_ID_ * GROUP_SIZE_1 + LOCAL_ID_1 int DST_Z = linear_id_1 / dst_tensor.Height(); int DST_Y = linear_id_1 % dst_tensor.Height(); int DST_S = GLOBAL_ID_2; * GROUP_SIZE_2 + LOCAL_ID_2; No implementation of perform const expressionNo implementation of 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V @P  `*` A*A88 <@0D @ W `D`P @K P DP@`D1/ UPKV DPJ1/D`VT DPG1/D@TpFO-MP`P  0p pQpQpP  R P 0Pp0 pPPl0p0P pPP VpM @ Q pW P$ P pPPpP ppP `P`P@Q V@ P pPPWW P pPp VK P` Q QQ` F K-`PP % p pP `@ @T  1PCX  3P R P APPEL-@Q P PApL-`PP  '   P  @0  P 0   p@0@  p  P!pCDŽM-P@ R `U   PUp `aE߄K-@P R pUP  pE`0FpS:B:qU` P `3pU   EK-M  `PP% p pP `@ @T  1PCX  3P RPAPPPKEM-@`Pp @R*V `w*ڀWp1pq#PU```   @R *pP `PU PU  E߄K-M C00O@ @@TLpp` FB!11@T@1R@!T T>`"2!   `PDW @D@DAD@DP P``W  D@GPD1/T@pW  KT 1/D@EL-@`W D7p1/pWP ЌC̈́padding_xpadding_ykernel_size_xkernel_size_ypadding_zkernel_size_zgrid_size_ysrc_tensordst_tensorweightsR += S.x * R += S.y * R += S.z * R += S.w * R += TO_ACCUM_TYPE(S.x * R.x += dot(S, R.y += dot(S, R.z += dot(S, R.w += dot(S, ACCUM_FLT4 r = INIT_ACCUM_FLT4(0.0f); int sz bool in_z int sy bool in_y int sx bool in_x int addr = args.src_tensor.GetAddress( addr = select(-1, addr int ds = select(0, args.src_tensor.SliceStride(), ( FLT4 src = args.src_tensor.Read( ? args.src_tensor.Read() : INIT_FLT4(0.0f); ) * INIT_FLT( addr CONVxc < args.dst_tensor.Width() && yc < args.dst_tensor.Height() int xc = dst_x + args.stride_x * int yc = dst_y + args.stride_y * int zc = dst_z + args.stride_z * && zc < args.dst_tensor.Depth() if ( FLT4 res = TO_FLT4(r) + bias_val; args.dst_tensor.Write(res, , dst_s); weights_cache[]f#define CONV(R, S) \ , S.x, R); \ , S.y, R); \ , S.z, R); \ , S.w, R); ; \ ; (R, S) \ + S.y * + S.z * + S.w * ); ); \ ); MAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int dst_x = (linear_id / args.dst_tensor.Batch()); int B = linear_id % args.dst_tensor.Batch(); args.dst_tensor.SetBatchRef(B); args.src_tensor.SetBatchRef(B); int dst_x = GLOBAL_ID_0; int rem_x = dst_x % args.stride_x; int ceil_x = dst_x / args.stride_x; dst_x = ceil_x * args.stride_x * + rem_x; int linear_id_y = GLOBAL_ID_1; int dst_y = linear_id_y % args.grid_size_y; int dst_z = linear_id_y / args.grid_size_y; int rem_z = dst_z % args.stride_z; int ceil_z = dst_z / args.stride_z; dst_z = ceil_z * args.stride_z * + rem_z; if (dst_z >= args.dst_tensor.Depth()) return; int dst_y = GLOBAL_ID_1; int rem_y = dst_y % args.stride_y; int ceil_y = dst_y / args.stride_y; dst_y = ceil_y * args.stride_y * + rem_y; int dst_s = GLOBAL_ID_2 * ; if (dst_x >= args.dst_tensor.Width() || dst_y >= args.dst_tensor.Height() || dst_s >= args.dst_tensor.Slices()) return; int f_base = dst_s * args.src_tensor.Slices() * args.kernel_size_x * args.kernel_size_y * args.kernel_size_z * 4; int kernel_first_dst_x = dst_x + args.padding_x; int kernel_first_dst_y = dst_y + args.padding_y; int kernel_last_dst_x = kernel_first_dst_x - args.kernel_size_x; int kernel_last_dst_y = kernel_first_dst_y - args.kernel_size_y; int offset_x = abs(args.padding_x); int offset_x_strided = offset_x * args.stride_x; int src_x = (kernel_first_dst_x + offset_x_strided) / args.stride_x - offset_x; int offset_y = abs(args.padding_y); int offset_y_strided = offset_y * args.stride_y; int src_y = (kernel_first_dst_y + offset_y_strided) / args.stride_y - offset_y; int kernel_first_dst_z = dst_z + args.padding_z; int kernel_last_dst_z = kernel_first_dst_z - args.kernel_size_z; int offset_z = abs(args.padding_z); int offset_z_strided = offset_z * args.stride_z; int src_z = (kernel_first_dst_z + offset_z_strided) / args.stride_z - offset_z; int src_as_dst_z = src_z * args.stride_z; for (;src_as_dst_z > kernel_last_dst_z; src_z -= 1, src_as_dst_z -= args.stride_z) { = src_z + = sz >= 0 && sz < args.src_tensor.Depth(); sz = clamp(sz, 0, args.src_tensor.Depth() - 1); if (!in_z0) continue; int kernel_z = kernel_first_dst_z - src_as_dst_z; int src_as_dst_y = src_y * args.stride_y; int src_y_copy = src_y; for (;src_as_dst_y > kernel_last_dst_y; src_y_copy -= 1, src_as_dst_y -= args.stride_y) { int src_as_dst_y = src_y * args.stride_y; for (;src_as_dst_y > kernel_last_dst_y; src_y -= 1, src_as_dst_y -= args.stride_y) { src_y_copysrc_y = + = sy >= 0 && sy < args.src_tensor.Height(); sy = clamp(sy, 0, args.src_tensor.Height() - 1); if (!in_y0) continue; int kernel_y = kernel_first_dst_y - src_as_dst_y; int src_as_dst_x = src_x * args.stride_x; int src_x_copy = src_x; for (;src_as_dst_x > kernel_last_dst_x; src_x_copy -= 1, src_as_dst_x -= args.stride_x) { = src_x_copy + = sx >= 0 && sx < args.src_tensor.Width(); = clamp(sx, 0, args.src_tensor.Width() - 1); if (!in_x0) continue; , 0); , ( int ds = args.src_tensor.SliceStride(); int kernel_x = kernel_first_dst_x - src_as_dst_x; int kernel_index = (kernel_z * args.kernel_size_y + kernel_y) * args.kernel_size_x + kernel_x; int kernel_index = kernel_y * args.kernel_size_x + kernel_x; int f_offset = f_base + kernel_index * args.src_tensor.Slices() * int x_c = kernel_index * args.src_tensor.Slices(); for (int s = 0; s < args.src_tensor.Slices(); ++s) { , s); += ds __global FLT4* weights_cache = args.weights.GetPtr(f_offset); FLT4 f$1 = args.weights0.Read(dst_s + $0, x_c); FLT4 f$2 = args.weights1.Read(dst_s + $0, x_c); FLT4 f$3 = args.weights2.Read(dst_s + $0, x_c); FLT4 f$4 = args.weights3.Read(dst_s + $0, x_c); x_c++; FLT4 f0, f1, f2, f3; f0 = args.weights.Read(f_offset + f1 = args.weights.Read(f_offset + f2 = args.weights.Read(f_offset + f3 = args.weights.Read(f_offset + , src f_offset += } } } if (dst_s < args.dst_tensor.Slices()) { FLT4 bias_val = args.biases.Read(dst_s); xc, yc { dst_s++; } biasesvectorbasic_stringNo implementation of perform const expressionNo implementation of perform selector_s && N6tflite3gpu21ConvolutionTransposedEN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%&()*+,./012456789;<=>?@BCDEFHIJKMNOPRSTUVWYZ[\^_`acdefhijklnopqrtuvwxz{|}~     !"#%&'()+,-./12345789:;=>?@ABDEFGHOPRTU!$nzxpvtv Kt K*s Kmq0Kx3svqIzp KoKnLx Klj(uvKSz0Vx|vttLrLr Gw{LouZLsLqLn>\m>IqLk>iDB+p8KNyHBQwBnHKyuCsE)m4Lvk.4LibDLyDLw'LFu4LosESLq'Lp4LnSL mF4LMkzDLq F5p|Hi'Lx4LvSLul-LFsXLnH3mHqh Ko LkIiJ%yJ(w$LinxKlL$k Lvi LPu4Lys\Nux3 Lv? $LqdN pPl` -Lj XLnPmTQtc Ls~ 7L[q /Lo L0n _L:x L7z LWkpQiScv Kt Lr Lx(SvHT'uLT9 Ps4U*qKq8UohVo LsnlVlV n Lbl L.kViYz5 L xA %LgzYxZvf L[t 7LvZt<[r /Lq LRo _Lm K&le L#sP[fq]o];nD^xjKlH^j^yv Lw| LBz^Ex_u Lnv_tar Lra5qKbnlxl@(Kk|oi@;kh(K`zDnxi(Kvtx!KsTqo)n u KljqK0z3xoK\vtr#qtWn $KoxnlH K[ljzxvTt,ku Lr0pdiLKovxmlqjBn@ KlPKj` Kt y w  u#trpl"oQvLjmlKiHSjy7vh!w!u!#}t#(s([rT(*.p.o\.0mkdto4*j4ry46m6wluHl;s;2r(;=j=BwpBDHnHMbmMkMcxLRjRTyDRTAt TYWwYu Y^s^ r(^c;pcncv Lh9mhjnknptitvz+yz|.wVus0qp4nmt.L]kis&Lyw-uVsqy oynl4kixp vu8s{qoPnluw  k]iYz\xvdp t nrBqo!%"n%'+zl+-1j137)z79=,x=?q ?DJvDFjHqK J0)#^Y "M0"^d".KIxKFEF##j[x"7f(Kj$FE$!OOCH CJ;$R=T"?P"A0"_ "cR" TIvrM"h"h"h}GD#,xe  g DH '"!BcB_f\"(EgKV@_h#"7Pl"nXL"tVL"z2SL"JBDI("4vh_hClT>"B0";z!"1"=x"B,`"5 ""H %L"R%$"Yy$}#4"8"e "c; 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V @P  `*` A*A88 <@0D @ W `D`P @K P DP@`D1/ UPKV DPJ1/D`VT DPG1/D@TpFO-MP`P  0p pQpQpP  R P 0Pp0 pPPl0p0P pPP VpM @ Q pW P$ P pPPpP ppP `P`P@Q V@ P pPPWW P pPp VK P` Q QQ` F K-`PP % p pP `@ @T  1PCX  3P R P APPEL-@Q P PApL-`PP  '   P  @0  P 0   p@0@  p  P!pCDŽM-P@ R `U   PUp `aE߄K-@P R pUP  pE`0FpS:B:qU` P `3pU   EK-M  `PP% p pP `@ @T  1PCX  3P RPAPPPKEM-@`Pp @R*V `w*ڀWp1pq#PU```   @R *pP `PU PU  E߄K-M C00O@ @@TLpp` FB!11@T@1R@!T T>`"2!   `PDW @D@DAD@DP P``W  D@GPD1/T@pW  KT 1/D@EL-@`W D7p1/pWP ЌC̈́src_tensordst_tensorweightsfilter_offsetpadding_xpadding_y CONV( < args.dst_tensor.Width() && < args.dst_tensor.Height()) { FLT4 res0 = TO_FLT4(r) + bias_val; args.dst_tensor.Write(res0, GLOBAL_ID_args.src_tensor.Read( * INIT_FLT(#define CONV(R, SRC, F) \ R += SRC.x * weights_cache[F]; \ R += SRC.y * weights_cache[F + 1]; \ R += SRC.z * weights_cache[F + 2]; \ R += SRC.w * weights_cache[F + 3]; R += TO_ACCUM_TYPE(SRC.x * weights_cache[F] + SRC.y * weights_cache[F + 1] + SRC.z * weights_cache[F + 2] + SRC.w * weights_cache[F + 3]); R.x += dot(SRC, weights_cache[F]); \ R.y += dot(SRC, weights_cache[F + 1]); \ R.z += dot(SRC, weights_cache[F + 2]); \ R.w += dot(SRC, weights_cache[F + 3]); SIMD_LOCAL_MEM_BARRIERLOCAL_MEM_BARRIER__constant__global__attribute__((reqd_work_group_size(8, 4, 1))) MAIN_FUNCTION($0) { int linear_id = ; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); int X = int DST_X = X * 2; int SRC_X = X + args.padding_x; int Y = int DST_Y = Y * 2; int SRC_Y = Y + args.padding_y; int Z = if (DST_X >= args.dst_tensor.Width() || DST_Y >= args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) return; ACCUM_FLT4 r0 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r1 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r2 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r3 = INIT_ACCUM_FLT4(0.0f); int f_offset = Z * args.filter_offset; __local FLT4 weights_cache[36]; int local_id = LOCAL_ID_1 * 8 + LOCAL_ID_0; bool in_x0 = SRC_X >= 0 && SRC_X < args.src_tensor.Width(); bool in_x1 = SRC_X + 1 >= 0 && SRC_X + 1 < args.src_tensor.Width(); bool in_y0 = SRC_Y >= 0 && SRC_Y < args.src_tensor.Height(); bool in_y1 = SRC_Y + 1 >= 0 && SRC_Y + 1 < args.src_tensor.Height(); int addr_0 = args.src_tensor.GetAddress(SRC_X, SRC_Y, 0); int addr_1 = args.src_tensor.GetAddress(SRC_X + 1, SRC_Y, 0); int addr_2 = args.src_tensor.GetAddress(SRC_X, SRC_Y + 1, 0); int addr_3 = args.src_tensor.GetAddress(SRC_X+1, SRC_Y+1, 0); addr_0 = select(-1, addr_0, (in_x0 && in_y0)); addr_1 = select(-1, addr_1, (in_x1 && in_y0)); addr_2 = select(-1, addr_2, (in_x0 && in_y1)); addr_3 = select(-1, addr_3, (in_x1 && in_y1)); int dz_0 = select(0, args.src_tensor.SliceStride(), (in_x0 && in_y0)); int dz_1 = select(0, args.src_tensor.SliceStride(), (in_x1 && in_y0)); int dz_2 = select(0, args.src_tensor.SliceStride(), (in_x0 && in_y1)); int dz_3 = select(0, args.src_tensor.SliceStride(), (in_x1 && in_y1)); int xc0 = clamp(SRC_X, 0, args.src_tensor.Width() - 1); int xc1 = clamp(SRC_X + 1, 0, args.src_tensor.Width() - 1); int yc0 = clamp(SRC_Y, 0, args.src_tensor.Height() - 1); int yc1 = clamp(SRC_Y + 1, 0, args.src_tensor.Height() - 1); int addr_0 = args.src_tensor.GetAddress(xc0, yc0, 0); int addr_1 = args.src_tensor.GetAddress(xc1, yc0, 0); int addr_2 = args.src_tensor.GetAddress(xc0, yc1, 0); int addr_3 = args.src_tensor.GetAddress(xc1, yc1, 0); int dz = args.src_tensor.SliceStride(); for (int s = 0; s < args.src_tensor.Slices(); ++s) { async_work_group_copy(weights_cache, args.weights.GetPtr(f_offset), 36, 0); weights_cache[local_id] = args.weights.Read(f_offset + local_id); if (local_id < 4) { weights_cache[local_id + 32] = args.weights.Read(f_offset + local_id + 32); }; FLT4* weights_cache = args.weights.GetPtr(f_offset); FLT4 src0 = FLT4 src1 = FLT4 src2 = FLT4 src3 = f_offset += 36; rsrc, ); } FLT4 bias_val = args.biases.Read(Z); if (, Z); } biasesvectorbasic_stringNo implementation of perform const expressionNo implementation of perform selectorGROUP_ID_ * GROUP_SIZE_ + LOCAL_ID_addr_); += dz_) * INIT_FLT(in_x && in_y += dz; )args.src_tensor.Read(SRC_X + , SRC_Y + , s)in_xin_y && N6tflite3gpu24ConvolutionTransposed3x3EN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%'()*+-./02345789:;<>?@ACDEFHIJKLNOPQRTUVWXZ[\]^`abcdfghijlmnoprstuwxyz|}~     !"#%&'()+,-./12345689:;<DEGIJ^'ksjjYi&> Th } ?jj ?kgQfUeOdKh(?bg8 ?HfH ?hb$BJ$A5ccba($BkP$BLe@Fd$@,c?(@Zbg(@k)@7iF(@)hn,@@g,@&f-@Sj@$d @*e@8b' @ c @ek00@1j`@iu@h@k$!B]j( g0@f0@d#@d#@b1 @Ai@3hhb<@0kR#@ju @Jgx0fh@g#@f @ew@d;*@ce*@b*@a*@k*@i #@h0/@4e.dg_?@fG@e@@d%H@cm=@cBbbA@aA@k,A@im2@h2@g2@f2@e5J@dJ@cJ@b J@ok;j a] ;@j ?@i <@h @@gS 9@f 9@e 9@ i h`!zd 9@c7 +@gh!f"bb 8@e 7@d" d%i G@h2 @gK S@f @b& b'j Q@:k 'jd'jd @c @b @hp'g(a @f(e)j! @d)c)b) bD+xf< @i6 @#kL+j+{h8 @gX ?h+g-|e? 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V @P  `*` A*A88 <@0D @ W `D`P @K P DP@`D1/ UPKV DPJ1/D`VT DPG1/D@TpFO-MP`P  0p pQpQpP  R P 0Pp0 pPPl0p0P pPP VpM @ Q pW P$ P pPPpP ppP `P`P@Q V@ P pPPWW P pPp VK P` Q QQ` F K-`PP % p pP `@ @T  1PCX  3P R P APPEL-@Q P PApL-`PP  '   P  @0  P 0   p@0@  p  P!pCDŽM-P@ R `U   PUp `aE߄K-@P R pUP  pE`0FpS:B:qU` P `3pU   EK-M  `PP% p pP `@ @T  1PCX  3P RPAPPPKEM-@`Pp @R*V `w*ڀWp1pq#PU```   @R *pP `PU PU  E߄K-M C00O@ @@TLpp` FB!11@T@1R@!T T>`"2!   `PDW @D@DAD@DP P``W  D@GPD1/T@pW  KT 1/D@EL-@`W D7p1/pWP ЌC̈́src_tensordst_tensorweights ACCUM_FLT4 r FLT4 src0 = args.src_tensor.Read(X, Y, FLT4 src1 = args.src_tensor.Read(X + 1, Y, FLT4 src2 = args.src_tensor.Read(X, Y + 1, FLT4 src3 = args.src_tensor.Read(X + 1, Y + 1, int c0 = args.src_tensor.GetAddress(X, Y, int c1 = args.src_tensor.GetAddress(X + 1, Y, int c2 = args.src_tensor.GetAddress(X, Y + 1, int c3 = args.src_tensor.GetAddress(X + 1, Y + 1, src1 = args.src_tensor.Read(X + 1, Y, src2 = args.src_tensor.Read(X, Y + 1, src3 = args.src_tensor.Read(X + 1, Y + 1, FLT4 bias_val = args.biases.Read( FLT4 result = TO_FLT4(r]) + bias_val; args.dst_tensor.Write(result, MAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.dst_tensor.SetBatchRef(B); args.src_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int Y = GLOBAL_ID_1; if (X >= args.src_tensor.Width() || Y >= args.src_tensor.Height()) return; [2][2]; r[0][0] = INIT_ACCUM_FLT4(0.0f); [0][1] = INIT_ACCUM_FLT4(0.0f); [1][0] = INIT_ACCUM_FLT4(0.0f); [1][1] = INIT_ACCUM_FLT4(0.0f); { ); bool x_in = X + 1 < args.src_tensor.Width(); bool y_in = Y + 1 < args.src_tensor.Height(); c1 = select(-1, c1, x_in); c2 = select(-1, c2, y_in); c3 = select(-1, c3, x_in && y_in); FLT4 src0 = args.src_tensor.Read(c0); FLT4 src1 = args.src_tensor.Read(c1); FLT4 src2 = args.src_tensor.Read(c2); FLT4 src3 = args.src_tensor.Read(c3); FLT4 src1 = INIT_FLT4(0.0); FLT4 src2 = INIT_FLT4(0.0); FLT4 src3 = INIT_FLT4(0.0); if (x_in) { } if (y_in) { if (x_in && y_in) { [0][0][0][1][1][0][1][1] X *= 2; Y *= 2; X + Y + } biasesbasic_stringNo implementation of perform const expressionNo implementation of perform selector $0 += $1.x * args.weights.Read($2); $0 += $1.y * args.weights.Read($3); $0 += $1.z * args.weights.Read($4); $0 += $1.w * args.weights.Read($5); $0 += TO_ACCUM_TYPE($1.x * args.weights.Read($2) + $1.y * args.weights.Read($3) + $1.z * args.weights.Read($4) + $1.w * args.weights.Read($5)); $0.x += dot($1, args.weights.Read($2)); $0.y += dot($1, args.weights.Read($3)); $0.z += dot($1, args.weights.Read($4)); $0.w += dot($1, args.weights.Read($5)); vectorN6tflite3gpu28ConvolutionTransposed3x3ThinEN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$&  "#$%&()*+-./12345789:;=>?@ACDEFGIJKLNOPQRSUVWXZ[\]_`abcefghiklmnpqrsuvwyz{}~ =ZYY XW   Y  W(vVU,UW W  mV50 Ue0 #U# iT# S mZ sY N rTSPX( WY  wZX}YVVf! 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R.x += dot(SRC, weights_cache[F]); \ R.y += dot(SRC, weights_cache[F + 1]); \ R.z += dot(SRC, weights_cache[F + 2]); \ R.w += dot(SRC, weights_cache[F + 3]); __constant__global__attribute__((reqd_work_group_size(8, 4, 1))) MAIN_FUNCTION($0) { GLOBAL_ID_0(GROUP_ID_ * GROUP_SIZE_0 + LOCAL_ID_0); GLOBAL_ID_1 * GROUP_SIZE_1 + LOCAL_ID_1); GLOBAL_ID_2 * GROUP_SIZE_2 + LOCAL_ID_2); ; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); if (X * 2 > args.dst_tensor.Width() || Y * 2 > args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) return; ACCUM_FLT4 r0 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r1 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r2 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r3 = INIT_ACCUM_FLT4(0.0f); int f_offset = Z * args.filter_offset; __local FLT4 weights_cache[64]; int local_id = LOCAL_ID_1 * 8 + LOCAL_ID_0; bool in_x0 = X - 1 >= 0 && X - 1 < args.src_tensor.Width(); bool in_x1 = X >= 0 && X < args.src_tensor.Width(); bool in_y0 = Y - 1 >= 0 && Y - 1 < args.src_tensor.Height(); bool in_y1 = Y >= 0 && Y < args.src_tensor.Height(); int addr_0 = args.src_tensor.GetAddress(X - 1, Y - 1, 0); int addr_1 = args.src_tensor.GetAddress(X, Y - 1, 0); int addr_2 = args.src_tensor.GetAddress(X - 1, Y, 0); int addr_3 = args.src_tensor.GetAddress(X, Y, 0); addr_0 = select(-1, addr_0, (in_x0 && in_y0)); addr_1 = select(-1, addr_1, (in_x1 && in_y0)); addr_2 = select(-1, addr_2, (in_x0 && in_y1)); addr_3 = select(-1, addr_3, (in_x1 && in_y1)); int dz_0 = select(0, args.src_tensor.SliceStride(), (in_x0 && in_y0)); int dz_1 = select(0, args.src_tensor.SliceStride(), (in_x1 && in_y0)); int dz_2 = select(0, args.src_tensor.SliceStride(), (in_x0 && in_y1)); int dz_3 = select(0, args.src_tensor.SliceStride(), (in_x1 && in_y1)); int xc0 = clamp(X - 1, 0, args.src_tensor.Width() - 1); int xc1 = clamp(X, 0, args.src_tensor.Width() - 1); int yc0 = clamp(Y - 1, 0, args.src_tensor.Height() - 1); int yc1 = clamp(Y, 0, args.src_tensor.Height() - 1); int addr_0 = args.src_tensor.GetAddress(xc0, yc0, 0); int addr_1 = args.src_tensor.GetAddress(xc1, yc0, 0); int addr_2 = args.src_tensor.GetAddress(xc0, yc1, 0); int addr_3 = args.src_tensor.GetAddress(xc1, yc1, 0); int dz = args.src_tensor.SliceStride(); for (int s = 0; s < args.src_tensor.Slices(); ++s) { async_work_group_copy(weights_cache, args.weights.GetPtr(f_offset), 64, 0); weights_cache[local_id] = args.weights.Read(f_offset + local_id); weights_cache[local_id + 32] = args.weights.Read(f_offset + local_id + 32); FLT4* weights_cache = args.weights.GetPtr(f_offset); FLT4 src0 = FLT4 src1 = FLT4 src2 = FLT4 src3 = f_offset += 64; CONV(r0, src0, 0); CONV(r1, src0, 4); CONV(r2, src0, 8); CONV(r3, src0, 12); CONV(r0, src1, 16); CONV(r1, src1, 20); CONV(r2, src1, 24); CONV(r3, src1, 28); CONV(r0, src2, 32); CONV(r1, src2, 36); CONV(r2, src2, 40); CONV(r3, src2, 44); CONV(r0, src3, 48); CONV(r1, src3, 52); CONV(r2, src3, 56); CONV(r3, src3, 60); } X = X * 2 - 1; Y = Y * 2 - 1; FLT4 bias_val = args.biases.Read(Z); if (X >= 0 && Y >= 0) { FLT4 result = TO_FLT4(r0) + bias_val; args.dst_tensor.Write(result, X, Y, Z); if (X + 1 < args.dst_tensor.Width() && Y >= 0) { FLT4 result = TO_FLT4(r1) + bias_val; args.dst_tensor.Write(result, X + 1, Y, Z); if (X >= 0 && Y + 1 < args.dst_tensor.Height()) { FLT4 result = TO_FLT4(r2) + bias_val; args.dst_tensor.Write(result, X, Y + 1, Z); if (X + 1 < args.dst_tensor.Width() && Y + 1 < args.dst_tensor.Height()) { FLT4 result = TO_FLT4(r3) + bias_val; args.dst_tensor.Write(result, X + 1, Y + 1, Z); } biasesvectorbasic_stringNo implementation of perform const expressionNo implementation of perform selectoraddr_); += dz_;) * INIT_FLT(in_x && in_y += dz;)args.src_tensor.Read(X + , Y + , s)in_xin_y &&  N6tflite3gpu24ConvolutionTransposed4x4EN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$&  "#$%&()*+-./02345789:;<>?@ACDEFHIJKLNOPQRTUVWXZ[\]^`abcdfghijlmnoprstuwxyz|}~     !"#$%'()*+,./01245679:;<CDFHI%jfii#hg ?]i ?edXd\caa g(?d@e@jEi@Ac)@bD$@ah(@`(@j)@ hfho(@f,@e,@d-@;i@b' @c @a00@``@i @g @cju @f @e @d @c @eD!|%db8?a@`0@Aj70@hg#@g#@fP ?e` ?dp ?cb cu@a `!b"*@mj !i!zaL*@g !f0!`v*@e4!d@!j*@h*@cH!bd!g#@ah!`!of/@Kj!h!seF?@g!f!ed7@e!d"|c@@c"b,"b8@a0"`h"ca4=@)jl"h"z`q9@j9@h5@g"yf"g2@}e"od"EfJ2@\e|2@c"b"Nd2@ecJ@ma#`$#Wb*J@j(#h4#LatJ@g8#OfP#c`J@i ;@feX#Xdp#hC 7@oct#ab#Zgz <@Va#m`#.f 8@i#h#Ee 9@dg#8f#7d' 9@Oe#Ad#Nc` 9@Xc#Jb#@b 9@5a +@S` 8@?a#]`$qh5 Q@Jg G@f Q@'dU @>cf @0bw @%a @C` @i @ah @:g @f @%e @d( @.cA @ bZ @as @3` @i @Qh @*g @e @e @d"@c;@b@@aB@#`T@jf(@Ki@h+@f-@e4@d5+@c`1@b5@a+@`1@sj"N@)ip+@g5@f@5e 7@?h8 i {h(  g Tg(f?e|%1d5`B@Hc5:bl6g@/ap6M`6f@i6kh7Qj?hH@gL@fT@eV@dh @cq@e@`{@/j@h@b ?ay@e\DgfT/e8!d8 cp8c8*b9a9=`d>`ip>[h@i4gf\e@dPDf "(c"$(b(-a-2-`2j2d@7Vi7hD79a 9>g>e >CdCc(CHbHJNaNPT`TVZ~jZ\`4i`bfgff0fhleld4lnrcrbrb.@waw`wa&@|\j|hgfedud cba`c @:jhgfedUf cbsa`jgb hghfle^dhucjgzb\a s`  jh}g!>f!#'Ue')i ).Gd.04^c49Pb9Ea9A+CAe`C"#Z "2?0"Cd"_=zi;0" :?>?Sx"%CBq!%`!"C<% AuVB?>$!C "m"\">2 ""(hE"h"Hl@8/8|9PC9_~D Wo^~=p>Li=>BZR;Hl"N6QL"TcNL"ZKL"`B'<x<@o9"o#"/"'""V`"S"(]"-:"4z&L"7&$">. %B%"04"f8"lO\ "r,[7 "wpA "||"> "0","5:"C h"?d" ""`"p "x" 6"$ "!Y" RV"g)"T"""P". 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Vx   K   K D A  `Q 0 Spp @ @    0CS R 00  @T @p0T @ p0p T @KP@ D T @TF O-tMp`0P  倀0 P $P (P !AAX@ t PX     PP PpX @@ PLP`,`(wiFHP3 4KgtGD0 ,K<@ 8@ 4K8 K88 P 1/4[ ,D`P H4P@US 8QM `VG v 0X wiF3 4KgtG0 ,KD@P 8P 4K8 K88 P 1/4[ ,LP PlY K48P$K(K488 P 1/88 P4[1/4[ 4[ ,4[ 4[ ,Y (P $ L hFY  $ L-D@8P < <AH-@H WYPU[PUmP P `V Q DPApD1/UP``V Q DPApD1/UP`\P `D L$<80,$   PU Q `V v PPU Q `V v PPD CO-tM@p `   $ ( !AAXP u` ``X  @ @Pf Pp pX @PpL`,`(wiFH3 4KgtGD@0 ,pK< $0  pp`0  p$p(p,P0@48 = args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || S >= args.dst_tensor.Slices()) { return; } ACCUM_FLT4 r = INIT_ACCUM_FLT4(0.0f); int fx_c = S * args.kernels_total_size; int fx_c = 0; args.weights.Width()args.kernel_size_xargs.weights.Height()args.kernel_size_yargs.weights.Depth()args.kernel_size_z; ++kz) { int z_c = z_src + kz * args.dilation_z; z_c bool inside_z = z_c >= 0 && z_c < args.src_tensor.Depth(); z_c = clamp(z_c, 0, args.src_tensor.Depth() - 1); ; ++ky) { int y_c = y_src + ky * args.dilation_y; y_c bool inside_y = y_c >= 0 && y_c < args.src_tensor.Height(); y_c = clamp(y_c, 0, args.src_tensor.Height() - 1); ; ++kx) { int x_c = x_src + kx * args.dilation_x; x_c bool inside_x = x_c >= 0 && x_c < args.src_tensor.Width(); x_c = clamp(x_c, 0, args.src_tensor.Width() - 1); (kz * + ky) * + kx] FLT4 f = args.weights.Read(kx, ky, S); FLT4 f = args.weights.Read(fx_c); FLT4 f = args.weights.Read(fx_c, S); kx * ky * ][LOCAL_ID_0 + FLT4 src_final; ); fx_c++; FLT4 res0 = TO_FLT4(r) + args.biases.Read(S); args.dst_tensor.Write(res0, X, Y, Z, S); args.dst_tensor.Write(res0, X, Y, S); } biasesvectorbasic_string = args.src_tensor.Read(, S); {int s_layer = S / 2; , s_layer); FLT2 t0 = S % 2 == 0 ? src.xy : src.zw; = INIT_FLT4v4(t0.x, t0.x, t0.y, t0.y);} {int s_layer = S / 4; FLT t0 = src.x; int reminder = S % 4; if (reminder == 1) t0 = src.y; if (reminder == 2) t0 = src.z; if (reminder == 3) t0 = src.w; = INIT_FLT4v4(t0, t0, t0, t0);} {int s_layer = S / args.ch_multiplier; int s_offset = (S % args.ch_multiplier) * 4; FLT temp_arr[4] = {src.x, src.y, src.z, src.w}; src.x = temp_arr[(s_offset + 0) / args.ch_multiplier]; src.y = temp_arr[(s_offset + 1) / args.ch_multiplier]; src.z = temp_arr[(s_offset + 2) / args.ch_multiplier]; src.w = temp_arr[(s_offset + 3) / args.ch_multiplier]; = src;} , S)No implementation of perform const expressionNo implementation of perform selector(y_src + (LOCAL_ID_1 + (x_src + (LOCAL_ID_0 + spatial_cache[ } else { = INIT_FLT4(0.0f); weights_cache[ weights_cache[src_tensorweightsdst_tensor for (int kz = 0; kz < for (int ky = 0; ky < for (int kx = 0; kx < weights_cache[spatial_cache[LOCAL_ID_1 + src_final src_final = src_final * INIT_FLT( r += TO_ACCUM_TYPE(kernel_size_xpadding_xdilation_xkernel_size_ypadding_ydilation_ykernels_total_sizech_multiplierkernel_size_zpadding_zdilation_z FLT4 src = args.src_tensor.Read( >= 0 && < args.src_tensor.Width() < args.src_tensor.Height()args.weights.Read(S * args.kernels_total_size + args.weights.Read(N6tflite3gpu13DepthwiseConvEN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$&  "#$%&()*+,./01235678:;<>?@ABDEFGHJKLMNPQRSTVWXY[\]^_`bcdeghijlmnoqrstuwxyz{}~     ZY{X W K'B |VYiUNTdrX!lSh8R|~W sV%`U8QZET YZXcS0fW[V/R@HU8T|"S KS"R$RQ$Z4%YY8%/XH)DWL)CV*QU* T+!S+QB>UPAS`nU,PBZOY'VHUaShSh%Q P-hZ*W W V2 $TV $Sz $R "Q ,P 2FZ 5XS <W <V <U <TC ST\7YX0P\4-WT\ZLOYj_%X:Wx9VUT\W4S QGLRh!V\T^P1$ZXM =Q<S^RnQ QnPPozZ -YX #W20Vb0T#S#RQ"P2XZD2 YvWbZoYqW3U3T 3Wq WtrS?RUjQP6Z)UrTsUMW'X+V8SsRsSvT`QsP tQRP@ZtXuZ WuV$vX-V@U-7U0vT|wSRd SwR yQo-YAX8QyP{V Z {X{U W{VT|T$-UX|T|~RU@oQ7S|R}XQ~P,~WY0~X~sP8*nR,_Q'W~VV0UTUSR,uTyQ0PXbWhV@Un/Q'eT~qS` ^Rp&OQcPZ Y1lW)`X,aV*QPdYZXWNUQS R QrY HX JWIV(_YVU\5X"T"ST"$(xR(iQ\(*}PY$U,XW &T8RH PX T.V.U.0'S05oT5:{S:>hR>@DYQDFJmPJLPZPRVYVkXVZ4[wW[lVD[]T ]bYUb>T bg\Sg(R(gl(QlZl=Y; q}YqswSXwy}UW}TV}7U1T:SRQ0ZHY4X3WWR .2V UV &SSQPsZ&YXWTVTSRQPdRQZYWZ VUTV SR(UQPL /Z Xh Wp  F.4-XnN0L+" O@0 "V10"gYf4|A#Fh"q:3"l6h" `" "wY!40P\ =-_3^8"1a1.))@"d(""}`"#0$.5l"K ,OBx"d"(\""=10$!rF\"D"f-l",0"":"o2d7l">@L"D3=L"J_:L"P4*.//8".NK" IP""52 ":FL"[$"bMe4"8"M "L& "3 ""K "$ "g"f"""*"1d" . -241!0#!3 `Xx<l@,8LL (           4x4D\4h0T   dtTp|`|H D 0t`|P (Hdt dX t  ,!!!""X"|" ,#H#d#$$$$$#%4%#%&$&&d'''''(((H) (*D*T*h****`++*++++ , ,4,H,\,-8-H-\---t...(/(0D0T0h00011111@23,3`3(44585h56666<7x77888`8P9l99<:P:d:x:::::;;$;,;4;<;D;L;T;\;d;l;t;|;;;;;;;;;;;;;;;;;< <`<<<<<==== >D????@@,@@@T@h@|@AdApAAAAAAAB$B8BLB`BxB|BB/B/B0B0CO?P@PAPB P8P9PCPDPE PF$PG(PH,PILP`PxPPPPPQ 8* D )@c) P*P ) ) * (p( * ` /l *  %|h! + p + | \^ + "H )pT"% , % \d (, ( cp̫(_ , + ԫT , .` - 0p. - 2  . 5p5 . 7 2 2p:2  . ; ^7$l=6 0. >T7  5p>5 P. 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-ء-\-/ԫ00x1233l44556788l99::p;<==p>Ш>̨?,ԫ@@lAABBxCDEElFFGGpHIJJhJKLLtMاMԧNOlOħPQQpRRSThTUVVdWWXXpYZ[[d\ܦ\ئ],ԫ^^l_Ȧ_Ħ``habcclddeepfghܪhhiijتjdklmԪmlmХn̥oЪoppqr̪rhrstȪtduuvvpwxyydzz{,ԫ||h}ؤ}Ԥ~~hĤd̂Ѓ؃hdȈd,ԫ|ܣأtȣďģȐАtđt ̔ԫԝܝĞ̞ԞܞܪتԪЪ̪ȪȟП؟ܢ̢ȠРؠءAAFX 5tH5 5 ////h///h/// h / / / h / / 0 d /0d /0d /0d /5x5 5 43 225t2 1 11 1 1"5"t#1$ 1$ 1%1% 0&0(5(t) 0) 0* 0*0+ 0+0.5.5.5.5.0.0.0.0././././/E߄EE (ZHZT,[`,v< v wH hxT O-M@ ` p `*`8$G A*A8P<`P v  p8<@pp  *@ :@*J@:\@JQp Y* W: ZJ @*@*:@:J@J` P\ P*P:Z@J^*:J0 `@P\p@*@:Pp@J*Yp:ZPJ'@&*@*%:@:$J@Ja\QpPp*Yp:ZPJ#@"*@*!:@: J@Ja\QpPp*Yp:ZPpJ@*@*:@:J@J\QpPp*Yp:ZPpJ@*@*:@:J@J\PQpPp*Yp:ZPpJ@*@*:@:J@J\PQpPp*Yp:ZPpJ@*@*:@:J@J\QpPp*Yp:ZPJ@* : JpP`p\ @*P@:P@JZ @*P*@:P:@JZJKFO-,M   /"/BqBqpW;@ * |B: q4qDqt `R:*::#qP5; JB: 6P Y ::::#qPEK JB: F@P NQ:Z::#qPu{ JB: vpP ~V%hT:p#8"j0:qDN 0Np:#P0qUPEPS&8ZJZV @Q q 0!$ p$PP$P @Ul @ 겠@\㲀NPN `$p$PPa@R(ZC W\wA:J::#PqqUPP ZJZvVPpW p^$HP@Rq:z::#0qqS00 :J:60S'8 p 0Z 4qD: ::#0qS0E0K:J:F60@T >@ 0 W4qd): ::#0qS0e0k:J:f60`V > 0fKFpL-@0P 4 PU $Q `V v  $P pCDŽsrc_tensordst_tensor r0 += TO_ACCUM_TYPE( r1 += TO_ACCUM_TYPE( r2 += TO_ACCUM_TYPE( r3 += TO_ACCUM_TYPE( r0 += TO_ACCUM_TYPE( r1 += TO_ACCUM_TYPE( r2 += TO_ACCUM_TYPE( r3 += TO_ACCUM_TYPE(OpenCL 2.0 QUALCOMM build: commit #7daed58 changeid #I7ece6fe30d Date: 10/19/16 * INIT_FLT( s0 = args.src_tensor.Read( s1 = args.src_tensor.Read( s2 = args.src_tensor.Read( s3 = args.src_tensor.Read(weights__attribute__((reqd_work_group_size(8, 4, 1))) MAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = (linear_id / args.dst_tensor.Batch()) * 2; int B = linear_id % args.dst_tensor.Batch(); args.dst_tensor.SetBatchRef(B); args.src_tensor.SetBatchRef(B); int X = GLOBAL_ID_0 * 2; int Y = GLOBAL_ID_1 * 2; int S = GLOBAL_ID_2; ACCUM_FLT4 r0 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r1 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r2 = INIT_ACCUM_FLT4(0.0f); ACCUM_FLT4 r3 = INIT_ACCUM_FLT4(0.0f); if (X >= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || S >= args.dst_tensor.Slices()) { return; } __local FLT4 f[10]; event_t e = async_work_group_copy(f, args.weights.GetPtr() + S * 10, 10, 0); wait_group_events(1, &e); int local_id = LOCAL_ID_1 * 8 + LOCAL_ID_0; if (local_id < 10) { f[local_id] = args.weights.Read(S * 10 + local_id); } LOCAL_MEM_BARRIER; __global FLT4* f = args.weights.GetPtr() + S * 10; FLT4 s0; FLT4 s1; FLT4 s2; FLT4 s3; X - 1X + 1X + 2Y - 1Y + 1Y + 2 FLT4 f0 = args.weights.Read(0, S); FLT4 f1 = args.weights.Read(1, S); FLT4 f2 = args.weights.Read(2, S); FLT4 f3 = args.weights.Read(3, S); FLT4 f4 = args.weights.Read(4, S); FLT4 f5 = args.weights.Read(5, S); FLT4 f6 = args.weights.Read(6, S); FLT4 f7 = args.weights.Read(7, S); FLT4 f8 = args.weights.Read(8, S); int x0 = X - 1; int x1 = X; int x2 = X + 1; int x3 = X + 2; bool x0_in = x0 >= 0 && x0 < args.dst_tensor.Width(); bool x1_in = x1 >= 0 && x1 < args.dst_tensor.Width(); bool x2_in = x2 >= 0 && x2 < args.dst_tensor.Width(); bool x3_in = x3 >= 0 && x3 < args.dst_tensor.Width(); x0 = clamp(x0, 0, args.dst_tensor.Width() - 1); x1 = clamp(x1, 0, args.dst_tensor.Width() - 1); x2 = clamp(x2, 0, args.dst_tensor.Width() - 1); x3 = clamp(x3, 0, args.dst_tensor.Width() - 1); int y0 = Y - 1; int y1 = Y; int y2 = Y + 1; int y3 = Y + 2; bool y0_in = y0 >= 0 && y0 < args.dst_tensor.Height(); bool y1_in = y1 >= 0 && y1 < args.dst_tensor.Height(); bool y2_in = y2 >= 0 && y2 < args.dst_tensor.Height(); bool y3_in = y3 >= 0 && y3 < args.dst_tensor.Height(); y0 = clamp(y0, 0, args.dst_tensor.Height() - 1); y1 = clamp(y1, 0, args.dst_tensor.Height() - 1); y2 = clamp(y2, 0, args.dst_tensor.Height() - 1); y3 = clamp(y3, 0, args.dst_tensor.Height() - 1); args.weights.Read(S * 10 + f[) { * s0); * s1); * s2); * s3); FLT4 bias = args.weights.Read(9, S); ); if(X + 0 < args.dst_tensor.Width() && Y + 0 < args.dst_tensor.Height()) { FLT4 result = TO_FLT4(r0); args.dst_tensor.Write(result, X + 0, Y + 0, S); if(X + 1 < args.dst_tensor.Width() && Y + 0 < args.dst_tensor.Height()) { FLT4 result = TO_FLT4(r1); args.dst_tensor.Write(result, X + 1, Y + 0, S); if(X + 0 < args.dst_tensor.Width() && Y + 1 < args.dst_tensor.Height()) { FLT4 result = TO_FLT4(r2); args.dst_tensor.Write(result, X + 0, Y + 1, S); if(X + 1 < args.dst_tensor.Width() && Y + 1 < args.dst_tensor.Height()) { FLT4 result = TO_FLT4(r3); args.dst_tensor.Write(result, X + 1, Y + 1, S); } vectorbasic_stringNo implementation of perform const expressionNo implementation of perform selectorx0_inx1_inx2_inx3_iny_in, , S); N6tflite3gpu16DepthwiseConv3x3EN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$&  "#$%&()*+-./12346789:;=>?@BCDEGHIJKMNOPQSTUVWYZ[\]_`abcefghiklmnpqrsuvwyz{}~:DCDCA @c B ??A0@0?E ?e6>0&=#&<#H;#D-BIAa+@+?+>+&;></=pDPB= j=w<<6A/@>?V9>=; ; C B /<Q;C4'SB['/A'4@'b?'r>'x='}<E';l':C1B A@9K?9-DPB[>M9a=9f<3y;3:%3lCX3D>J=O<A,[@@b;::\C :BG:@:@4.?44># 4:=W 4?d>@ B ==)> = <)0;*=  D*B ,< 6;@A,@L-?P->.D =.</B ;/;01C81Bp2A`iAx2@3?3>4=4<(6;,6:`7@Ch7uB8QA8V@9y?9>;=;<T<;X<:=C=]B>9A>>@4@l?@@|>tA=xA<B;B:CCC;B 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args.intermediate.Read(0, 0, Z, B); int state_stride = args.activation.Slices(); FLT4 r1 = args.intermediate.Read(0, 0, Z + state_stride, B); FLT4 r2 = args.intermediate.Read(0, 0, Z + state_stride * 2, B); FLT4 r3 = args.intermediate.Read(0, 0, Z + state_stride * 3, B); FLT4 input_gate; FLT4 new_input; FLT4 forget_gate; FLT4 output_gate; input_gate.x = native_recip(1.0h + native_exp(-r0.x)); input_gate.y = native_recip(1.0h + native_exp(-r0.y)); input_gate.z = native_recip(1.0h + native_exp(-r0.z)); input_gate.w = native_recip(1.0h + native_exp(-r0.w)); new_input.x = 1.0h - 2.0h * native_recip(1.0h + native_exp(2.0h * r1.x)); new_input.y = 1.0h - 2.0h * native_recip(1.0h + native_exp(2.0h * r1.y)); new_input.z = 1.0h - 2.0h * native_recip(1.0h + native_exp(2.0h * r1.z)); new_input.w = 1.0h - 2.0h * native_recip(1.0h + native_exp(2.0h * r1.w)); forget_gate.x = native_recip(1.0h + native_exp(-r2.x)); forget_gate.y = native_recip(1.0h + native_exp(-r2.y)); forget_gate.z = native_recip(1.0h + native_exp(-r2.z)); forget_gate.w = native_recip(1.0h + native_exp(-r2.w)); output_gate.x = native_recip(1.0h + native_exp(-r3.x)); output_gate.y = native_recip(1.0h + native_exp(-r3.y)); output_gate.z = native_recip(1.0h + native_exp(-r3.z)); output_gate.w = native_recip(1.0h + native_exp(-r3.w)); FLT4 input_gate = INIT_FLT4(1.0f) / (INIT_FLT4(1.0f) + exp(INIT_FLT4(-1.0f) * r0)); FLT4 new_input = tanh(r1); FLT4 forget_gate = INIT_FLT4(1.0f) / (INIT_FLT4(1.0f) + exp(INIT_FLT4(-1.0f) * r2)); FLT4 output_gate = INIT_FLT4(1.0f) / (INIT_FLT4(1.0f) + exp(INIT_FLT4(-1.0f) * r3)); FLT4 new_st = input_gate * new_input + forget_gate * prev_st; FLT4 act_value = output_gate * tanh(new_st); args.activation.Write(act_value, 0, 0, Z, B); args.new_state.Write(new_st, 0, 0, Z, B); } clang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%(@% & & &0 &9' ''/'GN'4'1'0'*@'ejD'/D''''z.'wC:' }:':':'[+M'%xM'M'M'_;'p;'m;';'K;'~;'Q;';'7X' 'X'fX'c_A'0'1't-'G.'Q   \  oB!!#fU[:d" 3<l"L" L"L"!FD 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+ args.padding_x) / args.stride_x; int t_x = X - (src_x * args.stride_x - args.padding_x); int src_y = (Y + args.padding_y) / args.stride_y; int t_y = Y - (src_y * args.stride_y - args.padding_y); int src_z = (Z + args.padding_z) / args.stride_z; int t_z = Z - (src_z * args.stride_z - args.padding_z); int t_index = (t_y * args.kernel_size_x + t_x) * args.kernel_size_z + t_z; int t_index = t_y * args.kernel_size_x + t_x; bool inside_x = src_x >= 0 && src_x < args.src_tensor.Width(); src_x = clamp(src_x, 0, args.src_tensor.Width() - 1); bool inside_y = src_y >= 0 && src_y < args.src_tensor.Height(); src_y = clamp(src_y, 0, args.src_tensor.Height() - 1); bool inside_z = src_z >= 0 && src_z < args.src_tensor.Depth(); src_z = clamp(src_z, 0, args.src_tensor.Depth() - 1); src_x, src_y, src_z, Ssrc_x, src_y, S); args.src_tensor::type result; result.x = t_index == ind.x ? src.x : INIT_FLT(0.0f); result.y = t_index == ind.y ? src.y : INIT_FLT(0.0f); result.z = t_index == ind.z ? src.z : 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((''('' ( (( CDŽAF    $  , 0    P   H      PAC,, lLC%(t  @F<<            D    @<  E TT h`$CDŽAF p  t      h   t   h     `Xx|&4'l(4)h/0|00(L-@ A $0H-M@T Pd T004/ P K0\PA $`th( 0S/0 S& L- S!  @T @R 0 R0 R@@T  @T @T/oAO- M@`R`' PZP  0PpP     PKF L4hL-`@V*DЌЌ`C@ (pL-@P`$`p C D$0K-PpP` PP `W:P*PP@A@pP@@@EH-`@V Q DPApD1/UP``V Q DPApD1/UP`CL-D@8P < <AH- H/H- ^ P H 0HH-@H WYPU[PUmP P `V Q DPApD1/UP``V Q DPApD1/UP`\P `D L$<80,$   PU Q `V v PPU Q `V v PPD CH- HH- ^ P H 0HO- M@`R`' PႡZP  0PpP !  PKF L4hH- pL-`P\ ^ 0P S PQ10S1 @@T1 @T `VSPpQ: P PQ PQ PQpPPp@`V@ Q @^SPpP P PP ^P PP pCDŽH-     Q/o" /L-^ o L 0 RH R R @T  R @T P7   R0Q00'P  P0 R0 Q 0S L/ P  R00L/AQ/0H- P@0HAH- 0H-P@  A 8 ,H- Q/0H-@PP 1/ 0HAQ/0H-@P 0HAQ/0H-@P 0HAQ/0H-@P 0HAL-M@ p (!2/ K$A $HH-    H- /P/ P///H-@ `P A`pQ w  PPPP CLT$xH- P@  `pQ w  P PPP CH|P$t||/H- L-M@ p (!2/ K$A $HK-M C00O@ @@TLpp` FB!11@T@1R@!T T>`"2!   `PDW @D@DAD@DP P``W  D@GPD1/T@pW  KT 1/D@EO-M@ ` p `*`8$G A*A8P<`P v  p8<@p(X, Y, S); FLT4 result = TO_FLT4((t - mean) * stddev_inv); args.dst_tensor.Write(result, X, Y, S); } }MeanStdDevNormalization not suitable. float stddev_inv = rsqrt(variance + args.variance_bias); for (int S = local_id; S < args.src_tensor.Slices(); S += reduction_group_size) { float4 t = args.src_tensor.Read(X, Y, S); float4 mul0_res = stddev_inv * args.mul_linear.Read(S); float4 mul1_res = mul0_res * t; float4 mul2_res = mul0_res * mean; float4 sub_res = args.sub_linear.Read(S) - mul2_res; FLT4 result = TO_FLT4(mul1_res + sub_res); args.dst_tensor.Write(result, X, Y, S); } }basic_string__attribute__((reqd_work_group_size(, ))) MAIN_FUNCTION($0) { floatfloat2 shared_mem[]; ][ int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int Y = GLOBAL_ID_1; if (X >= args.dst_tensor.Width()) { return; } if (Y >= args.dst_tensor.Height()) { return; } float4 private_sum4_sq = INIT_FLOAT4(0.0f); int local_id = LOCAL_ID_2; int reduction_group_size = GROUP_SIZE_2; int local_id = 0; int reduction_group_size = 1; float4 private_sum4 = INIT_FLOAT4(0.0f); for (int S = local_id; S < args.src_tensor.Slices(); S += reduction_group_size) { int x_clamped = min(X, args.src_tensor.Width() - 1); int y_clamped = min(Y, args.src_tensor.Height() - 1); float4 t = args.src_tensor.Read(x_clamped, y_clamped, S); private_sum4 += t; } float sum = dot(private_sum4, INIT_FLOAT4(1.0f)); private_sum4_sq += t * t; float2 sum; sum.x = dot(private_sum4, INIT_FLOAT4(1.0f)); sum.y = dot(private_sum4_sq, INIT_FLOAT4(1.0f)); sum // Calculate the mean float mean = sum * args.inv_ch_count; // Calculate the squared sum of the difference from the mean. float4 private_sum_diff_sq4 = INIT_FLOAT4(0.0f); for (int S = local_id; S < args.src_tensor.Slices(); S += reduction_group_size) { int x_clamped = min(X, args.src_tensor.Width() - 1); int y_clamped = min(Y, args.src_tensor.Height() - 1); float4 t = args.src_tensor.Read(x_clamped, y_clamped, S); float4 diff = t - mean; private_sum_diff_sq4 += diff * diff; } // Reduce float sum_diff_sq = dot(private_sum_diff_sq4, INIT_FLOAT4(1.0f)); float variance = sum_diff_sq * args.inv_ch_count; float mean = sum.x * args.inv_ch_count; float mean_sq = sum.y * args.inv_ch_count; float variance = mean_sq - mean * mean; // no more shared memory usage, 'useless' threads can exit now // no need to check first element, always valid if ($0 * 4 + 1 >= $1) { $2.y = 0.0f; } if ($0 * 4 + 2 >= $1) { $2.z = 0.0f; } if ($0 * 4 + 3 >= $1) { $2.w = 0.0f; } shared_mem[LOCAL_ID_1][LOCAL_ID_0]shared_mem { // reduction [local_id] = ; LOCAL_MEM_BARRIER; if (LOCAL_ID_2 == 0) { = [0]; += [[0] = } { // reduction, all threads inside workgroup must execute this code $2[local_id] = $1; LOCAL_MEM_BARRIER; // The number of items still need to be summed int reduction_size = $0; while (reduction_size > 1) { int active_thread_limit = reduction_size / 2; int offset = (reduction_size + 1) / 2; if (local_id < active_thread_limit) { $1 += $2[local_id + offset]; $2[local_id] = $1; } LOCAL_MEM_BARRIER; reduction_size = offset; } $1 = $2[0]; } Invalid node.Type mismatch.Not a single consumer.Not a scalar value inside attributes.vectorNo implementation of perform const expressionNo implementation of perform selectorN6tflite3gpu23MeanStdDevNormalizationEN6tflite3gpu18LayerNormalizationE N6tflite3gpu25ElementwiseAttributesBaseILNS0_8DataTypeE2EfEEN6tflite3gpu19GPUObjectDescriptorEN6tflite3gpu14MeanAttributesEclang version 18.1.8A?aeabi5C2.09 A   "$&  !#$%&'(*+,-./12345789:;=>?@ACDEFHIJLMNOQRSTUWXYZ\]^_abcdefhijkmnoprstuwxyz|}~     !"#%&'(*+,-./12345789:;=>?@ACDEFHIJKLNOPQSTUVXYZ[]^_`bcdeghijkrtuwyz|~}u`  |Hn| n{ n{0 n=z[o5} |`{|PHp#|`Fzy"{x#0.xH}%ouwLvp|o}t|{{|{o0zyLzoxPxt~yo&zo_w|vx o} |Uwo{zdTyovo} o|0o{50oze#oy#oxow1o+w 2onv>/o}mo|,o{oz!oy9ox`n8ye ow&oKv>o}C5o|xo{oz1oy4oxo w os}j 5o;v nt| +os{ .oz +oy# BoKzzT64'8[&hl(0^y&@{oizoy[&o3xx&x,' 5w  v xv}v |{|z4'y`(yo{Nyl(x)=`ly &oPlz@#w#% z %*%w*UvP*,dy ,1}137|79{)z\/x@ n%xP nlwo;wpy/Hy0~v=x=wT=?w0CEvCH}}HL~|LQ}{Qz\QSWyW\By\axac[vchwhmwmnr5vrm}(rw[|wx|Z{|~zyvu oykxDx wv /v]}K|J{szh@x #ow? oyp@y8AvJ oc}] oQ|k oP{n oyz oy oax o%v oS} ow ov oA| o{0[xwLz vv0M};| :{czyxKxwa| v`{ vG}5|Qx1o4{]zL%y yqx xEx(wwv0v}4 | { w8.o {6zvf&oyxx ew %v%*}*,w ,1|137{79=z=?CzCwyCHxHJNxNNwNSvSX}X|X]{]bzbcgygi`ZDqVVT_d"Q+Xl }x R;"a5"w m<"|T !g]t |G|$9 `Y, qn[2 "]7"\k<"g{N(" cT""5"L8"9H"#^Y&ST"* "1"7"hc[!7U!,."b P"P"[!wm!t<0"(";!)4n;Qtix"=\"=XlUjU$!y\!/0t #|08i")j "C}>W "H6rH"L8"Stj^l" gL"9dL"eaL"YT "WsH"\,"ma0"rZ Hs: U"L"#$"("  ] $"c) NP"NO"L"I"5H"F""A"< ""N P"H0 " "CR4" 8"Zp " 7o3 "W "b"  "*"%&"*h"7d"14"XX8 lXD lVX'pW>YX'"pm=!rWU!~U#!|U!M<NO P4Q<OPQRQ4SHQ\TUQVWVWQV W(V,W4V8W@VDWH`XLPT X \ Z[N\](^P_\`haZ b4cOdef4gtexW|TUQW 8iLjhkUjUUHjhUUUP Qd U b O b( UT jt U U U0 Op b U j U U8 jX U U j U UL U Q QQQ4QHQ\QpQQQQQQQQQ(Q<QPQdQxQQQQUUUU8ULUhU|UUUUUU$OlUQQQQ4UHUdUxUUUUU(U<QPQlUO0lPUdQxQQQUO @UTQhQUUUUUUQQQQ4QH\QpQQhQ| QQQQ Q4QL#`Qt&x'QQQ*Q0QHQtQ-QQQQQ$Q,QDQ\Q`Wd0h*l1p1t-x2|3456789:;<=>?@ABCDECFGHI@AJKLMNOP89prstuvXwlt|wSxyyt(t<QHwdxxytQzQ{ T, |L T` |l T | S | } v ~ w !S4!|D!UX!|x!S!|!S!|!t"t"Q,"t8"wL""x"Q#(#z<#Q##x#z#$p$l$V|$$$$$$$$Q %Q%D%V`%Qt%Q|%%w%w%Q&Q8&QD&wH&WT&wX&Wd&wh&Wt&wx&W&w&W&w&W&&W&X&`&`&Y&Y&Y&Y&Y&Y&Y&s 't$'t,'W0'XP'zh'{|'Q's't't((QX(Q\(W`(od(Wh(X4)td)l)p)Wx)|)W)))`)`)s)t)u)M)NT*l*O*P*Q*O8+PL+Q+R+Q+S+Q,<,OH,`,,Q,,O, -@-QT-T--U-Q-Q..Q0.D.VH.Wx.Q.Q.Q.Q.V.W/V/W/Q /V$/W,/V0/W8/VQ>>$>,>4> ?Q0?QT?Qh?Qh@l@t@Q@Q@Q@Q@Q@Q@QAWAQ0AQ4AW8A; cV:pQaR: eQ hipQhe j,Q,S +pSm+ (oS0  @(rpTr htȂd5 T5U 5pUw5 xy܂emU<el |l,V kp8V|k O@VK pXV м`VLg 8V )pV%  $V$ 0pV @8d^VlC] P Z^hW &\ptW"\ pPg|WLf  fW  epWe h3dWLpP[W> l<X[ <pd[< |l[ *p[&  [P)  [ п\ p[X ؿ(\L( P(](( 8'p]' @Ȅ<]0B< PXy<_(u<  <p<_< LD_4 Bx_ p_  _8  _ ~ p_z Tp_ Pp  op_ o ( (3` 3 82p `2 H<W(` WpH`W XL\P`RpT`N h\\` ph` xl0p` 0  /p|a / "*a* @%D)pf%@) '&fm% @*&f$& @,<$pg*8$ H. gdH X1g pg1 p4ȅgh  7h p h7 :ihxh 0=ih gph=g @h C|phCx E hP (Hi 5piH1 0K$$i HNp= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) { return; } int idx = Z * 4; int hot_idx = args.src_tensor.Read(0, 0, 0).x; FLT4 res = INIT_FLT4(args.off_value); if ((hot_idx >= idx) && (hot_idx < (idx + 4))) { res.x = (idx + 0) == hot_idx ? args.on_value : args.off_value; res.y = (idx + 1) == hot_idx ? args.on_value : args.off_value; res.z = (idx + 2) == hot_idx ? 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R0 Q 0S L/ P  R00L/AQ/0H-@P 0HAK-M@I J@UUA`V_  0* *@0CC1V`1Q`!V VQ 0   PY  Y   @ @    IY`   PY`WP`` @G DT@ @ pW KEL-`@WP ЌPp G W C̈́H- H-@ R   HPt *p` HCQ/0H-@PP 1/ 0HAQ/0H-@P 0HAQ/0H-@P 0HAQ/0H-@P 0HAkernel_size_xpadding_xkernel_size_ypadding_ykernel_size_zpadding_zsrc_tensordst_tensor r += args.src_tensor.Read( r += !outside ? args.src_tensor.Read( args.dst_tensor.Write(result, dst_indices FLT4 src = args.src_tensor.Read( args.dst_tensor.Write(maximum, args.dst_indices.Write(indexes, basic_stringx_cy_cd_cMAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int linear_id_1 = GLOBAL_ID_1; int Y = linear_id_1 / args.dst_tensor.Depth(); int D = linear_id_1 % args.dst_tensor.Depth(); int Y = GLOBAL_ID_1; int Z = GLOBAL_ID_2; if (X >= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) { return; } float4 r = INIT_FLOAT4(0.0f); float window_size = 0.0; int xs = X * args.stride_x + args.padding_x; int ys = Y * args.stride_y + args.padding_y; int ds = D * args.stride_z + args.padding_z; for (int kz = 0; kz < args.kernel_size_z; ++kz) { int d_c = ds + kz; if (d_c < 0 || d_c >= args.src_tensor.Depth()) continue; for (int ky = 0; ky < args.kernel_size_y; ++ky) { int y_c = ys + ky; bool outside_y = y_c < 0 || y_c >= args.src_tensor.Height(); for (int kx = 0; kx < args.kernel_size_x; ++kx) { int x_c = xs + kx; bool outside = outside_y || x_c < 0 || x_c >= args.src_tensor.Width(); ); ) : INIT_FLOAT4(0.0f); window_size += !outside ? 1.0 : 0.0; } } } // Depth FLT4 result = TO_FLT4(r / window_size); } vector args.dst_indices.SetBatchRef(B); FLT4 maximum = INIT_FLT4(-10000.0f); args.dst_indices::type indexes = args.dst_indices::zero_value; if (y_c < 0 || y_c >= args.src_tensor.Height()) continue; if (x_c < 0 || x_c >= args.src_tensor.Width()) continue; 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f_coords = args.warp_tensor.Read(X, Y, 0).xy; float2 f_coords_floor = floor(f_coords); int4 st; st.xy = INIT_INT2v2(f_coords_floor.x, f_coords_floor.y); st.zw = st.xy + INIT_INT2v2(1, 1); float2 t = f_coords - f_coords_floor; float4 src0 = args.src_tensor.Read(st.x, st.y, S); float4 src1 = args.src_tensor.Read(st.z, st.y, S); float4 src2 = args.src_tensor.Read(st.x, st.w, S); float4 src3 = args.src_tensor.Read(st.z, st.w, S); bool stx_in = st.x >= 0 && st.x < args.src_tensor.Width(); bool stz_in = st.z >= 0 && st.z < args.src_tensor.Width(); bool sty_in = st.y >= 0 && st.y < args.src_tensor.Height(); bool stw_in = st.w >= 0 && st.w < args.src_tensor.Height(); float4 src0 = (stx_in && sty_in) ? args.src_tensor.Read(st.x, st.y, S) : INIT_FLOAT4(0.0f); float4 src1 = (stz_in && sty_in) ? args.src_tensor.Read(st.z, st.y, S) : INIT_FLOAT4(0.0f); float4 src2 = (stx_in && stw_in) ? args.src_tensor.Read(st.x, st.w, S) : INIT_FLOAT4(0.0f); float4 src3 = (stz_in && stw_in) ? args.src_tensor.Read(st.z, st.w, S) : INIT_FLOAT4(0.0f); FLT4 r0 = TO_FLT4(mix(mix(src0, src1, t.x), mix(src2, src3, t.x), t.y)); args.dst_tensor.Write(r0, X, Y, S); } clang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%k' & & &[''9 '50'e0'#'$'#''s/'QGj'/' '?','0 '<<'x&')'G'i'%IL''''   }\  dB !!#gdo d" )l"L" L"$ L"!G3X4l5t6457(5L8X9t88888888(8<8P8d8x88888::88L8`8t85;<5;<      $(,048<@DHLPTX\`*=** 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@-|Lx @(-p @0-H-;dL @- wP p\  - `->#dl  - p -x-?L ( -0  p< H--@ DL ` -   p --A L*  -!  :p!6 -$2 +23 Lo0p@]Lo-P2reshape.cc.o/ 1749669066 1000 1000 100644 12948 ` ELF(d+4(.H-MP@T `po G  o G   P    /  / " <  ,     i     )  1  1  1  1 "P|   d u T D ! 4 5 $   2  *  /  '  0 P  ,  &  E   p  ` P  @  0     *   PD L  hK D4(tt`P@0 |l\L<, CLL  H-@H WYPU[PUmP P `V Q DPApD1/UP``V Q DPApD1/UP`\P `D L$<80,$   PU Q `V v PPU Q `V v PPD CQ/0H-@PP 1/ 0HAQ/0H-@P 0HAQ/0H-@P 0HAQ/0H-@P 0HAsrc_tensordst_tensorMAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.dst_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int Y = GLOBAL_ID_1; int Z = GLOBAL_ID_2; if (X >= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) { return; } args.src_tensor::scalar_type temps[4]; temps[0] = args.src_tensor::scalar_zero_value; temps[1] = args.src_tensor::scalar_zero_value; temps[2] = args.src_tensor::scalar_zero_value; temps[3] = args.src_tensor::scalar_zero_value; int base = B; int base = 0; base = ((base * args.dst_tensor.Height() + Y) * args.dst_tensor.Width() + X) * args.dst_tensor.Channels() + Z * 4; for (int i = 0; i < 4; ++i) { int dst_channel = Z * 4 + i; if (dst_channel < args.dst_tensor.Channels()) {; int p = base + i; int src_c = p % args.src_tensor.Channels(); p = p / args.src_tensor.Channels(); int src_x = p % args.src_tensor.Width(); p = p / args.src_tensor.Width(); int src_y = p % args.src_tensor.Height(); int src_b = p / args.src_tensor.Height(); args.src_tensor.SetBatchRef(src_b); args.src_tensor.ReadPerChannel(temps[i], src_x, src_y, src_c); } } args.src_tensor::type result; result.x = temps[0]; result.y = temps[1]; result.z = temps[2]; result.w = temps[3]; args.dst_tensor.Write(result, X, Y, Z); } clang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%eSt & &m''`'I'j'j'cx'7~*' 2'2' 2'}>2'?'Vp'v'!'Y)"'-K6''3'+'s0'L(('5P1'-'''OF'#'"''!'H'i`'Bx'+'+'{'A '50'e0'#'   v\  J!!#Bg d" l"aL" L"L"!BTChDEDFGFF(FLF`FtFFFFFFFFF GDFXFlFFFFFFFF FG4FHF\FpFFFFFFFFF(DdDlHpItx|      !"#$%&'()* 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X4 @-tP,p @`-p| @h--HdL x- w p  - -Kl ( -h {ptw H--L[|Lf ` -Q u pq -0-M L  -~ (  p4  -H-N< L  -! p ! -$2 2 Lo0p@WLo-` Areshapex4.cc.o/ 1749669066 1000 1000 100644 11428 ` ELF(t%4(.H-MP@ `po G  o G |  P    / t / d"        i    !P   t y d 4 T 4 D 3 4 3 $ 4 P  4  &  L  *   PD L  hK pp`P@0 p\CLL  H-@H WYPU[PUmP P `V Q DPApD1/UP``V Q DPApD1/UP`\P `D L$<80,$   PU Q `V v PPU Q `V v PPD CQ/0H-@PP 1/ 0HAQ/0H-@P 0HAQ/0H-@P 0HAQ/0H-@P 0HAsrc_tensordst_tensorMAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.dst_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int Y = GLOBAL_ID_1; int Z = GLOBAL_ID_2; if (X >= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) { return; } int dst_bhwc4 = B; int dst_bhwc4 = 0; dst_bhwc4 = ((dst_bhwc4 * args.dst_tensor.Height() + Y) * args.dst_tensor.Width() + X) * args.dst_tensor.Slices() + Z; int src_z = dst_bhwc4 % args.src_tensor.Slices(); dst_bhwc4 = dst_bhwc4 / args.src_tensor.Slices(); int src_x = dst_bhwc4 % args.src_tensor.Width(); dst_bhwc4 = dst_bhwc4 / args.src_tensor.Width(); int src_y = dst_bhwc4 % args.src_tensor.Height(); int src_b = dst_bhwc4 / args.src_tensor.Height(); args.src_tensor.SetBatchRef(src_b); args.src_tensor::type result = args.src_tensor.Read(src_x, src_y, src_z); args.dst_tensor.Write(result, X, Y, Z); } clang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%eh4 &_ & 'c'P''Uj'%j'x''~'z'{$5'YY5'F4'4'K5'+5'`''M'+'' '50'e0'#'  / \  !!#Fi d" |l"eL" L"L"!42T3h4546766(6L6`6t66667666606D6X6d7666664$4,80948<@D H L P T 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0HAsrc_tensordst_tensorscale_factor_xscale_factor_yscale_factor_zMAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); int X = GLOBAL_ID_0; int Y = GLOBAL_ID_1; int Z = GLOBAL_ID_2; if (X >= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || Z >= args.dst_tensor.Slices()) return; float f_coords_x = (INIT_FLOAT(X) + 0.5f) * args.scale_factor_x; float f_coords_y = (INIT_FLOAT(Y) + 0.5f) * args.scale_factor_y; float f_coords_x = INIT_FLOAT(X) * args.scale_factor_x; float f_coords_y = INIT_FLOAT(Y) * args.scale_factor_y; FLT4 r0; f_coords_x += 0.5f; f_coords_y += 0.5f; args.src_tensor.ReadNearest(r0, f_coords_x, f_coords_y, Z); f_coords_x -= 0.5f; f_coords_y -= 0.5f; args.src_tensor.ReadBilinear(r0, f_coords_x, f_coords_y, Z); args.dst_tensor.Write(r0, X, Y, Z); } int linear_id_z = GLOBAL_ID_2; int S = linear_id_z % 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O,4'| @A C' @dLC p) @|L0C7CY)d$ LC O\, ph,  DMC 7Cp, \MCp, lMC7C,L |M8C,  MCp, MC7C-$ MCQp$-M MC7Cz,- M(C Ap<. = NC"8C D.l $N C% . {p.%w DNC(8C[.Lf \N C+Q/ up/+q |NC.48C$/L N C1~p/ p|/1 NC4L8C /L N C7 /  p/7 NC:2/g2O0Lo=70=7'S7pS7@WLoOCd8P psoftmax1x1.cc.o/1749669068 1000 1000 100644 38788 ` ELF(4(lH-M`P@P P |Pp{PpTX  ?CCW pPPpWPp PD L  KK-0M@ `Pp o E+   (t  o +E   ( mQ _`s[F!P'   ( !P _ '   ( !P _ '   ( !P _'    ( P t d/ T/ D, 4"`" t` ` P, @- 0S F  PP& 70`    ``` `(  (0$    <R ,0 7 )   ) # # % 0p    ppp (  (0$    mx Fi u F `% 0 `(0$    ( d H$ 70  ,  ppp (  (0$   xz U N |% l sm@ ` 0 (0$    (   * R ( -  x K( (7 56(  ! -3A@  (7 4 +*   (     (  d l\L<, 8(x`D$xhtp`P@,H- P/L-@L/ O-MMd@SPT X \  SS9  S.h l p pK\K 0JS S= @Sl p pK\K 0;'  SpK ` B\K0/l p pK\K 0&S$p0 pK\K 0h l p pK\K 0h l p pK\K 0l p pK\K 0D@ xd    P`@@pwO* W0 0K, ( P0 ( q,p /00KP  bQPT @  P ``0K p0Kph  K```p[h0l (p dp[0[ \XQ h0[ (\XQx P0K@pK  d A0 , A 4  8 0 K       P  $   x  < h  @ K K   H 诟 H`XH\ ABBV=*AV= CwKtdBKԏ1 H0@K/0  h  KhpK  p[x  K h0[ (pr*@ PL`* `TK  p`@ `  d L`倀[|@@pwK* W0 0K, ( `L`0 q( ,p p   iF0KpT x 0K,  h  Kp[h0l (0 dp[0[ \P h0[ (\PH@\`H` @Vh`\@h@hl``@  @qPR+*  HAQ:@pP:pXP Q P3p VO`G@    hlpp!p@@@V h  P  T `D`@hl00 p x| l0h0p0x @B @T <P`P:tY ` P `3 p] x |p< ]x0x|`D `P%R |`x``"  R-@ppPu* U1*W@` <` 8` @K3$5P㥠p w  Wj*@ZP` L` H` PKm$@ppo &  P8 @ >>>>??x ?? ? @ ? @ ( B @ p A A HEE FDdFBC C #B#&D&)D),F,/E02E26?6D7@7@8@8A9B: ?;?;h< ?<?=F=E=E=E=F=C=C=C=B>B>B>B>B>A>?>?> C ddPC@0 0`22H-@H WYPU[PUmP P `V Q DPApD1/UP``V Q DPApD1/UP`\P `D L$<80,$   PU Q `V v PPU Q `V v PPD CH- H PQ/0H-@PP 1/ 0HAQ/0H-@P 0HAQ/0H-@P 0HAQ/0H-@P 0HAH- 0H-P@  A 8 ,H- H-    M-@pP`@AS W pV2*V`1pa#V,*p`Xpp   @BV`P pPX  `X  E߄H- H-@ R   HPt *p` HCO-M0X * ppKPJ JJHIUUA`Vc C: :@B!V`1R`!V VX@J JJp0X! p IR* *X2ptqpaI @PH0 @2P1:㢑0pC0`HN!00Ff0Sf0`GGGp`pY  p 2  RX pK FH- src_tensordst_tensormaximum loc_mem[tid] = loc_mem[tid + = max(mask_xmask_ymask_zmask_wMAIN_FUNCTION($0) { int linear_id = GROUP_ID_1; int X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); if (B >= args.dst_tensor.Batch()) return; args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); int X = GROUP_ID_1; int Y = GROUP_ID_2; if (X >= args.dst_tensor.Width()) return; if (Y >= args.dst_tensor.Height()) return; float4 mask = INIT_FLOAT4v4(args.mask_x, args.mask_y, args.mask_z, args.mask_w); float4 maxx4 = INIT_FLOAT4(args.src_tensor.Read(X, Y, 0).x); int tid = LOCAL_ID_0; for (int s = tid; s < args.src_tensor.Slices(); s += ) { float4 mask_a = s == args.src_tensor.Slices() - 1 ? mask : INIT_FLOAT4(1.0f); float4 mask_b = INIT_FLOAT4(1.0f) - mask_a; float4 src = args.src_tensor.Read(X, Y, s); src = src * mask_a + mask_b * src.x; maxx4 = max(maxx4, src); } float maximum = max(maxx4.x, maxx4.y); maximum = max(maximum, maxx4.z); maximum = max(maximum, maxx4.w); __local float loc_mem[]; float sum = 0.0f; float4 mask_temp = s == args.src_tensor.Slices() - 1 ? mask : INIT_FLOAT4(1.0f); float4 src = args.src_tensor.Read(X, Y, s) - INIT_FLOAT4(maximum); sum += dot(mask_temp, exp(src)); sum sum = 1.0f / sum; int dst_s = GLOBAL_ID_0; if (dst_s < args.dst_tensor.Slices()) { float4 src = args.src_tensor.Read(X, Y, dst_s) - INIT_FLOAT4(maximum); FLT4 res = TO_FLT4(exp(src) * sum); args.dst_tensor.Write(res, X, Y, dst_s); } basic_string LOCAL_MEM_BARRIER; ; tid % == 0loc_mem[0]loc_mem[tid] if ( = = loc_mem[0]; vector + N6tflite3gpu10Softmax1x1Eclang version 18.1.8A?aeabi5C2.09 A   "$&  !"#%&'()+,-./12346789:;=>?@BCDEGHIJKMNOPRSTUVXYZ[]^_`b i"!<" L!@ l$ $ U c! cd #d :d= Q-d~.drTd GdGdI"`8d!d,!Sd 1d !8d- Y*ddbd*d$d9"$d!d!1d~ 5d JVdOdR&dd)".d!J+d !uSd )dn .d d1dP0d0dY"-d!#d= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || S >= args.dst_tensor.Slices()) { return; } bool block_is_power_of_2 = (args.block_size & (args.block_size - 1)) == 0; bool src_c_is_power_of_2 = (args.src_tensor.Channels() & (args.src_tensor.Channels() - 1)) == 0; args.src_tensor::scalar_type tmp[4]; tmp[0] = args.src_tensor::scalar_zero_value; tmp[1] = args.src_tensor::scalar_zero_value; tmp[2] = args.src_tensor::scalar_zero_value; tmp[3] = args.src_tensor::scalar_zero_value; int block_exponent = (int)log2((float)args.block_size); for (int i = 0; i < 4; ++i) { int dst_c = 4 * S + i; int block_id = dst_c / args.src_tensor.Channels(); int src_x; int src_y; if (block_is_power_of_2) { src_x = X * args.block_size + (block_id & (args.block_size - 1)); src_y = Y * args.block_size + (block_id >> block_exponent); } else { src_x = X * args.block_size + block_id % args.block_size; src_y = Y * args.block_size + block_id / args.block_size; } int src_c; if (src_c_is_power_of_2) { src_c = (dst_c & (args.src_tensor.Channels() - 1)); src_c = dst_c % args.src_tensor.Channels(); args.src_tensor.ReadPerChannel(tmp[i], src_x, src_y, src_c); } args.src_tensor::type result; result.x = tmp[0]; result.y = tmp[1]; result.z = tmp[2]; result.w = tmp[3]; args.dst_tensor.Write(result, X, Y, S); } FLT tmp[4]; tmp[0] = INIT_FLT(0.0f); tmp[1] = INIT_FLT(0.0f); tmp[2] = INIT_FLT(0.0f); tmp[3] = INIT_FLT(0.0f); int block_x = X % args.block_size; int src_x = X / args.block_size; int block_y = Y % args.block_size; int src_y = Y / args.block_size; int block_id = block_y * args.block_size + block_x; int src_c = block_id * args.dst_tensor.Channels() + dst_c; src_c = min(src_c, args.src_tensor.Channels() - 1); FLT4 result; clang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%$  & &0 &''}'& '#j'']'N'd'S('N{0'0's0' 0';;'v!'S'8'' 'D'K'rE'i'B'B'I'IP' ` ';'z3':B'0'_5!'V'l''?'+''g ''50'e0'#'X#'  9 \  p0 p'0''U#'?'[('u&'5('&'9'f0@'&p9''@0!a!#H&=d" l"EL"r L" L"!,>WXXlYZY[Y(\0]L\`\t\\\\\\\\(\<\P\d\x\\\\\\\\\,\@\T\h\|\\\\\\\\\0\D\X\l\\\\\YY^ _$(,04 8 < @ D HLPTX\`dhlptx| !"#$%!&'()*+,-./0123W@XTYZY[Y\]4\H\\\t\\\\\\\\$\8\L\`\t\\\\\\\ \ \( \< \P \d \x \ \ \ \ \ Y Y( ^, _0 4 8 < @  D  H  L  P  T X <\ =` >d ?h @l p t Ax B| C D E F G & ' H ) * + , - . / 0 1 2 3*`4*`**4* 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[ [  [   x[[[[  p[ 3h[0 `-k Zi [Y qc |S m\F HCV x[C [;J j|= W? ]px[h#[+ C#|) C+ I- O& FTx[L | - 8p \[[| "x[$[ |     x[` p][ZY V  [ x[F A [ \ [[[(+H[ x[![ [ [[ [ [ [ D[P[\[h[x8[<P[ H\[ Th[ `x 8[ 0,[ $@O-YM@K0 Ko 8@KK<0[ < Q1 ,@K⸐KPp` <Dp` AO@V* 0  . KPPP< [ ,[ $<AT*KK $ T a'a A'A( , 6KK  4 ! T a+ A'A8 0 BKKH T<  a'a A 'A@  D NKK TH  a'a A'AL P \K\K@P @P!XP \ T@   W H%dGi'F  Kht K K K0tKB S,tFyKDui#Fs hKptGP e#0 h0p p'K :Kp K8K}Kx 6Kd ` hP  0 phK 0 hK 00`hK 0`@@⼀hK 0@t[P[[[[ Kx K K PrKKKKKK K P 0p 0 0 0`밀 0@t[ PJ[L[N[P[      < P=B@  P`[L@@pw* WIIl[x |[v [t [rsl[ |[ [ [ ,`[(@@ pw* tZ:ZPqp/0P  bQPTO'b @'@ HPK p``ఠ  . K```[0 80 [  Pp[L``@ta* T<<Pqp/ P Q PT @ $,K ``  . K```[0 80 Pq@/0P  bQPVO'b @'@ HPK @@ఠ  . K@@@[0 80 [  ,p[(`` @t* v:Pq@/ P Q PV @ $,K @@  . K@@@[0 80 [  <P  8`[4@@pw* W@ 8`[4@@ pwp* tZ:ZPqp.0P  bQPTO'b @'@ 08K ``ఠ  . K```[0 80 [  8p[4``@t * T==Pqp`/ P Q PT @ 08K ``  . 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L";  $"B  z  A 0"G> "_`"Y"k2d"pW *?&ohx`(x0DXl$t0Hp Lh  h      $ h D ` | <d  8x|  (h8#$`'(<Xt+,P.$@Pd11$88L`t@6P 8 \  6 6!!!!!6 """#l#=p#=#P$l$|$$$%%%&L& '<'`'(((($)`))))*$*8*L*`*x*****++@+++++++ ,,,$,,,4,<,D,L,T,\,d,l,t,|,,,,,,,,,,-X-d----.h.t. 0= 00=00000011811$2822233,3D3X3l3p3t3Dx3E|3F33X4l44444P556p66x7777748888 9(9p9999:,:@:T:l:::::$;;;;<<l<<<(=<===>>,>>>?@?T?h?x???H@@@A$A8AAA BLBTB dBBB,C@CTCC CD,DlDDDDDNDODPEQEpEEEEEF(FT,FUTFtFF@GGGGH\H(I8IpIIII$JpJJJK^K_HKhLblLcLLLMfM_\NNbNc$O(O,Om@OxO= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || S >= args.dst_tensor.Slices()) { return; } int s_x = X * args.stride_x + args.offset_x; int s_y = Y * args.stride_y + args.offset_y; * args.stride_b + args.offset_b; args.src_tensor.SetBatchRef(s_b); int s_z = S + args.offset_z; args.src_tensor::type result = args.src_tensor.Read(s_x, s_y, s_z); args.src_tensor::type result; { (S * 4 + ) * args.stride_z + args.offset_z, args.src_tensor.Channels() - 1); , s_x, s_y, s_ch); } 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Z/W/d0Y1Y13W36W68W9<X<?W?4W@ MAMAdAMBMBhCMDMDNENFWKYKYLWLWLWLWLULSLSLSLRLQLPLOLOLMLMMFyt|x   h     t       FE8 <      l   A F'l\CDŽE߄A ,(CDŽFV@@ X       p    F LL(Id E EEJL FF F h F F F F G H H H H JI$L KKKJtKKKLLLLLLLLL JJJJQ QP!L!#P#&M&)P),M,. Q0P03M36O69M9<N<?L@LDQDNENENENENENEMEMEMEMELEIE FE8 <      l A CppDEE߄C*00dl 4pL-@0P 4 PU $Q `V v  $P pCDŽL-D@8P < <AO-M0X * ppKPJ JJHIUUA`Vc C: :@B!V`1R`!V VX@J JJp0X! p IR* *X2ptqpaI @PH0 @2P1:㢑0pC0`HN!00Ff0Sf0`GGGp`pY  p 2  RX pK FH-@H WYPU[PUmP P `V Q DPApD1/UP``V Q DPApD1/UP`\P `D L$<80,$   PU Q `V v PPU Q `V v PPD CH- H PH- H/ PH- HH- HH- 0H-P@  A 8 ,H- H-    O-M@ ` p `*`8$G A*A8P<`P v  p8<@p= 0 && coord_x < args.src_tensor.Width(); coord_x = clamp(coord_x, 0, args.src_tensor.Width()-1); FLT4 src = args.src_tensor.Read(coord_x, coord_y, S) I[0][] += args.Bt.Read() * src; I[1][ I[2][ I[3][ I[4][ I[5][kernel_global_spaceargs.src_tensor.Read(xcMAIN_FUNCTION($0) { int linear_id = GLOBAL_ID_0; int DST_X = linear_id / args.dst_tensor.Batch(); int B = linear_id % args.dst_tensor.Batch(); args.src_tensor.SetBatchRef(B); args.dst_tensor.SetBatchRef(B); int DST_X = GLOBAL_ID_0; int DST_Y = GLOBAL_ID_1; int DST_Z = GLOBAL_ID_2; if (DST_X >= args.tiles_total || DST_Y >= 6 || DST_Z >= args.dst_tensor.Slices()) { return; } int tile_x = (DST_X % args.tiles_x) * 4; int tile_y = (DST_X / args.tiles_x) * 4; FLT4 I0, I1, I2, I3, I4, I5; FLT bt_ar[6]; FLT4 t0 = args.bt_non_uniform.Read(DST_Y * 2 + 0); FLT4 t1 = args.bt_non_uniform.Read(DST_Y * 2 + 1); DST_Y *= 6; bt_ar[0] = t0.x; bt_ar[1] = t0.y; bt_ar[2] = t0.z; bt_ar[3] = t0.w; bt_ar[4] = t1.x; bt_ar[5] = t1.y; = tile_x + args.padding_x + ; = (xc >= 0 && xc < args.src_tensor.Width()); _x = INIT_FLT(inx); = clamp(xc, 0, args.src_tensor.Width() - 1); { int yc = tile_y + args.padding_y; bool iny = (yc >= 0 && yc < args.src_tensor.Height()); yc = clamp(yc, 0, args.src_tensor.Height() - 1); FLT bt = bt_ar[0] * INIT_FLT(iny); FLT bt = bt_ar[0]; src I = bt * ] * INIT_FLT(iny); ]; I0 = INIT_FLT4(0.0f); I1 = INIT_FLT4(0.0f); I2 = INIT_FLT4(0.0f); I3 = INIT_FLT4(0.0f); I4 = INIT_FLT4(0.0f); I5 = INIT_FLT4(0.0f); for (int y = 0; y < 6; ++y) { int yc = tile_y + args.padding_y + y; FLT bt = bt_ar[y] * INIT_FLT(iny); FLT bt = bt_ar[y]; FLT4 r0 = I0 + args.Bt.Read(2) * I2 + args.Bt.Read(4) * I4; args.dst_tensor.Write(r0, DST_X, DST_Y, DST_Z); DST_Y++; FLT4 r0 = args.Bt.Read(7) * I1 + args.Bt.Read(8) * I2 + args.Bt.Read(9) * I3 + args.Bt.Read(10) * I4; FLT4 r0 = args.Bt.Read(13) * I1 + args.Bt.Read(14) * I2 + args.Bt.Read(15) * I3 + args.Bt.Read(16) * I4; FLT4 r0 = args.Bt.Read(19) * I1 + args.Bt.Read(20) * I2 + args.Bt.Read(21) * I3 + args.Bt.Read(22) * I4; FLT4 r0 = args.Bt.Read(25) * I1 + args.Bt.Read(26) * I2 + args.Bt.Read(27) * I3 + args.Bt.Read(28) * I4; FLT4 r0 = args.Bt.Read(31) * I1 + args.Bt.Read(33) * I3 + I5; } biases int tile_id = linear_id / args.dst_tensor.Batch(); int tile_id = GLOBAL_ID_0; int tile_x = (tile_id % args.tiles_x) * 4; int tile_y = (tile_id / args.tiles_x) * 4 + DST_Y; if (tile_x >= args.dst_tensor.Width() || tile_y >= args.dst_tensor.Height() || DST_Z >= args.dst_tensor.Slices()) { FLT at_ar[6]; FLT4 t00 = args.at_non_uniform.Read(DST_Y * 2 + 0); FLT4 t01 = args.at_non_uniform.Read(DST_Y * 2 + 1); at_ar[0] = t00.x; at_ar[1] = t00.y; at_ar[2] = t00.z; at_ar[3] = t00.w; at_ar[4] = t01.x; at_ar[5] = t01.y; FLT at = at_ar[0]; = at * FLT at = at_ar[ FLT at = at_ar[y]; = args.src_tensor.Read(tile_id, y * 6 + FLT4 t0 = I1 + I2; FLT4 t1 = I3 + I4; FLT4 bias_val = args.biases.Read(DST_Z); FLT4 r0 = I0 + t0 + t1 + bias_val; args.dst_tensor.Write(r0, tile_x, tile_y, DST_Z); tile_x++; FLT4 t2 = I1 - I2; FLT4 t3 = I3 - I4; if (tile_x < args.dst_tensor.Width()) { FLT4 r0 = t2 * args.At.Read(7) + t3 * args.At.Read(9) + bias_val; FLT4 r0 = t0 * args.At.Read(13) + t1 * args.At.Read(15) + bias_val; FLT4 r0 = t2 * args.At.Read(19) + t3 * args.At.Read(21) + I5 + bias_val; basic_string int X = (linear_id / args.dst_tensor.Batch()) * 4; int X = GLOBAL_ID_0 * 4; int Y = GLOBAL_ID_1 * 4; int S = GLOBAL_ID_2; if (X / 4 >= args.tiles_x || Y / 4 >= args.tiles_y) return; FLT4 I[6][6]; for (int y = 0; y < 6; ++y) { for (int x = 0; x < 6; ++x) { I[y][x] = INIT_FLT4(0.0f); } } + args.padding_y; bool in_y = coord_y >= 0 && coord_y < args.src_tensor.Height(); coord_y = clamp(coord_y, 0, args.src_tensor.Height() - 1); { * INIT_FLT(in_y && in_x) * INIT_FLT(in_x) * INIT_FLT(in_y) } int dst_x = Y / 4 * args.tiles_x + X / 4; for (int y = 0; y < 6; ++y) { FLT4 value = I[y][0] + args.Bt.Read(2) * I[y][2] + args.Bt.Read(4) * I[y][4]; args.dst_tensor.Write(value, dst_x, y * 6 + 0, S); value = args.Bt.Read(7) * I[y][1] + args.Bt.Read(8) * I[y][2] + args.Bt.Read(9) * I[y][3] + args.Bt.Read(10) * I[y][4]; args.dst_tensor.Write(value, dst_x, y * 6 + 1, S); value = args.Bt.Read(13) * I[y][1] + args.Bt.Read(14) * I[y][2] + args.Bt.Read(15) * I[y][3] + args.Bt.Read(16) * I[y][4]; args.dst_tensor.Write(value, dst_x, y * 6 + 2, S); value = args.Bt.Read(19) * I[y][1] + args.Bt.Read(20) * I[y][2] + args.Bt.Read(21) * I[y][3] + args.Bt.Read(22) * I[y][4]; args.dst_tensor.Write(value, dst_x, y * 6 + 3, S); value = args.Bt.Read(25) * I[y][1] + args.Bt.Read(26) * I[y][2] + args.Bt.Read(27) * I[y][3] + args.Bt.Read(28) * I[y][4]; args.dst_tensor.Write(value, dst_x, y * 6 + 4, S); value = args.Bt.Read(31) * I[y][1] + args.Bt.Read(33) * I[y][3] + I[y][5]; args.dst_tensor.Write(value, dst_x, y * 6 + 5, S); } } No implementation of perform const expressionNo implementation of perform selectorvector, yc, DST_Z)_x * INIT_FLT(iny) = int Z = GLOBAL_ID_2; int tiles_count_x = (args.dst_tensor.Width() + 3) / 4; int tile_x = (tile_id % tiles_count_x) * 4; int tile_y = (tile_id / tiles_count_x) * 4; if (tile_x >= args.dst_tensor.Width() || tile_y >= args.dst_tensor.Height()) return; FLT4 I[4][6]; for (int y = 0; y < 4; ++y) { for (int x = 0; x < 6; ++x) { I[y][x] = INIT_FLT4(0.0f); } } for (int y = 0; y < 6; ++y) { for (int x = 0; x < 6; ++x) { FLT4 src = args.src_tensor.Read(tile_id, y * 6 + x, Z); I[0][x] += src * args.At.Read(y); I[1][x] += src * args.At.Read(y + 6); I[2][x] += src * args.At.Read(y + 12); I[3][x] += src * args.At.Read(y + 18); } } FLT4 bias_val = args.biases.Read(Z); for (int y = 0; y < 4; ++y) { FLT4 t0 = I[y][1] + I[y][2]; FLT4 t1 = I[y][3] + I[y][4]; if (tile_x < args.dst_tensor.Width() && tile_y + y < args.dst_tensor.Height()) { FLT4 value = I[y][0] + t0 + t1 + bias_val; args.dst_tensor.Write(value, tile_x, tile_y + y, Z); } FLT4 t2 = I[y][1] - I[y][2]; FLT4 t3 = I[y][3] - I[y][4]; if (tile_x + 1 < args.dst_tensor.Width() && tile_y + y < args.dst_tensor.Height()) { FLT4 value = t2 * args.At.Read(7) + t3 * args.At.Read(9) + bias_val; args.dst_tensor.Write(value, tile_x + 1, tile_y + y, Z); } if (tile_x + 2 < args.dst_tensor.Width() && tile_y + y < args.dst_tensor.Height()) { FLT4 value = t0 * args.At.Read(13) + t1 * args.At.Read(15) + bias_val; args.dst_tensor.Write(value, tile_x + 2, tile_y + y, Z); } if (tile_x + 3 < args.dst_tensor.Width() && tile_y + y < args.dst_tensor.Height()) { FLT4 value = t2 * args.At.Read(19) + t3 * args.At.Read(21) + I[y][5] + bias_val; args.dst_tensor.Write(value, tile_x + 3, tile_y + y, Z); } } } N6tflite3gpu15Winograd4x4To36EN6tflite3gpu15Winograd36To4x4EN6tflite3gpu21Winograd4x4To36TileX6EN6tflite3gpu22Winograd36To4x4Tile4x1EN6tflite3gpu19GPUObjectDescriptorEclang version 18.1.8A?aeabi5C2.09 A   "$&  !"#%&'(*+,-/01345689:;=>?@BCDEGHIJKLNOPQSTUVXYZ[\]_`abcefghiklmnpqrsuvwyz{}~W0T3.lC(JUp T R ;Q0 O@ R,TR`KgJ ,J 6eUi0S#aR#VC U_ DQOMN+M8SH&RPK@pJ|PdE|O@VoU,L`S0kRhLKQlONMh IFKp HJ!hV?TV!3U #QS#BR\#XS P ;Pd#O'SO` MpEN'L(hK( J|*L V*T+tS+R.#K P.oO<0N@0L2?K2I3[V 3T5I KS5Q 7P7FOX7M\7L9K9I<:xP4>O|>M>_LAJArI`AVdATLDT SPDQHEVPLENEMEHLHJ H[IxHV|HwTJ/S >JP58IQRJQNJO, ?P N  MN1LQ0MLJQDI aUa: Dd`Ta"MP RaQtcV54(PcNcQOjMdLHdwNL3WKV,)U,S Jdd-Id8RP&6O\6;NL^KJzVTjSUeSTfPeO7RflQg N` PgNhL:SMhL8i5KA IMJ@iItkTkWxkUkAS}TkRHmP Lq+QINnMo~L'Tw K<Kp`JLpI62VO(VTp^UrnP SrZRr QrOdtpNhtLtOx)MJKt7JwVw"UPxULSTx1R{hI P{O{4N{L~UAmT5RRQ`k5PnN9nwMn'LCJXJ(KWKDII V SQK \PuJ8sVTX:IHcSQTPp^O@9UNL S8.K,IKNTVyQRb6OnKT<:SHJ QLPP5OTMP.wLKHN6`M wI\+VL J 7#I 7U IT% R: bQO Pd Ny xR TShS)Q *QtgPد I QS(  OMNL JlaIp VIM }TRQEPhJ"NpM7LJܴV JIUfTRdQh.P|U NpM LJ3IUHYTLRrQPNYM0O N M1 ,K] (UJ 7V SU S OR +Q" GOi IeN NV@  LJL8T@ IUzS BT0 R RN [QP\ N %BM%*K*/J/3I38V8=uU=BSBqRBK G"QGODGIM INNN M NSKSNJ(SXVXLU(XZIZ_S_HR0_aePeO4egk^NkLk*Om.pKp%JpM&uVuyUy}S}RPuOxI -NLEKIaVTlLQSQPLOMLKIBVT(SQ~P#OMeLtU;)#bU:,`,.g'&MpDd<x"Jd"" G8'.&$!%0"X9%*" "B&7x". 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W@ @A8* p @k[$ W @lm[v m0  Ap = ,n [\ Dn  p$ dn[#,# |n m#p<i# n[DDd n: p Do[3 \o p  lo"[4AA |o%@p%@ o'[6}y o*Ep*A o,[7( (p/( o0[,8C C o3`Bp03\B o5[@98 o8mpL8i o:[T:T o=ph=  p?[h p pB{ pBw ,pD[|;Lw pxk> qm[ L! ! qp pp qr[4M~* t*pup* qv[DNpy  qz[TO p}  r~[dG; 7 r.p* 4r[xP Dr@p r[Q r@t$ rp~ r[Ud r 7 p3 s[Th s  !p 2 Tu[ lu0p0 u[W) 8% upP u[ X uq ppm u[5$x$ u 3$p/$  vK2{ @v U2H vR[ !&$& `"2!   `PDW @D@DAD@DP P``W  D@GPD1/T@pW  KT 1/D@EO-M@ ` p `*`8$G A*A8P<`P v  p8<@p= args.dst_tensor.Width() || Y >= args.dst_tensor.Height() || S >= args.dst_tensor.Slices()) return; int4 offset0 = args.offsets.Read(S * 2 + 0, 0); int4 offset1 = args.offsets.Read(S * 2 + 1, 0); ACCUM_FLT4 res = INIT_ACCUM_FLT4(0.0f); FLT4 last_mask; int last_src_ch = (args.src_tensor.Slices() - 1) * 4; last_mask.x = INIT_FLT(1.0f); last_mask.y = last_src_ch + 1 < args.src_tensor.Channels() ? INIT_FLT(1.0f) : INIT_FLT(0.0f); last_mask.z = last_src_ch + 2 < args.src_tensor.Channels() ? INIT_FLT(1.0f) : INIT_FLT(0.0f); last_mask.w = last_src_ch + 3 < args.src_tensor.Channels() ? INIT_FLT(1.0f) : INIT_FLT(0.0f); for (int s = 0; s < args.src_tensor.Slices(); ++s) { FLT4 src = args.src_tensor.Read(X, Y, s); FLT4 w0 = args.weights_tensor.Read(X + offset0.x, Y + offset0.y, s); FLT4 w1 = args.weights_tensor.Read(X + offset0.z, Y + offset0.w, s); FLT4 w2 = args.weights_tensor.Read(X + offset1.x, Y + offset1.y, s); FLT4 w3 = args.weights_tensor.Read(X + offset1.z, Y + offset1.w, s); FLT4 mask = INIT_FLT4(1.0f); if (s == (args.src_tensor.Slices() - 1)) { mask = last_mask; } src *= mask; res.x += dot(src, w0); res.y += dot(src, w1); res.z += dot(src, w2); res.w += dot(src, w3); } FLT4 result = TO_FLT4(res); FusedPointwiseConv not suitable.vectorbasic_string result = result / INIT_FLT(args.src_tensor.Channels()); args.dst_tensor.Write(result, X, Y, S); } No implementation of perform const expressionNo implementation of perform selectorNot valid attributes in slice node.Invalid node.Not correct node type. Expected , received Expected input in a node. 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"  }vEF" r#W*g " L"! y:$"K#6'$(h)x*(+,(8-H,\(.,(/*,(p0*12*13*14*(105@,X1`6p,17,18,19 ,$1,:<,T1\;l,<< <@<t<<<<D<x<<< <<<l<<< <`<<< <` < < < <` < < < <` < = < =                *>**?X(t@AB**CD*EF4G<H@=D`IH`J*>**!K `LD*#>=I.rel.ARM.exidx__cxa_throw_ZdlPv_ZN6tflite3gpu15NewMergeDensifyEv_ZN6tflite3gpu26NewRemoveSingleInputConcatEv_ZN6tflite3gpu24NewMakePaddingFromConcatEv_ZN6tflite3gpu22NewAddQuantAdjustmentsEv_ZN6tflite3gpu36NewMakeFullyConnectedFromConvolutionEv_ZN6tflite3gpu26NewMergeMulWithConvolutionEv_ZN6tflite3gpu26NewMergeAddWithConvolutionEv_ZN6tflite3gpu39NewMergePaddingWithDepthwiseConvolutionEv_ZN6tflite3gpu26NewMergeConvolutionWithMulEv_ZN6tflite3gpu29NewRemoveDegenerateUpsamplingEv_ZN6tflite3gpu26NewMergePaddingWithPoolingEv_ZN6tflite3gpu24NewRemoveIdentityReshapeEv_ZN6tflite3gpu29NewRemoveIdentityStridedSliceEv_ZN6tflite3gpu23NewRemoveSingleInputAddEv_ZN6tflite3gpu26NewMergeConvolutionWithAddEv_ZN6tflite3gpu32NewMergePaddingWithConvolution2DEv_ZNSt12length_errorD1Ev.rel.ARM.exidx.text._ZNKSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE20__throw_length_errorB8ne180100Ev.rel.text._ZNKSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEE20__throw_length_errorB8ne180100Ev.rel.text.comment.linker-options.ARM.attributes.L.str_ZTVSt12length_error_ZTISt12length_error.group__cxa_end_cleanup__cxa_allocate_exception__cxa_free_exceptionstrlen.note.GNU-stack_Znwj.llvm_addrsigmemmovemodel_transformations.cc.rel.ARM.exidx.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEC2B8ne180100ILi0EEEPKc.rel.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEC2B8ne180100ILi0EEEPKc.ARM.extab.text._ZNSt3__112basic_stringIcNS_11char_traitsIcEENS_9allocatorIcEEEC2B8ne180100ILi0EEEPKc_ZNSt11logic_errorC2EPKc.rel.ARM.exidx.text._ZNSt3__120__throw_length_errorB8ne180100EPKc.rel.text._ZNSt3__120__throw_length_errorB8ne180100EPKc.rel.ARM.extab.text._ZNSt3__120__throw_length_errorB8ne180100EPKc.rel.ARM.exidx.text._ZNSt12length_errorC2B8ne180100EPKc.rel.text._ZNSt12length_errorC2B8ne180100EPKc.rel.ARM.extab.strtab.symtab_ZN6tflite3gpu26ApplyCustomTransformationsEPNS0_16ModelTransformerE_ZN6tflite3gpu25ApplyModelTransformationsEPNS0_16ModelTransformerE_ZN6tflite3gpu16ModelTransformer5ApplyERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEPNS0_18NodeTransformationE_ZN6tflite3gpu16ModelTransformer5ApplyERKNSt3__112basic_stringIcNS2_11char_traitsIcEENS2_9allocatorIcEEEEPNS0_22SequenceTransformationE.L.str.9.L.str.8$d.8.rodata.str1.8.L.str.7$a.7.L.str.16.L.str.6$d.6.L.str.15.L.str.5$a.5.L.str.14.L.str.4$d.4GCC_except_table3.L.str.13.L.str.3$a.3.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11.L.str.1$d.1.rodata.str1.1__gxx_personality_v0__aeabi_unwind_cpp_pr0GCC_except_table0.L.str.10$a.0mY 4  @$&b8 0^ @<&ph  @D&`&1p ] T &  p   t& `&A &p, &`$&C4L~ 8& &@p< &`@&F4$0 &p  &' 2 2v)Lo0p@Lo&uT&/2604 1749669076 1000 1000 100644 41996 ` ELF(l4(M-(M   P` p  #  # 0@0 p `P K   M-(M   P` p  #  # 0@0 p `P K   M-(M;   P` p  #  # 0@0 p `P K   L-@ L-@ 8 /L- @L/08  L- @L00H-P@T 00  0 0L<    0  / 8/  L- @L0H-0 @PPU 0\ :  B0 RP@0U?o2T0 o0 0 S/ /L-L@ P P 1/<L-T@ P PL 1/LD/K-MP@ `pPP `c  03/P  0 P P`P/KP U :P @ Pu1* U*`U P p`P`  pp 0  ppp       8 /L- @L/08  L- @L00H-P@T 00  0 0L<    0  / 8/  L- @LH-Mp0P @``V  T:0 `PU 0 R Q K@T H 4004/P @q3K<0 0 S/ /8 /L- @L/08  L- @L00H-P@T 00  0 0L<    0  / 8/  L- @LM-M`Pp 0p@@Tp  S: 0PU P P K     BR  BR P  P KP P  P  P  0 S/ /EDDLEDDLEDDLAAAAA XXh`AAAAE5,48AAA XXh`AC $4AAA XXh`AE  T,X,\\, D P, \ x0 @ d t   t H-@ R   HPt *p` HCH- 0H-P@  A 8 ,H- H- M-@p*P P*pU `p E߄H-`@P0 p ppp CM-P@u* U*pU `p E߄L-@ A $H-    H- HH-    H- pL-`P f@ D eP @`opC $$h,HO-?@ACDEFHIJKMNOPRSTUVWYZ[\^_`abcefghijlmnpqrsuvwxyz7Y5L*,|"@|5 4T?4-d,|48434,,|D4dz33(2,2X 7  S542 {944D2 3k3  3 \D2\2c D 7M5x434X4(\H3\33e300$351~2258|e `7G5( ,h4,-4q313 4 {4 %L3%'+3+-12137y279R3 9>7>.54>C4C D'4 3 v D3 F3( , x2, 2 45hQ) Hs2 6 R (5 ! 0Q0 u48 3@ $!4@ 3` 6a.~d 3d -3p 6|H2H20HMZ2M6 MZ t D5t \4  D4 3 . x3 '3p {4(t H2t 2  T2  0335$664~L 5V4M6|R4RT`2 TY3Y^3^!38^4>3@2`5`e2egb4 gl2lpN2pu6u5uq3'\{3a{2 {w3w|+, |&+~~q"X |@"-~. |V.~H- |,~T7$h" ,rm5|TTTt0u$!4L,0%!;"uL"5k$"N 9x" @">/ ("7$!x"%T"+"1#!# !Q T "CE8"H'!'! $"M bt"R "Y60P"^ x"e"cU%\&!   @lBHp  @Bk8*$h dE  p  E kP* Eupq Ekd*oL) E8e a Ep( Ek*0$  FpT Fk*r\n ,F Gpl C Yp>U ,G@k +N J b L T-+O_HPUW DP SV dPxP P3]hxP |P'QPPdP xP9DTdP hxP-8xP pKP* '% "HKU pK[ dP xP |pP l HP D HKt \ LdH P xx`0  t T  d h X hO-\MP  HBqW: @ BB!R:W ``1 1W@11 NS( pIQ` BB1UppWJp`BIpG0CPEWUJYSZSJX~!R^ ^ Y` BR[ R Rh 4p0 ` ` 0 P$@  0 `!1 T H   p@( 㥀8  0 X`D0@<@4PL(P4 (00,  (  K0  $K R R 0S 0S RK( 0    $ pL-M$P@U  0P KpPU  0P  PPX' Kp8 `  PKp,LK-M@K`PV @OoPBPV@pU A L@U5K(`@,(` `@Q1P`0 < '0P LPK( @ @K, ,  ` 0 L[D0H  0(`@,(` `@P0P`0 < 0P LPK( @ @K, ,  ` 0 L[D0H  L[KDKL[ DxpL-M @R, `PooUbP`RP$:,P`. D @ t@,``K0DK0 [0  6 AR ! CR PP)KpB, ,L,P`*0D @0 @,``K0DK0 [0  [KpKp[ dM-M`@P KpVW0TP-H L `@TPPX0,@P$PKLK,0 `$[0  $[ PK$[ pL-MP@ B(Q)`G Q* 0 SS!` R" R< L!(]>@,ZAYACYCGYG YG]GHYI YJYJYKYLYL`MYM XN8YNXOXOXPXPXPS XSXT0XTXVXV]V XV XWXWXWW]W]W\XX]XZXFCDŽEXCPEPC%4EE@F\ltD <t E1((TELELEA$$4A ,EC/lh3t468:,;P>\h?|DF$GDHdLMNTOL-@ A $H-@P`Q v  ppP C4h<$`hhH-@` EGRoCM-@`P pQ w  ` ``P EDL0|O-dM `@!Ѐ 8@` P,(40 <0`@TPPP(\  X`KFpL-@( 0PU `V `FV P PPU `V `FV P PpCDŽH- H- 0H-P@  A 8 ,H- H- O-,M@Q' ` p@pPU   @p PUK F<844H- 0H-P@  A 8 ,H- H- H-@ R   HPt *p` HCADD requires two input tensors.ADD_N only supports 2 inputs.Expected 2 inputs and 1 output, got: inputs and outputsCould not parse input typeCould not parse output typeIf input and output types have the same element size, they must have the same shapesIf input element size is greater than output element size, require that input rank is one greater than output rankShapes must match in all but last dimLast output dim must be equal to input element size divided by output element sizeIf output element size is greater than input element size, require that output rank is on greater than input rankLast input dim must be equal to output element size divided by input element sizeNot supported Cast case. Input type: and output type: DEPTH_TO_SPACE block_size = 1 is a no-op.DEPTH_TO_SPACE block_size must be > 1.Expected 1 input & output each from Dequantize, got: %d, %dUnsupported dequantization type.Expected 2, but got inputs.Expected 1D, but got D input #0.Expected > 1D, but got D input #1.Expected 1, but got outputs.Expected , but got for output. for output.dim[].Expected int8, int4, or float32, but got for input #1.DynamicUpdateSlice requires 3 inputs.Array to update and updated slice must have the same data type, but got: array to update: , updated slice: Start indices must be 1D, but got: start_indices must be of type int32.Operand and update must have the same number of dimensions, but got: operand: , update: Unsupported FullyConnected weights format: FullyConnected doesn't support more than 2 runtime inputs.FullyConnected doesn't support constant input.Input and output dimensions different and FullyConnected doesn't support keep_num_dims.Op can only handle 1 or 2 operand(s).Only support 1D indices Only accept INT32 indices Expected 20 or 24 input tensors, but node has input(s).Expected 1 output tensor, but node has output(s).Only sigmoid or tanh activation is supported, but node has Only TANH activation is supported. but node has cell_clip is not supported.proj_clip is not supported.MUL requires two input tensors.SLICE requires 3 inputs, but node has SLICE supports for 3 or 4 dimensional tensors only, but node has dimensional tensors.Softmax.beta != 1 is not supported.SPACE_TO_DEPTH block_size = 1 is a no-op.SPACE_TO_DEPTH block_size must be > 1.Slice does not support ellipsis_mask.Slice does not support new_axis_mask.Slice does not support shrink_axis_mask parameter. STRIDED_SLICE requires 4 inputs.STRIDED_SLICE supports for 3 or 4 dimensional tensors only.If half_pixel_centers is True, align_corners must be False.Only Reflective padding is supported for Mirror Pad operation. But node has Invalid paddings tensor dimension: expected 2 dim, got dimInvalid paddings tensor shape: expected 4x2 or 3x2, got xrequires one runtime input, one const input, and one outputOnly support 1D indicesOnly support int32 indicesRequire size(indices) = rank(operand)Only support float inputsInput and output types must matchClamp tensors must all be the same typeMin tensor must be the same shape as the input, or a scalarMax tensor must be the same shape as the input, or a scalarNot supported op vectorDoesn't support broadcasting - input0: [,], input1: []basic_stringUnable to retrieve custom_initial_data.Unable to retrieve builtin_data.Incorrect kernel values: kernel_height = , kernel_width = runtime input tensor(s), but node has runtime input(s). output tensor(s), but node has Expected 1 or 2 input tensor(s), but node has runtime inputs.Expected 1 output tensor(s), but node has runtime outputs.Incorrect dilation values: dilation_height = , dilation_width = TfLiteFusedActivation.kTfLiteActSignBitExpects 2 inputs and 1 outputInput/output must be float type and indices must be constant int32 typeinput.dims.size != 4filter.dims.size != 4output.dims.size != 4input.b != output.bfilter.i != output.coutput.c != input.c * depth_multiplierbias.size != output.cdepth_multiplier != 1 && input.c != 1 const input tensor(s), but node has const input(s).Expects 4 inputs and 1 outputIndices must be int32 type, on/off tensors must be constant, scalar, float type, axis must be -1 or last dimUnspported non-singleton dim at Expected 3 inputs and 1 outputCond must be float or bool type, if, else tensors must be either be same the shape as output or constant, scalar.2-D if tensor only supported if constant.2-D else tensor only supported if constant.Incorrect stride values: stride_height = , stride_width = Requested index goes beyond array size: vs Convolution2DTransposeBiasMaxPoolingWithArgmax2DMaxUnpooling2DResamplerNot supported custom op ADDAVERAGE_POOL_2DCONCATENATIONCONV_2DDEPTHWISE_CONV_2DDEPTH_TO_SPACEDEQUANTIZEEMBEDDING_LOOKUPFLOORFULLY_CONNECTEDHASHTABLE_LOOKUPL2_NORMALIZATIONL2_POOL_2DLOCAL_RESPONSE_NORMALIZATIONLOGISTICLSH_PROJECTIONLSTMMAX_POOL_2DMULRELURELU_N1_TO_1RELU6RESHAPERESIZE_BILINEARRNNSOFTMAXSPACE_TO_DEPTHSVDFTANHCONCAT_EMBEDDINGSSKIP_GRAMCALLCUSTOMEMBEDDING_LOOKUP_SPARSEPADUNIDIRECTIONAL_SEQUENCE_RNNGATHERBATCH_TO_SPACE_NDSPACE_TO_BATCH_NDTRANSPOSEMEANSUBDIVSQUEEZEUNIDIRECTIONAL_SEQUENCE_LSTMSTRIDED_SLICEBIDIRECTIONAL_SEQUENCE_RNNEXPTOPK_V2SPLITLOG_SOFTMAXDELEGATEBIDIRECTIONAL_SEQUENCE_LSTMCASTPRELUMAXIMUMARG_MAXMINIMUMLESSNEGPADV2GREATERGREATER_EQUALLESS_EQUALSELECTSLICESINTRANSPOSE_CONVSPARSE_TO_DENSETILEEXPAND_DIMSEQUALNOT_EQUALLOGSUMSQRTRSQRTSHAPEPOWARG_MINFAKE_QUANTREDUCE_PRODREDUCE_MAXPACKLOGICAL_ORONE_HOTLOGICAL_ANDLOGICAL_NOTUNPACKREDUCE_MINFLOOR_DIVREDUCE_ANYSQUAREZEROS_LIKEFILLFLOOR_MODRANGERESIZE_NEAREST_NEIGHBORLEAKY_RELUSQUARED_DIFFERENCEMIRROR_PADABSSPLIT_VUNIQUECEILREVERSE_V2ADD_NGATHER_NDCOSWHERERANKELUREVERSE_SEQUENCEMATRIX_DIAGQUANTIZEMATRIX_SET_DIAGROUNDHARD_SWISHIFWHILENON_MAX_SUPPRESSION_V4NON_MAX_SUPPRESSION_V5SCATTER_NDSELECT_V2DENSIFYSEGMENT_SUMBATCH_MATMULPLACEHOLDER_FOR_GREATER_OP_CODESCUMSUMCALL_ONCEBROADCAST_TORFFT2DCONV_3DIMAGREALCOMPLEX_ABSHASHTABLEHASHTABLE_FINDHASHTABLE_IMPORTHASHTABLE_SIZEREDUCE_ALLCONV_3D_TRANSPOSEVAR_HANDLEREAD_VARIABLEASSIGN_VARIABLEBROADCAST_ARGSRANDOM_STANDARD_NORMALBUCKETIZERANDOM_UNIFORMMULTINOMIALGELUDYNAMIC_UPDATE_SLICERELU_0_TO_1UNSORTED_SEGMENT_PRODUNSORTED_SEGMENT_MAXUNSORTED_SEGMENT_SUMATAN2UNSORTED_SEGMENT_MINSIGNBITCASTBITWISE_XORRIGHT_SHIFTSTABLEHLO_LOGISTICSTABLEHLO_ADDSTABLEHLO_DIVIDESTABLEHLO_MULTIPLYSTABLEHLO_MAXIMUMSTABLEHLO_RESHAPESTABLEHLO_CLAMPSTABLEHLO_CONCATENATESTABLEHLO_BROADCAST_IN_DIMSTABLEHLO_CONVOLUTIONSTABLEHLO_SLICESTABLEHLO_CUSTOM_CALLSTABLEHLO_REDUCESTABLEHLO_ABSSTABLEHLO_ANDSTABLEHLO_COSINESTABLEHLO_EXPONENTIALSTABLEHLO_FLOORSTABLEHLO_LOGSTABLEHLO_MINIMUMSTABLEHLO_NEGATESTABLEHLO_ORSTABLEHLO_POWERSTABLEHLO_REMAINDERSTABLEHLO_RSQRTSTABLEHLO_SELECTSTABLEHLO_SUBTRACTSTABLEHLO_TANHSTABLEHLO_SCATTERSTABLEHLO_COMPARESTABLEHLO_CONVERTSTABLEHLO_DYNAMIC_SLICESTABLEHLO_DYNAMIC_UPDATE_SLICESTABLEHLO_PADSTABLEHLO_IOTASTABLEHLO_DOT_GENERALSTABLEHLO_REDUCE_WINDOWSTABLEHLO_SORTSTABLEHLO_WHILESTABLEHLO_GATHERSTABLEHLO_TRANSPOSEDILATESTABLEHLO_RNG_BIT_GENERATORREDUCE_WINDOWSTABLEHLO_COMPOSITESTABLEHLO_SHIFT_LEFTSTABLEHLO_CBRTSTABLEHLO_CASE is only supported with constant axes. supports int32 tensor for axes. 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R, R R' P`@! p$@ @ p  0ppp6/(@$X p pW $@ @TP pP(`Pp `$ (0KF0H-+P@@P*eQm@Je!vje@Axe@P@@az*E!l@!XJEjE*E@Q AQ*dQM@d!t*EP0@*!1*@:@*A:P*"*0AO-LMP@  00pX 0P`@@X0`@P0 @p P#@T0K00FPP x`O-LMP@  00pX 0P`@@X0`@P0 @p @T0K00FPP xXO-LMP@  00pX 0P`@@X0`@P0 @p @T0K00FPP xXO-LMP@  P,0p0PY 0`@ @Y0@P> @0p  @T-00PpU 0`@ @U0@P @0p  P#@T0K 000F=\\ ( tO-LMP@  P,00pY 0P`@@Y0@P< @0p  @T+0p0`PV 0@  @V0@P @0p  @T0K 000F=\\ ( lO-LMP@  P,00pY 0P`@@Y0@P< @0p  @T+0p0`PV 0@  @V0@P @0p  @T0K 000F=\\ ( lO-M- M@`T pPPTP O*ipR 00R0Cp Qb,+ P{;Ep0 p@ ` *$lp *Q$k #l(^llXR%~Z|F$DƋX@-@M@͜$DT%EV^F j!jAja\N+nT@ \%PPb(^b\B"n '@l G GG @Qp0@ p `dtypeoutput->typeinput->params.zero_point0output->params.zero_point%s:%d %s was not true.params->output_multiplier_exponent <= 02alpha->typeHaveSameShapes(input, output)Only float32, uint8, int8 and int16 are supported currently, got %s.Only float32, uint8, int8 supported currently, got %s.Only 1D, 2D, 3D and 4D tensors supported for int16 input with int16 output, got %dD.Only float32 and int8 is supported currently, got %s.Only float32, int8 and uint8 supported currently, got %s.vectorCheckedLog2(output->params.scale, &output_scale_log2_rounded)output_scale_log2_rounded-kOutputFractionalBitsOnly float32, uint8, int16 and int8 are supported currently, got %s.output->params.scale == 1. / 256output->params.scale == 1. / 32768output->params.zero_point == 0std::numeric_limits::min()std::numeric_limits::min()NumDimensions(input) >= 1-128%s:%d %s not near %s (%f != %f)output->params.scale1.f / 2561.f / 32768Only uint8_t and int16_t outputs are supported with uint8_t inputs currently, got %s.Only int8_t and int16_t outputs are supported with int8_t inputs currently, got %s.Only float32, uint8_t, Int8_t, Int16_t are supported currently, got %s.16.0 / 256255127Only float32, uint8 and int8 are supported currently, got %s.Only float32 and uint8 and int8 are supported currently, got %s.Only float32, int8, int16 and uint8 is supported currently, got %s.N6tflite13optimized_ops17SoftmaxWorkerTaskEN8gemmlowp4TaskEUI돉$J՜ZءP(߭.s ';DC7 șW αMfU׽n۷-Y|_7Q_6T^U:r/0[Z4e@f0Mi$7I[l} '09AHPW^ekqw|clang version 18.1.8A?aeabi5C2.09 A   "$& !"#$&'()+,-./12345789:;=>?@ACDEFGIJKLMNPQRSTVWXYZ[]^_`acdefghjklmnpqrstuwxyz{}~     !#$%'()*,-./02345789:<=>?@BCDEGHIJLMNOQRSTVWXY[\]^`abcdfghiklmnpqrsuvwxy{|}~     !"#%&'(*+,-./12346789:;=>?@ACDEFGIJKLMNPQRSTVWXY[\]_`abdefghiklmnoprstuvwyz{|}~Y˸J$APjQz| ; ƵZ <# ( D X Ŭ346 B@-RŸ2l=v`E}HhZpl'j7 x<b حAx w T  dVmP%!;!&&&PUL+@+++-ڳ "16D1F13'$"#772X79="=<=? #D'{g:vL'(X'y0\'ͮh'00ll'x'`0|'S'0''I0E' '0CͯCXC޶>ZEINIpIIHIuEKYK'Y' 0P PذXPRVVapV&VΫVXK Xҷ''[P0]]E]]İ]_cc:pccDce e'''1'0jϱjjjj&jF\!6}#lpppĸp:pr r'J'0wwww4wy}}p}}x} ',(0ho$<#pt g ((Ҳ(z((}0[8ѭHp( Z E% d M׶pSlpVTH,(f8(@04(?/pӳ<(5H(p0 ڮhîb bmqy!u>@L(X(F0Xe \(h(0[A l(Lx(0ܴzHձ >|((00ƯxG۫Dp ߷((`0RxѰ (Z(K0ǫp ˷((N0>d_ ((/03@ Iy*ʬ ȱ  ٲcD  3(##'C',,.2227-7<<|<>BBBGGL%LQQRVVh8VW[[ޭ([``m` `}P `bff˲DfgksklpTpquuw{ʭ{i{}FP8_-8p(̳|.Ӯr@ ö l? ^dӯxT1_#ްzx,ԫط `K  ʰS   %%**,s,1ķ1668 8==?C7CEIIKگKPPxPRV,VW[[__`ddf8fkkmȴmrrrtfty#y{*{\ 3 ݬDs4Pt`H/(8+jYv+t-˵0*X,cr<(ldtYW LWX ~U@^% \V6WVav ͊")" }$D "$`"2^$"7= "  `"!۔وT" "g~"Q H "&"!ߏ$"+X6-TV,^P"1yX$";,@"=-`"7$% V#\l"VL'\'Yl'|''~'S"C MP"I'B"P{<"VDi"f,"[ "`U'1T"]|Y7.H"c""u\"{c''HU< "j O"p'?D< "w>|"}w+""$@"'63H""0$"$"&^" ((1R"5~]G"ʑ""-,((A"U%X"T6"<(P"E"Q'"o!"[T"XL(?"4 "("o|"Mq"\(H""w"`y"*w"%Hz"1")|$"l(7P"-"I"PH"C{* "V|(nJ">0"r8"d֞0"k(e9"""y0"5(:"ys"u"L(Kl"*r4"Ut4"-(5gt"-"("Y4A Y ZL"[$"MYH 0"!  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"]D"yl"z###x#`#`#`#`$y<$zl$$$$4%D%P%t%%%%%&&$&\&l&|&&&&&'''''$'('4'<'@'H'nX'rh'ux'x'{'~''''''((((8(H(X("h(.x(7(?(J(T(\(dn*n*n*n* n *(n(*0n0*8n8*@n@*H}H*L* PnP*XnX*`}`*d* hnh*pnp*xnx*}** }** }** ** ** ** ** ** ** }** ** ** ** ** }** ** }** * * n*n* n *(n(*0n0*8n8*@n@*HnH*PnP*XnX*`n`*hnh*pnp*xnx*n*n*n*n*n*n*n*n*n*n*<*d****0*l****8**dpp}*=*@m|Lq\dhpt|`**A*Dhtn*G`l}*I*Lhtn*N\hn*P`l(}*V*Z(4L}*_*a0}*d*g$}*h*kTytz||L\{hlptx|    }** yDz<X ,P\p|  $8@DHL***Tytz||L\{hlptx|    }** yDz8X ,P\p|$<@LP`dlpx|***PypzPd| |8{     $(,048<@DHLP}** yDz8X (P\| (,4<@D***Tytz||{             $ ( , 0 4 8 }**(yTz<0p||\`hltx***Tytz||{             $ ( , 0 4 8 }** yDzPht(4H|(,@DLPX\hptx***Pypz|| 4X{      $(,048<@D}** yDzP|(4|\x  ***\y|z4Ht{<T,D(,048<@ DHLPTX\`dhlptx|}** yDz(<|`|||}**\y|z T{4 $   $(,048<@DHLPTX\`dhlptx|}**  yDz(<|`|||}* *Pypz||{lptx|    }** yDzt ,8|,***Tytz||{\`dhlpt x|   }*#*&$yLz|$4T|| **'**y@y\z d(Dd|08Tt @HPX ``2**/*3y@y\zLh| $4@HP 0P $,48@DH`L2**8*; yHzT\x | E**@*F yHzT\x  | E**K*P 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wp b @ @ @ @+R@PpU PT  0S PRP\ 0wpSP pPP p`0Ps0Up`0Pq QY:P0 C RY !IQKFO-4MP@U P@ (U$ p`pU P $ VX` Pp  PP$ VZ>R> @KPK ` 0 `!0p $`K(KP%  03/P$ p `R $`` Q0`0PK!KOFH-   // Q/ 00R/ //H-   // Q3/ 00R/ /O-0-PpYcP6  ` `Q ^V @Pp wp b @ @ @ @+PR@PpU PT  0wS PRP\ 0wp0SP pPP p`0Ps0PUp`0P0 q QY:P0 C RY !IQKFO-4MP@U P@ (U$ p`pU P $ VX` Pp  PP$ VZ>R> @KPK ` 0 `!0p $`K(KP%  03/P$ p `R $`` Q0`0PK!KOFH-   // Q/ 00R/ //H-   // Q/ 00R/ /O-R> @KPK ` 0 `!0p $`K(KP%  03/P$ p `R $`` Q0`0PK!KOFO-4MP@U P@ (U$ p`pU P $ VX` Pp  PP$ VZ>R> @KPK ` 0 `!0p $`K(KP%  03/P$ p `R $`` Q0`0PK!KOFO-= 0axis_value < NumDimensions(input)%s:%d %s != %s (%d != %d)NumInputs(node)2NumOutputs(node)1NumElements(axis)axis->type == kTfLiteInt32 || axis->type == kTfLiteInt64Unknown index output data type: %dUnknown input type: %d, only float32, int types and bool are supportedNumDimensions(input) >= 1Only float32, uint8, int8, int32 and bool are supported currently, got %s.Only int32 and int64 are supported currently, got 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params.zero_point0rhs_data->params.zero_pointoutput->params.zero_point%s:%d %s was not true.lhs_data->type == kTfLiteFloat32 || lhs_data->type == kTfLiteInt8 || lhs_data->type == kTfLiteInt16rhs_data->type == kTfLiteFloat32 || rhs_data->type == kTfLiteInt8 || rhs_data->type == kTfLiteInt16(lhs_data->type == kTfLiteFloat32 && rhs_data->type == kTfLiteInt8) || lhs_data->type == rhs_data->typeNumDimensions(lhs_data) >= 2NumDimensions(lhs_data) <= 5NumDimensions(rhs_data) >= 2NumDimensions(rhs_data) <= 5rhs_dimaccum_dim_lhsaccum_dim_rhsCan only transpose tensors with float, int8 or int16 type.tensor->quantization.typekTfLiteAffineQuantizationaffine_quantizationaffine_quantization->scalescaling_factor_size >= num_batches_to_quantizeaffine_quantization->scale->sizefilter->dims->data[affine_quantization->quantized_dimension]Currently BatchMatMul doesn't support type: %sCurrently only hybrid, int8 and int16 quantization are supported. /home/kerigan/projects/tflite/build/ruy/ruy/kernel_common.hRUY_CHECKmul_params.multiplier_exponent_perchannel()params->multiplier_fixedpointparams->multiplier_exponent%s:%d: %s condition not satisfied: %s vectorallocation failuregemmlowp error: %s NEON, 4x2, depth 16, accumulating two within signed int16N6tflite16cpu_backend_gemm6detail14CustomGemvTaskIaaiaLNS0_18QuantizationFlavorE1EEEN8gemmlowp4TaskEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_26KernelSideFormatInt8InputsINS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEaaNS_14BitDepthParamsINS_12OperandRangeILin127ELi127EEENSB_ILin128ELi127EEEEELNS_8MapOrderE1ELSF_0ELSF_1ENS_9VectorDupIKiLNS_11VectorShapeE1EEENSG_ISH_LSI_0EEENSt3__15tupleIJNS_23OutputStageBiasAdditionINS_9VectorMapISH_LSI_1EEEEENS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_31OutputStageSaturatingCastToInt8EEEENS_11GemmContextEEEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_26KernelSideFormatInt8InputsINS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEaaNS_14BitDepthParamsINS_12OperandRangeILin127ELi127EEENSB_ILin128ELi127EEEEELNS_8MapOrderE1ELSF_0ELSF_0ENS_9VectorDupIKiLNS_11VectorShapeE0EEENSG_ISH_LSI_1EEENSt3__15tupleIJNS_23OutputStageBiasAdditionINS_9VectorMapISH_LSI_0EEEEENS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_31OutputStageSaturatingCastToInt8EEEENS_11GemmContextEEEN8gemmlowp13DefaultKernelINS_14BitDepthParamsINS_12OperandRangeILin127ELi127EEENS2_ILin128ELi127EEEEEEEN8gemmlowp17DefaultKernelImplILb0ELb0ELb1EEEN8gemmlowp50NEON_32bit_GEMM_Int8Operands_LhsNonzero_Int8InputsEN8gemmlowp39NEON_32bit_GEMM_Int8Operands_LhsNonzeroEN8gemmlowp10KernelBaseEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_26KernelSideFormatInt8InputsINS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEaaNS_14BitDepthParamsINS_12OperandRangeILin127ELi127EEENSB_ILin128ELi127EEEEELNS_8MapOrderE1ELSF_0ELSF_1ENS_9VectorDupIKiLNS_11VectorShapeE1EEENSG_ISH_LSI_0EEENSt3__15tupleIJNS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_31OutputStageSaturatingCastToInt8EEEENS_11GemmContextEEEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_26KernelSideFormatInt8InputsINS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEaaNS_14BitDepthParamsINS_12OperandRangeILin127ELi127EEENSB_ILin128ELi127EEEEELNS_8MapOrderE1ELSF_0ELSF_0ENS_9VectorDupIKiLNS_11VectorShapeE0EEENSG_ISH_LSI_1EEENSt3__15tupleIJNS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_31OutputStageSaturatingCastToInt8EEEENS_11GemmContextEEEclang version 18.1.8A?aeabi5C2.09 A   "$&  !"$%&'()+,-./02345679:;<>?@ACDEFHIJKLMOPQRSTVWXYZ[]^_`abdefghiklmnoprstuvwyz{|}~     !"$%&')*+,-/012356789:<=>@ABCDEGHIJKMNOPQSTUVXYZ[]^_`bcdfghijlmnoqrsuvwxz{|}      !"'(*,./124689;=>@ACEFHIKMOQSUVXY[\^_abdegijlmoqrP(;#,#5Q##e # # #[ # # ###d# zd#N h# F# c#D #t # #f#l#  n    p;#d     @  vX 4 #7 3# M# a# \  |/#] !# =#$N $~ @ $ D $& &p8vx=0$+z+ +O /#-* -A | 0>00$2 2$ 824 4g  9Y9>_>CcCH H HJ  JOd O OU8C#Qj QV VX  X]= ]_  _d dfC fk/km  mr5rCrt5ty y{; { I W     &  p (,  J    j 9''# {<#  #3 ,#} #% #&  : P{ h  d  N# D     ! 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R  P0pR4  PP80K P0K P0K P0K P0K P0K Py0K PrP  P,< (@ 4D 8H<D@@D<H8tP K\ `P@!<1dpt$x@@H<L8PTX048<DH D ` ```h`lP|`D `$`(`,`pPT P \ ` d XhlPppx8@DTXK\ hptx0(4,80< Qd4 0HLPPp`````l|` `$`(`,`KP 5/K0K   P0K P0K P( $! $8@<$ D@cell_clip >= 0params->proj_clip >= 0%s:%d %s != %s (%d != %d)input_to_forget_weights->dims->size2input_to_forget_weights->dims->data[0]n_cellinput_to_forget_weights->dims->data[1]n_input(input_to_forget_weights->type == kTfLiteFloat32) || (input_to_forget_weights->type == kTfLiteInt8) || (input_to_forget_weights->type == kTfLiteUInt8)input_to_input_weights->dims->sizeinput_to_input_weights->dims->data[0]input_to_input_weights->dims->data[1]%s:%d %s != %s (%s != %s)input_to_input_weights->typeinput_to_forget_weights->typeinput_to_cell_weights->dims->sizeinput_to_cell_weights->dims->data[0]input_to_cell_weights->dims->data[1]input_to_cell_weights->typeinput_to_output_weights->dims->sizeinput_to_output_weights->dims->data[0]input_to_output_weights->dims->data[1]input_to_output_weights->typerecurrent_to_input_weights->dims->sizerecurrent_to_input_weights->dims->data[0]recurrent_to_input_weights->dims->data[1]n_outputrecurrent_to_input_weights->typerecurrent_to_forget_weights->dims->sizerecurrent_to_forget_weights->dims->data[0]recurrent_to_forget_weights->dims->data[1]recurrent_to_forget_weights->typerecurrent_to_cell_weights->dims->sizerecurrent_to_cell_weights->dims->data[0]recurrent_to_cell_weights->dims->data[1]recurrent_to_cell_weights->typecifg_weights_all_or_none == truecell_to_input_weights->dims->size1cell_to_input_weights->dims->data[0]cell_to_input_weights->typecell_to_forget_weights->dims->sizecell_to_forget_weights->dims->data[0]cell_to_forget_weights->typecell_to_output_weights->dims->sizecell_to_output_weights->dims->data[0]cell_to_output_weights->typepeephole_weights_all_or_none == trueinput_gate_biasnullptrinput_gate_bias->dims->sizeinput_gate_bias->dims->data[0]input_gate_bias->typekTfLiteFloat32forget_gate_bias->dims->sizeforget_gate_bias->dims->data[0]forget_gate_bias->typecell_gate_bias->dims->sizecell_gate_bias->dims->data[0]cell_gate_bias->typeoutput_gate_bias->dims->sizeoutput_gate_bias->dims->data[0]output_gate_bias->typeprojection_weights->dims->sizeprojection_weights->dims->data[0]projection_weights->dims->data[1]projection_weights->typeprojection_bias->dims->sizeprojection_bias->dims->data[0]projection_bias->typeprojecton_tensors_consistent == truenode->inputs->size48node->outputs->sizeparams->merge_outputs ? 1 : 2input->typeinput->dims->size3fw_input_to_output_weights->dims->sizefw_input_to_output_weights->dims->data[1]bw_input_to_output_weights->dims->sizebw_input_to_output_weights->dims->data[1]bw_input_to_output_weights->typefw_input_to_output_weights->typefw_recurrent_to_output_weights->dims->sizefw_recurrent_to_output_weights->dims->data[0]n_fw_cellfw_recurrent_to_output_weights->typebw_recurrent_to_output_weights->dims->sizebw_recurrent_to_output_weights->dims->data[0]n_bw_cellbw_recurrent_to_output_weights->typeaux_inputs_weights_all_or_none%s aux_input->dims->data[0] didn't equal input->dims->data[0]aux_input->dims->data[1] didn't equal input->dims->data[1]fw_activation_state != nullptrfw_cell_state != nullptrNumElements(fw_activation_state)n_batch * n_fw_outputNumElements(fw_cell_state)n_batch * n_fw_cellfw_aux_input_to_input_weights->dims->data[0]fw_input_to_input_weights->dims->data[0]bw_activation_state != nullptrbw_cell_state != nullptrNumElements(bw_activation_state)n_batch * n_bw_outputNumElements(bw_cell_state)n_batch * n_bw_cellbw_aux_input_to_input_weights->dims->data[0]bw_input_to_input_weights->dims->data[0]Type %s is not currently supported.clang version 18.1.8A?aeabi5C2.09 A   "$&  G `L w U  O %5  ,  $  '   @}' : P B  1 #;  $ & "& H bl "b%s %  %$ I' p'f  '\ **R0 c 9! Z( +v + "V & )L I)r B!Y "  %l  #L ;& aB ~#&8  b ! =B \ r8  .E   X # @ 8 ` w. ""$;    . N D % | @' P'v D+ i . | T+l+  $ } + $.   1 { ' * p. 0D " ' I *$ s ! ! + . '  % 0p 1 1f 1q = + h .:  % # ;1\2^  }  !A m $3 9 !  09 : - ) )| R q  H:` $?<@"A$B <C "$D($,048E<F@DHGL<PTXH\`IdJh"lptxK|<LMJ"N<OPJQ<RSJ"T U0 $(V,0"4W8$<@DHXL<PTXY\0`ZdJh"lptx[(0H$8L`t,""#&'))))*`****D+H+L+`P+a+++d+e , ,$.(.,.h0.i4.J8."<.@.D.H.jL.kP.T.X.l\.`.d.h.ml./// 000p00 0$0q(0,00040r80s<0@0D0tH0L0P0T0up0vt0x0|0w1s111|1111}1~1111s112333 33333 3D3334D4t44455`5555 606|666 7<7L7777,8`8p88 9$9(9,9t99999 :$:(:,:0:4:8:<:@:D:d:t:::;T;;;;<$<<<<$=4====4>D>>> ? pD $00p0P  H0K     P%0H $00p0P  L0K    P @L $00p0P  P0K     PPT K T P  X0     PXZP  T PP  L0     PL  H  HP  D0     YPD<  <@P  80    Pg80  04P Y  ,0   $  PH(p, $00p0P P0 PS$ Pp p0 PS(pp  inputs->size12node->outputs->sizeparams->merge_outputs ? 1 : 2%s:%d %s was not true.aux_inputs_weights_or_none%s:%d %s != %s (%s != %s)input->typekTfLiteFloat32input->dims->size3input->dims->data[2]fw_input_weights->dims->data[1]bw_input_weights->dims->data[1]fw_input_weights->dims->data[0]fw_bias->dims->data[0]bw_input_weights->dims->data[0]bw_bias->dims->data[0]fw_recurrent_weights->dims->data[0]bw_recurrent_weights->dims->data[1]NumDimensions(fw_hidden_state)2fw_hidden_state->dims->data[0]batch_sizefw_hidden_state->dims->data[1]fw_num_unitsNumDimensions(bw_hidden_state)bw_hidden_state->dims->data[0]bw_hidden_state->dims->data[1]bw_num_units%s aux_input->dims->data[0] didn't equal input->dims->data[0]aux_input->dims->data[1] didn't equal input->dims->data[1]fw_aux_input_weights->dims->data[0] didn't equal fw_num_unitsbw_aux_input_weights->dims->data[0] didn't equal bw_num_unitsaux_input->dims->data[2] didn't equal fw_aux_input_weights->dims->data[1]aux_input->dims->data[2] didn't equal bw_aux_input_weights->dims->data[1]Lstm_fw_row_sumsLstm_bw_row_sumsType not currently supported.clang version 18.1.8A?aeabi5C2.09 A   "$& P_]y13  Z(S:'<Q q  wP )$#$IGfh m F ?(,;g;>>cJ<hJf:(,%%%0d@^k=@FPH\:b DV$ !%8L;>>>>>,>H>d>><?P?d?@@PAtBCBC8BhCBDB<DlBDB(DXBDBC EPAFF G G E GH A A A A(A`AGHHLIPTX\ `dh l p tx |  $ (!,04"8<@D#HLPT$X%\&`'d`Jh&l(p&t)x&|*&+&,-.LLLLdLNN<N N !>L!>l!>!>!>!>!>"?"?0"?D"PX"Pp"E"Q#B #B@#B`#B#B#B#B#B$Rl$K%M%3%69**<*<*<* 9 *$*(<(*0<0*7:= O7:=O6TfLiteIntArrayCopyTfLiteIntArrayEqualsArray.rel.ARM.exidx_ZN6tflite3ops7builtin26bidirectional_sequence_rnn4FreeEP13TfLiteContextPv_ZdlPv_ZN6tflite3ops7builtin35Register_BIDIRECTIONAL_SEQUENCE_RNNEv.rel.textabort.comment.linker-options.ARM.attributes.L.strstderr_ZN6tflite16GetTemporarySafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin35Register_BIDIRECTIONAL_SEQUENCE_RNNEvE1rTfLiteIntArrayEqual.note.GNU-stack_Znwj_ZN6tflite3ops7builtin26bidirectional_sequence_rnn4InitEP13TfLiteContextPKcj_ZN6tflite12GetTemporaryEP13TfLiteContextPK10TfLiteNodei_ZN6tflite9GetOutputEP13TfLiteContextPK10TfLiteNodei_ZN6tflite16GetVariableInputEP13TfLiteContextPK10TfLiteNodei_ZN6tflite22GetOptionalInputTensorEPK13TfLiteContextPK10TfLiteNodei.llvm_addrsigfprintfTfLiteIntArrayCreateTfLiteTypeGetNameTfLiteIntArrayFree_ZN6tflite3ops7builtin26bidirectional_sequence_rnn4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin26bidirectional_sequence_rnn7PrepareEP13TfLiteContextP10TfLiteNodebidirectional_sequence_rnn.cc.ARM.extab.strtab.symtab_ZN6tflite12kernel_utils12RnnBatchStepEPKfPKafS2_S4_fS4_fS2_iiiii21TfLiteFusedActivationPaS6_S6_PfS7_S7_bPiS8_S8_Pb.rel.data_ZN6tflite3ops7builtin26bidirectional_sequence_rnn10EvalHybridEPK12TfLiteTensorS5_S5_S5_S5_S5_S5_S5_S5_S5_S5_PK36TfLiteBidirectionalSequenceRNNParamsPS3_S9_S9_S9_S9_S9_S9_S9_S9_S9_S9_S9_S9_PbSA__ZN6tflite3ops7builtin26bidirectional_sequence_rnn9EvalFloatEPK12TfLiteTensorS5_S5_S5_S5_S5_S5_S5_S5_S5_S5_PK36TfLiteBidirectionalSequenceRNNParamsPS3_S9_S9_S9__ZN6tflite12kernel_utils12RnnBatchStepEPKfS2_S2_S2_S2_S2_iiiii21TfLiteFusedActivationPfS4_.L.str.39.L.str.29.L.str.19.L.str.9.L.str.38.L.str.28.L.str.18.L.str.8.L.str.37.L.str.27.L.str.17.L.str.7$d.7.L.str.36.L.str.26.L.str.16.L.str.6$a.6.L.str.35.L.str.25.L.str.15.L.str.5$d.5.L.str.34.L.str.24.L.str.14.L.str.4$a.4.L.str.33.L.str.23.L.str.13.L.str.3$d.3.L.str.32.L.str.22.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.41.L.str.31.L.str.21.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.40.L.str.30.L.str.20.L.str.10$a.06 4% @1H&2p&8. @X62T&PH+0L @6 Lox+0x+N+p+@Lo6+@7bitcast.cc.o/ 1749669085 1000 1000 100644 3856 ` ELF( 4(K-M`Pp @P K PQPT TpE Q#B*0 D0 R0PK *D !pW PTT E R#)*!!TPPK 0` @0 @906/Kq 0 cQ BT 0p0S gp GY H- M R% 0S# R- 0S+0K P`@P0 p@P0 p@P$ K0@ p` Pp0G0P 0x@t tp` hPp0H0PpP @6/K 03/@Khd`X0H-M0 @PP K0 0 P0 0S  @K0/ECA %s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/bitcast.ccinput->dims->data[dims - 1]output_type_size / input_type_sizeNumInputs(node)1NumOutputs(node)clang version 18.1.8A?aeabi5C2.09 A   "$&vKBLf#&p 0+u|M3_0PpH `ptx |  ** * * ** * TfLiteIntArrayCopymemcpy_ZN6tflite3ops7builtin7bitcast14CalculateShapeEP13TfLiteContextPK12TfLiteTensorS7_PP14TfLiteIntArray.rel.ARM.exidx__aeabi_uidiv_ZN6tflite3ops7builtin16Register_BITCASTEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin16Register_BITCASTEvE1r.note.GNU-stack_ZN6tflite13GetSizeOfTypeEP13TfLiteContext10TfLiteTypePj.llvm_addrsigTfLiteIntArrayCreate_ZN6tflite3ops7builtin7bitcast4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin7bitcast7PrepareEP13TfLiteContextP10TfLiteNodebitcast.cc.ARM.extab.strtab.symtab.rel.data.L.str.6.L.str.5$d.5.L.str.4$a.4.L.str.3$d.3.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0$a.0 {4  @T$px  @XP2`0 @ Lo0p@Lo /3411 1749669086 1000 1000 100644 16952 ` ELF(64(NH- Q/pL- M R 0S R( 0S&0K `@PP 0 P0 P# Kp0d``!`P TA 0/0@ 0<`8!8P ,A 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%s)input1->typeinput2->typeBitwiseXor currently only supports 8-bit/16-bit/32-bit integer/unsigned integer, got %sclang version 18.1.8A?aeabi5C2.09 A   "$&  !"$%&')*+,-.01245679:;<=>@ABCD:8tEPEjEzEs|E:E&E E EhXE |  H C/  $$)4)+!+00440m<=0F949;Z ;@ @B e,<{G h" ")p x" "4"$e "w "k" "0"9E0"@ 6(9|;;<p=>??@8<@DHLP T X \ ` d;;<,CHChCDCCC(EDC`CCF?CC(C\GlCCCHCC(C\IdJlJtJJKJKJKJJJKJKJK JK`L`L `M$`M(`N,`N<-7*7*A**** 7 * *OPQR0RRR J,S4J8K@JDKLJPKXJ\KdJhKpJtK*O**7*8RDRlRxRT7*PQRHRRR8JDSLJPKXJ\KdJhKpJtK|JKJK*O**7*8RDRlRxRT7*!PQRDRRR(J4S<J@KHJLKTJXK`JdKlJpKxJ|K*O*#*%7*'8RDRlRxRT7*)P0P<VHVTRdRRRRRR,RTJ\JhSxJJK*O*.*0R,R<RPR`RtRRRA*2*458: 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W@ XX Yp Z [ 3 = =$ > ? H\ Il I J _ ` a b _ ` c d e ` f g h i `L Kd K K L K K K M MP M\ Mp N O O OtOxPOPOOOPKKK0R8KPKhKMMMMNOOOOPOPOOOP0KHKdKSKKKMM4M@MTNOO O,O0P8O<PHOPOXO\PKKKTKK KPM\MMMNPOXO`OOPOPOOOPKKK<UDK\KtKMMMMNOOOOPOPOO$O(PVWVWKK,KTX\KlKKYOOOOOOPOP OPtV|WVWKKK<ZDKTKhK[OOOOOOPOPOP<KHKXK|\KKKMMMM(NOOOOPOPO OOPDK\KxK^KKK MMHMTMhNOOOl Op Px O| P O O O P K K K(!_0!KH!K`!K!M!M!M!M!N"O"O"O"O"P"O"P"O"O"O#P,#KD#K`#K#`#K#K#K#M$M0$M<$MP$N$O$O%O$%O(%P0%O4%P@%OH%OP%OT%P%K%K%K%a%K&K&KH&MT&M&M&M&Nl'Ot'O|'O'O'P'O'P'O'O'O'P0(V8(Wd(Vl(W(K(K(K(b)K)K$)KL)cT)O\)Od)O)O)O)O)P)O)P)O)P*V *WL*VT*W*K*K*K*d*K*K +K4+e<+OD+OL+Oh+Ox+O+O+P+O+P+O+P+K+K+K(,f0,KH,K`,K,M,M,M,M,N-O-O-O-O-P-O-P-O-O-O-P(.K@.K\.K.g.K.K.K.M.M,/M8/ML/N/O/O0O 0O$0P,0O00P<0OD0OL0OP0P|0K0K0K0h0K0K1KD1MP1M1M1M1N2O2O2O2O2P3O3P3O3O 3O$3P3V3W3V3W4K4K(4KP4iX4Kh4K|4K4j4O4O4O4O4O4O4P4O5P5O 5Pp5Vx5W5V5W5K5K6K86k@6KP6Kd6K6l6O6O6O6O6O6O6P6O6P6O6P 7K87KT7K7m7K7K7K7M7M$8M08MD8N8O8O9O$9O(9P09O49P@9OH9OP9OT9P9K9K9K9n9K:K:KH:MT:M:M:M:NL;OT;O\;O|;O;P;O;P;O;O;O;P;K;K <K8<o@<KX<Kp<K<M<M<M<M<N=O=O=O=O=P=O=P=O=O=O>P,>KD>K`>K>p>K>K>K>M?M0?Mup{<u P@(P[w{Tw (PC#wpl}Cw  PE<P\zOt}N 0PHpO 0lO PJ8NpPH4N PLXPCuxXhkxpOgx PPhP^hKdJ pPS^K,,ZK HPUIpXSI PPWP_B`A `pPZB,B P\EApZAA P^P`55 pPa5,5 XPc[4pĄaW4 `PePaz"̄! ppPhp"P,l" Pj!p|h PlPb^^ pPo^T0^ hPqO]poK] pPsPc`H` (Pvj_pԋvf_ PxPdb܋ca pP{b0b (P}`p܎{` 0P$PescPoc @(Pbp4b hP8Pf@<? xpP@,@ P!?p? PTPg32 pP3x,3 pP72p32 xPpPhR  pPH ,,D PpX  PPi X`RW  pPX40W  PVpdV  PPj\YlLXY  (PXpX  PPkb[Z  pPX[0T[ @!PYpĞY H!PPl\̞T\ X!(P \p  \ !PPmG(XF !pPG,G "PEpآE "PPnH-, "pP>-`,:- "P+p+ "P$Po2:n9 "pP(:,$: #P8pD8 #P@Pp&L& (#pP&Ч,& #PY%pU% #P\PqSlk #pPIlت0El  $Pjpj ($PxPrmLm 8$(Pmp\m `$PPsod o p$pPo80o $PRnphNn $PPt%qpT!q $(PyppIJup  %PPut>̲= 0%pPj>P,f> %P=p|= %PPv+`* %pP+, + (&P)p0) 0&PPw180 @&pP1,|1 &P0p0 &PPx1v &pP't,# 8'Pp @'P,PyuQP P'pPkQ|0gQ 'PPp P 'PHPzRLR '(P Rp R (P \P{TT (pPT0T (PYSp US (PxP|VTV ((PeUphaU (PP}Dp(D (pPD,D @)PoCp kC H)P P~7(>7 X)pP#7,7 )P%6p#6 )P'P$# )pP*$`,$ P*P,,#p*(# X*P.Ped h*pP1weh0se *P3dp1 d *P5PfLf *(P8/fp8+f +P:Ph+h (+pP=h0h +P?wgp=sg +PA,P>jT:j +(PDipTDi +PFax` ]x @+`PH`2jLo0p@0LoH,P@@;/3487 1749669089 1000 1000 100644 6268 ` ELF(4(pL-M R2 0S0 R: 0S8 @`P PB `QGPG `P1!0  P+06/Kp08`4!4P (A 0 0@ 0` ! P A 0!0@@ `5/Kp `0 00&06/Kp P 0KpL/`P xx0xt 0  -0P6/Kp($ lhhdH- `Pp@  Q Q PpWW*P'0Pp RRA*PK@\ 4/FQQ`*a`V b `W0k 1pG0`pWQ5P Q:10CP10R1 :00PAqa0b0S @ A0Q0QQ`*a`V b `R0k 1 B0` RQ Q PH- `Pp@  Q Q PpWW*P'0Pp RRA*PK@` 4/FQQ`*a`V b `W0k 1pG0`pWQ6P Q:1pP10W1 :00PAa!0g0S @A 0Q0QQ`*a`V b `R0k 1 B0` RQ Q TH- `Pp@  Q QPP@P0PP*`'Pp@0PP-*P`7@ 4/`P2qQ *c R b `P+0; @ PV$@`VaQ *c R b `P+0; @ PU 1+S0 QPUp ///CDŽCCCt $%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/complex_support.ccNumInputs(node)1NumOutputs(node)%s:%d %s was not true.input->type == kTfLiteComplex64 || input->type == kTfLiteComplex128%s:%d %s != %s (%s != %s)output->typekTfLiteFloat32kTfLiteFloat64Unsupported input type, Real op only supports complex input, but got: %sUnsupported input type, Imag op only supports complex input, but got: %sUnsupported input type, ComplexAbs op only supports complex input, but got: %sclang version 18.1.8A?aeabi5C2.09 A   "$&$W(Tn~Dxj \G"t1IzIOse0Q A00`0t}St $R0z#H$l%&&'&&(,048<@ DH LP T X \`d h lp$%(&$%H&$%l&,t-"(**(* *(**(** / *(/(*0/0*# )8#<*h#l+#)*+"TfLiteIntArrayCopy.rel.ARM.exidx_ZN6tflite3ops7builtin20Register_COMPLEX_ABSEv_ZN6tflite3ops7builtin13Register_REALEv_ZN6tflite3ops7builtin13Register_IMAGEv.rel.texthypot.comment.linker-options.ARM.attributes.L.str_ZZN6tflite3ops7builtin20Register_COMPLEX_ABSEvE1r_ZZN6tflite3ops7builtin13Register_REALEvE1r_ZZN6tflite3ops7builtin13Register_IMAGEvE1r.note.GNU-stack_ZN6tflite9GetOutputEP13TfLiteContextPK10TfLiteNodei_ZN6tflite8GetInputEPK13TfLiteContextPK10TfLiteNodei.llvm_addrsighypotfTfLiteTypeGetName_ZN6tflite3ops7builtin7complex7EvalAbsEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin7complex8EvalRealEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin7complex8EvalImagEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin7complex7PrepareEP13TfLiteContextP10TfLiteNodecomplex_support.cc.ARM.extab.strtab.symtab.rel.data.L.str.9$d.9.L.str.8$a.8.L.str.7$d.7.L.str.6$a.6.L.str.5$d.5.L.str.4$a.4.L.str.13$d.13.L.str.3$d.3.L.str.12$a.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11$d.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.10$a.10$a.0B\4 @X70p( 8 @!2` Vx R @h0Lo 0 m p @LoJ` #/3509 1749669095 1000 1000 100644 66044 ` ELF(|4(0O-\M@` 0K PP K xpxuX   0(p p0S P(p h00`A P7/KW" @ Y p,`p 0P,Pp WY  pP o 4 Y,p` 0P ,0Sy`Y,0 P,p`Pz}0&p 7/KY$ ,0`(@ p`,0 p` V  P] , 0SPS`!` p@T(@`F0S Vpw^$A@.Wb$0%p %U( P`5P006/K%u` Up00 PpP6/K,0 3/ $ KPY,(Kp` 0P($ $pY`K0$p [$( p40007/K00$0t` $Tp00P p$4P d0`H0 p5/K $`Q  X0101 0R$0K P$P&W; W] ,Pp(0K P{$( @v`0SpW,:`@P2r"0p 0P4/KP p P6pW$P lPh"h2p \b0`H0K $pP $0 3/K$0 3/$0 KP!1p a0`H0P#@1P< 804!p  0 7/P p @p00p `4/,K,,|t$ |l,(($\XTL|xp///F  `  $ O-= 0axis < t0->dims->size || (t0->dims->size == 0 && axis == 0)%s:%d %s != %s (%d != %d)params->activationkTfLiteActNoneinput_type == kTfLiteFloat32 || input_type == kTfLiteUInt8 || input_type == kTfLiteInt8 || input_type == kTfLiteInt16 || input_type == kTfLiteInt32 || input_type == kTfLiteInt64 || input_type == kTfLiteBool || input_type == kTfLiteUInt32t->dims->sizet0->dims->sizet->typeinput_typet->dims->data[axis] >= 0t->dims->data[axis] <= std::numeric_limits::max() - sum_axist->dims->data[d]t0->dims->data[d]%s:%d %s != %s (%s != %s)output->typet->params.scaleoutput->params.scalet->params.zero_pointoutput->params.zero_point0vectorType '%s' is not supported currently.clang version 18.1.8A?aeabi5C2.09 A   "$&  !#$%&')*+,-/012346789;<=>?@BCDEGHIJLMNOQRSTUWXYZ\]^_`acdefghjklmopqrsuvwxyz|}~    !"#$%&8'4?4( C'64R'3i ')3s<'2'l2'2'1'1' 1'3 '3"B'2d'\2u'1'1 '&4 '0'p1'4'4'3'4'4 3  3 232u28 2x12 &'2 1 1 0(404 3 00(##3#%2$ f20 )1)+/1/1416z1616 3';4; 4D;=3 =B3B3 BG2GV2(GL1L1LQW1QSW0W4W\4\^]1^cu3ce0ej3jo2oqu=2uw{3w|1|1>1C204 4D1\322$2b311%1*2044+1V32221110423=3222 1 1 1043732!z2!28!1x!1!#C3 #& ##} d" &x"#!3"! 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->scaleaffine_quantizationaffine_quantization->scale(affine_quantization->scale->size == 1 || affine_quantization->scale->size == channels_out)Conv_hwcn_weightschannels_in != 0affine_quantization->scale->sizefilter->dims->data[affine_quantization->quantized_dimension]Conv_row_sumsnode->inputs->size >= 2vectorType %s not currently supported.batch_size != 0/home/kerigan/projects/tflite/build/ruy/ruy/kernel_common.hRUY_CHECKmul_params.multiplier_exponent_perchannel()params->multiplier_fixedpointparams->multiplier_exponent%s:%d: %s condition not satisfied: %s Group convolution currently not supported for hybrid kernel.allocation failuregemmlowp error: %s NEON, 4x2, depth 16, accumulating two within signed int16Weight type %s (%d) not supported for 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DajApD?j= Lal(Ya1L?,1px?o1 \ap( Za+?$+ lasj+p?sf+ tau( Za? ax9p?x5 az(4Za?5?;5 a} 5p?}5 a(HZai?e ap? a(\Za?0) ̍ax @ p@ ܍a(tZaL @L a0Lp<@,L a(ZaD@pH@  a(ZaZP@V apT@ $a(Za2\@2pl@2 4a(Za)t@${) Da)p@) La(Zaj @f \a p@ da(Za4@4 ta4p@4 |a(Za@p@ a([a!@p@ a([ai@_p@[ a(([ajC@P`Cp8G\C a(8[a@GpDG ̎a(H[a LG ܎apPG a(\[aXG0& auG pG a(t[adMG`M aLpGL $a([aGpG 4a([aG DapG La([aD>G:>pG6> \a([a?*G$;* la)pH) ta([aH a p,H a?8H? @a>INg2O5([aDR([ aDR D La([ aoDRkD d a(\ agWR,cW Pa(\aW SJ(\a(,]aYW/(4] aYDWY ̔aC(@] aNLW,N ܔPaF(L]aNxW9(T]aYW"(\] aQYWMY ,aM(h] a8OW 4O <aP(t]aFW(|]aFW(] aFFWBF TaW(] a+FW'F daZ%Lo X%0 Xc0"X%p"X@V2Lo|a.>]pr/3794 1749669100 1000 1000 100644 6764 ` ELF(4(pL- M R 0S R 0S0K P@P# Kp0`$ğP D 0/0@ 0`$ğP |D 000@@ `5/Kp0S>0SH0 PPJ0P4`QP  RZ 0 P@Q[ X  RT  RP #`3 00F06/Kp@<#`8ßP ,C 040@`#ßP C 050@"`2 00906/Kp"`2 00>06/Kp"`2 00?06/Kp R00S=Q%0" QQ) LH"`@2 00P06/Kp"`1 00M06/Kp!`1 00L06/KpR(P20 P 0Q1`10Q03/Kp `0 00R06/Kp `0 00S06/Kp|xtl,($<88O- MPU! @`pVZP`@!R r ڒg! ᔇ @TK0Ep0?7/K O-Mp@XXP:HQ`P*`Q b `^ 0 qHp`Q\pSpR\b `R`rP@QO 0` @ X4PU   PQO @BQt@DBJ`    PѠPU`  ` V$ ! @Rr VQ L0P !Rr Q0Dp 7/KK0H-M 0 P@P K00 P0 P0@P(`HH| Q K0 K0 2/K0 /CDŽAFF$ h %s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/embedding_lookup.ccNumInputs(node)2NumOutputs(node)1NumDimensions(lookup)lookup->typekTfLiteInt32%s:%d %s was not true.NumDimensions(value) >= 2qparams->scale != nullptrqparams->zero_point != nullptrqparams->zero_point->data[0] == 0value->type == kTfLiteUInt8 || value->type == kTfLiteInt8 || value->type == kTfLiteInt4output->type == kTfLiteFloat32qparams->quantized_dimension == 0qparams->scale->size == row_sizeqparams->zero_point->size == row_sizeEmbedding Lookup: index out of bounds. Got %d, and bounds are [0, %d]Type not currently supported.clang version 18.1.8A?aeabi5C2.09 A   "$&/q, #Uov ^ Fa."PX"l!T &<0F $  g Od Wvkh t )0h@x$ D%h L''p(,(D) $(,048 < @DH L PTX \ `dhlptx|,X- @ 'd ' ( +8 /d "t %***.*.**** . *& 0&0%memcpy.rel.ARM.exidx__aeabi_uidiv_ZN6tflite3ops7builtin25Register_EMBEDDING_LOOKUPEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin25Register_EMBEDDING_LOOKUPEvE1r.note.GNU-stack.llvm_addrsigTfLiteIntArrayCreate_ZN6tflite3ops7builtin16embedding_lookup4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin16embedding_lookup7PrepareEP13TfLiteContextP10TfLiteNodeembedding_lookup.cc.ARM.extab.strtab.symtab.rel.data_ZN6tflite3ops7builtin16embedding_lookup10EvalSimpleEP13TfLiteContextP10TfLiteNodePK12TfLiteTensorS9_PS7__ZN6tflite3ops7builtin16embedding_lookup10EvalHybridEP13TfLiteContextP10TfLiteNodePK12TfLiteTensorS9_PS7_.L.str.19.L.str.9$d.9.L.str.18.L.str.8$a.8.L.str.17.L.str.7$d.7.L.str.16.L.str.6$a.6.L.str.15.L.str.5$d.5.L.str.14.L.str.4$a.4.L.str.13.L.str.3$d.3.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11$d.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.20.L.str.10$a.10$a.0Nsv]4x Y @(C  p ( @`12 b 0^ @`lLo c0 a |p @qLopV &/3817 1749669103 1000 1000 100644 7948 ` ELF(4(/H-(M R 0S R 0S0K @PP# K0@$t` Tp0T0P 0@$t` Tp0U0PpP @6/K0SY0Se0K P0Sg0Ss0 P0Su0S0 P0S0S  p0SpS0 `PP0 `PP`K #s`@Rp0 PpPY0@"r` Rp0Z0P|"r`@Rp0 PpP^0n@"r` xRp0_0P_d`"`r`@TRp0 PpPc0Q4@0"0r` $Rp0d0PB " r`@Rp0 PpPh04!q`@Qp0 PpPi0$!aP A`0l0@ !aP |A`0n0@`@ p5/KPL!pD1 00r07/`KpP`10!  w0P7/KxtphT@LD$ |xtl@<<O-M-`M40K P@`P"80K P<0K P@0K P D0K PH0 P 0KЍHYY*P P!Q 0*`0S b `Y 0; 0I0S<@pPs8G(,@P< W4D@8p<@@ @ qP q X4Q8A< PHD D pP q Z40< 3/P@D 4 4p W$$DP HP$P Z $ ,P8 H4H 0#3P c0`H0 p5/ 044<,Q 8<!(RrY<@4080Aq0CS D0W^P P PI*@*X *B*0jX0$ X  H DH0p<X 8* 0p$!1p pW0 PJ P*QJQ:=J=J>J=    Xt0p!ph 7/TD 2/0KЍ$0 !p 6 D0@ p(0@4p|W@ /o@"Q Q X @  jX0X0KЍ  X|xpd``@PD CKD%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/embedding_lookup_sparse.ccNumInputs(node)5NumOutputs(node)1NumDimensions(ids)ids->typekTfLiteInt32NumDimensions(indices)2indices->typeNumDimensions(shape)shape->typeNumDimensions(weights)weights->typekTfLiteFloat32SizeOfDimension(indices, 0)SizeOfDimension(ids, 0)SizeOfDimension(weights, 0)%s:%d %s was not true.NumDimensions(value) >= 2%s:%d %s != %s (%s != %s)output->typeSizeOfDimension(dense_shape, 0)lookup_rankoutput_shape != nullptr/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/embedding_lookup_sparse.cc Lookup size overflowed./home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/embedding_lookup_sparse.cc Embedding size overflowed.output_ptr != nullptrEmbedding Lookup Sparse: index out of bounds. Got %d, and bounds are [0, %d]clang version 18.1.8A?aeabi5C2.09 A   "$&}6 "04h \ v  g E (      ,     ]  ;$ 2 A ] u "  u   DpDN S  1    w -t  .M qi^ \.(.d...</0 0h l p t x |                      $(, 048< @ l/.....20334D 5 6 6  $  ( %, &0 4  8 '< (@ )D H  L *P +-*1* *!1**! ".rel.ARM.exidx_ZN6tflite3ops7builtin32Register_EMBEDDING_LOOKUP_SPARSEEv.rel.text.commentmemset.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin32Register_EMBEDDING_LOOKUP_SPARSEEvE1r.note.GNU-stack_ZN6tflite24MultiplyAndCheckOverflowEjjPj.llvm_addrsigsqrtfTfLiteIntArrayCreateTfLiteTypeGetName_ZN6tflite3ops7builtin12_GLOBAL__N_14EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin12_GLOBAL__N_17PrepareEP13TfLiteContextP10TfLiteNodeTfLiteTensorReallocembedding_lookup_sparse.cc.ARM.extab.strtab.symtab.rel.data.L.str.29.L.str.19.L.str.9.L.str.28.L.str.18.L.str.8.L.str.27.L.str.17.L.str.7.L.str.26.L.str.16.L.str.6.L.str.25.L.str.15.L.str.5$d.5.L.str.24.L.str.14.L.str.4$a.4.L.str.23.L.str.13.L.str.3$d.3.L.str.22.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.21.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.30.L.str.20.L.str.10$a.0O;O4T K @,p  @@  0 @<2 {eLocU0cayupy@LoLp,exp.cc.o/ 1749669103 1000 1000 100644 5380 ` ELF(4(Q/O-M-M RC 0SA RK 0SI @P` @pPK P *šP`` *  (  v` 0V   0 `KЍO/0@"r` Rp0=0P 0l@h"hr` \Rp0>0PpP @6/`KЍ0S  "@r` Rp0M0P0S @! q` Qp0N0P[ ڶPX !*U "p" QL*;O " .ZL  (?PL*Z  *jp( *  i  z` *  j@ 1   9I I NH H  U    *  pI I NH H  SGFG;|t\XTL//(8WK- `@P R R R`0Q$Qp*P@z `VV*@$ `VV<*@F03/AP_AQP*aPU b `V0[ 1`F0P`VP00Q̠b@P@Qtp@spppGWAQP*aPU b `V0[ 1`F0P`VP00QQAQ *c R b `Q+0; !A 0QPppU PUE%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/exp.ccNumInputs(node)1NumOutputs(node)input->params.zero_point0output->params.zero_pointType %d is currently not supported by Exp.clang version 18.1.8A?aeabi5C2.09 A   "$& W, #H b r t    (40+  8D5/@#VBj ("]8l !"!!! "$"8"P"!"      $ 4D**#** *  *,!#** %%TfLiteIntArrayCopy.rel.ARM.exidx_ZN6tflite3ops7builtin3exp4FreeEP13TfLiteContextPv_ZdlPv_ZN6tflite3ops7builtin12Register_EXPEv_ZN6tflite3ops7builtin16Register_EXP_REFEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZZN6tflite3ops7builtin16Register_EXP_REFEvE1r.group.note.GNU-stack_Znwj_ZN6tflite3ops7builtin3exp4InitEP13TfLiteContextPKcj_ZN6tflite9GetOutputEP13TfLiteContextPK10TfLiteNodei_ZN6tflite8GetInputEPK13TfLiteContextPK10TfLiteNodei.llvm_addrsigexpfroundf.rel.ARM.exidx.text._ZN6tflite3ops7builtin3exp4EvalILNS2_10KernelTypeE0EEE12TfLiteStatusP13TfLiteContextP10TfLiteNode.rel.text._ZN6tflite3ops7builtin3exp4EvalILNS2_10KernelTypeE0EEE12TfLiteStatusP13TfLiteContextP10TfLiteNode.ARM.extab.text._ZN6tflite3ops7builtin3exp4EvalILNS2_10KernelTypeE0EEE12TfLiteStatusP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin3exp7PrepareEP13TfLiteContextP10TfLiteNodeexp.cc.ARM.extab.strtab.symtab.rel.data.L.str.8.L.str.7$d.7.L.str.6$a.6.L.str.5$d.5.L.str.4$a.4.L.str.3$d.3.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0$a.05 \4H @p p|( @ X %d  ` pl   12t`0 @ Lo0p@Lo0  p/3847 1749669104 1000 1000 100644 6256 ` ELF(4(H-(M R 0S R 0S0K @PP( K0`\"\Ÿ@ PR 0J0PP 4/K0 P"Ÿ@  0K0P P4/K0K P0 PP @ a!U0Pxq `p` 5/K0\\# Q!8P4!41p (a0 P`HY07/K p` Pp 0W0Pp 6/K  R  Qu0 KQi KPLH@ `tph($  O-DMYBY,P+ a$p(? c `(K1+Q$ `V(0 0;Y'`p2*2[PE.3;P쒣  !K ! 1 Q 0+W$a! %(Y pI@ `0pWÊᖡ!% `,, 0SSKY0*,Q$(B 0 `P`0Z0`1+S4pPU'i2*2{VG 3V "!!K! 1 Q 0+S$,q!#(Y  I P` RƇOt'v# PLPH H`Dp 0:0`pP:/K<800M-M`Rp BR !p 1 00'07/Kr*@Pp ` RA@0PqappPU US aq`0 KM/88 p00 00(07/K,(( O-LM 0K PP K$0K  P(0K  P$PW(  ^B^, P+ a(+ ` p$`0K`V, p0 0Y'`1 \2*2;U#E!3KU!  + ! 1 R$0;W( b" %^ pN` pWO4#2%`, !"QQ0  P$P $ 0S  K^P0+,Q(F `$ P 0 40Y0 1;R'`PU2*2{VG 3V #1!K! 1 Q$0+S(,Pq!# ^ N pQWOd"'# T`P PLp 0p :0P`8/KD@@</CE߄ F 0F %s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/expand_dims.ccNumInputs(node)2NumOutputs(node)1input->params.scaleoutput->params.scaleinput->params.zero_pointoutput->params.zero_point0NumElements(&axis)%s:%d %s was not true.axis <= input_dims.sizeaxis >= 0clang version 18.1.8A?aeabi5C2.09 A   "$&-Y XyPjz|xj\N@# / s0e W I 0E 0 L! !("l#       H& $L!p"! (H )     $**%*$**%* % * ' 'memcpy.rel.ARM.exidx_ZN6tflite3ops7builtin20Register_EXPAND_DIMSEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin20Register_EXPAND_DIMSEvE1r.note.GNU-stack_ZN6tflite3ops7builtin11expand_dims12_GLOBAL__N_122GetAxisValueFromTensorEP13TfLiteContextRK12TfLiteTensorPi.llvm_addrsigTfLiteIntArrayCreateTfLiteTensorDataFree_ZN6tflite3ops7builtin11expand_dims4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin11expand_dims7PrepareEP13TfLiteContextP10TfLiteNodeTfLiteTensorReallocexpand_dims.cc.ARM.extab.strtab.symtab.rel.data_ZN6tflite3ops7builtin11expand_dims12_GLOBAL__N_115ExpandTensorDimEP13TfLiteContextRK12TfLiteTensoriPS6_.L.str.9$d.9.L.str.8$a.8.L.str.7$d.7.L.str.6$a.6.L.str.5$d.5.L.str.14.L.str.4$a.4.L.str.13.L.str.3$d.3.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.10$a.02J@ F @  p( ( @H`2P 9 0 @YLo P0 I ip @Lo  fake_quant.cc.o/1749669104 1000 1000 100644 4492 ` ELF( 4(pL-M R 0S R 0S R(  2/Kp0` P @ 0+0@ 0` P @ 0,0@@ `5/Kp @P` P 0KpL///CDŽhxK--PM pP` Pp(V  U4 K00K 07 ,`K`(@T (` pPPT( ,4 0 0 ((K( (I `` (,D%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/fake_quant.ccNumInputs(node)1NumOutputs(node)narrow_range FakeQuant is not currently supported at runtime. narrow_range is only meant to be applied to weights, not activationsclang version 18.1.8A?aeabi5C2.09 A   "$& DOiyz{lht+0  uxghvhQT"7##hHxDHLPTX\ `d t** ** 4Th !""4"8#D"L"P#*$** $#TfLiteIntArrayCopy.rel.ARM.exidx_ZNK6tflite12RuntimeShape8FlatSizeEv_ZN6tflite3ops7builtin19Register_FAKE_QUANTEv_ZN6tflite3ops7builtin23Register_FAKE_QUANT_REFEv_ZN6tflite12RuntimeShapeD1Ev.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite14GetTensorShapeEPK12TfLiteTensor_ZZN6tflite3ops7builtin23Register_FAKE_QUANT_REFEvE1r.group__cxa_end_cleanup.note.GNU-stack_ZN6tflite9GetOutputEP13TfLiteContextPK10TfLiteNodei_ZN6tflite8GetInputEPK13TfLiteContextPK10TfLiteNodei_ZNK6tflite12RuntimeShape4DimsEi.llvm_addrsig_ZN6tflite17FakeQuantizeArrayEfffPKfPff.rel.ARM.exidx.text._ZN6tflite3ops7builtin10fake_quant4EvalILNS2_10KernelTypeE0EEE12TfLiteStatusP13TfLiteContextP10TfLiteNode.rel.text._ZN6tflite3ops7builtin10fake_quant4EvalILNS2_10KernelTypeE0EEE12TfLiteStatusP13TfLiteContextP10TfLiteNode.rel.ARM.extab.text._ZN6tflite3ops7builtin10fake_quant4EvalILNS2_10KernelTypeE0EEE12TfLiteStatusP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin10fake_quant7PrepareEP13TfLiteContextP10TfLiteNodefake_quant.cc.ARM.extab.strtab.symtab.rel.data_ZN6tflite22NudgeQuantizationRangeEffiiPfS0_S0_$d.6.L.str.5$a.5.L.str.4$a.4.L.str.3$d.3GCC_except_table2.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.1$d.1.rodata.str1.1__gxx_personality_v0__aeabi_unwind_cpp_pr0$a.04 @p p @8aKT ,A40=  OpdK  2l10- @Lo0zp@Lo%$`fill.cc.o/ 1749669104 1000 1000 100644 8520 ` ELF(4(H-(M R 0S R& 0S$0K @PP0K P( K0"Ÿ@ R 0I0PP 4/K0P"Ÿ@ 0J0P P4/K0SQQB0S hd"dŸ@ XR 0Y0P"PŸ@  0R00 PP @ a!`Pq `0p` 5/Kdd!P\1 00V05/K0\\% P#LPH!D1p 8a0 P`He07/K p` Pp 0b0Pp 6/KP PKP KXTTXTPH840,M-P @R R0` P 01S)JqP00M/ P 0p`pWJq0P`0M/`03/D 03/  03/X8K- MpPppp0`!p@  P``P :qQP`*e`V b `Pk0[ 1@p0PTP`I p @T  P P K H-@M0K P@P K0K PP 0 P P@ P1 (x PPPP P@@ P P:@ 0 C RP !@ P0 3/KPPP P`` P P:!@0M D0SP 0@PPPP P`` P P:!@0 D0SP~ 1@PxPPP P@@ aPPP P`` PU P:!@0M D0SPH 0@PBPPP Ppp P0 @P +A`; ` FQP! Q@ PPKPPP P@@ P K /CE߄ELC    t  t  $  t     `@ L-@ P P A%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/fill.ccNumInputs(node)2NumOutputs(node)1NumDimensions(dims)%s:%d %s was not true.dtype == kTfLiteInt32 || dtype == kTfLiteInt64NumDimensions(value)0output->params.scalevalue->params.scaleoutput->params.zero_pointvalue->params.zero_pointFill only currently supports int8, int16, int32, int64, float32, bool, string for input 1, got %d.Fill only currently supports int32, int64 for input 0, got %d.Fill dimensions must be >= 0 got %dclang version 18.1.8A?aeabi5C2.09 A   "$& \zIKc!s u/pA"<T*T?$`/$   \ UcL  n0|(YL`LZ(<" =@Ba~N L(h()Lp*      4,,-0-TX\/D0\1p223434()(0778H7d7|877 8p 7 7 8 7 7 8H 7d 7| 8 . 7 70 8H 9P :X : : : 4 : 4 : 4 : 4 : 4 : 4 : 4 : 4 " &*5@*5+**+* ***** < *202+**' 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k @ 0  @(Op (K @8` 3"( <  d pp    2x 0 @Lou0p@Lo8'floor.cc.o/ 1749669110 1000 1000 100644 6064 ` ELF(4(pL-M0 P@P Kp0 `PP `VP% P#P3 0 3/Kp P 0 0H+05/Kp0 ` P  0,0PP6/Kp`P\0\\0X  P-06/KpPLHH//CDŽK-@M0K @PP K 0K pP Pp `PPPV @  @V@P@T K Ell`O-dM40K @PP K80K `P4,48P`8PPP, `%@ Y `JY  p @@TV [ [& !PO00K pjbpfWH`VϪCϪcJhvnhaDmhjA P `F@ @P`V,K,,Fll%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/floor.ccNumInputs(node)1NumOutputs(node)%s:%d %s != %s (%s != %s)input->typekTfLiteFloat32clang version 18.1.8A?aeabi5C2.09 A   "$& KBJdtv &0  00B@t+qt(">#m_H"Dd p     !** #*#*DX%p%&&'()) )*) )$**+**DX%p%''(()))*))**+** 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4 @X < pH @ 8@$`(\ ( x,   p   \-z  xp$l 0 p 8 P2` @H Lo0.p@_Loh xfloor_div.cc.o/ 1749669106 1000 1000 100644 16428 ` ELF(|;4(/H- Q/pL- M R 0S R( 0S&0K `@PP 0 P0 P# Kp0`!P A 070@ 0|`x!xP lA 080@@ `5/Kp 0P P70R3 0  P   `P0 0  G0P6/Kp 0P 03/KpPH 5/Kplhd\<pL-M 0 P@`P Kp0 P0 P @Q'0$\@x Kp Kp Kp KpP 5/Kp O-M S p0p0 SJ0@$0SP`)(@o fP `Ѐ0P0PU41+Y'j`2*2;T,呃,3T ᒡ"!!, 含"!+ 1 Q0+S(@Pa!&0S $C PY/!& P T@PQ `P @pTPPT8V8 RR< b <K@P:@Q`0 F0SP 00C``0:<K!pT\ K|0K<@KpX4l L   YhpH )  )!$0  ,`(p`pW, d&(D$ ') (p*p,``V     0 Q0 A  ``@  2/K  P\KU@pp|KTPP<KV\``Z\K|K@ @Z\Z \Ktypeinput2->typeType '%s' is not supported by floor_div.Division by 0clang version 18.1.8A?aeabi5C2.09 A   "$& )  L0 ,< } N h xe zK    )6Ln T H( lp (Pi  # 0   -  y P_ `E D  Ppd p  s d Y   ?  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dims->data[input->dims->size - 1]cols%s:%d %s was not true.node->inputs->size == 2 || node->inputs->size == 3node->outputs->sizeexpected_outputs_countNumDimensions(filter)2NumElements(bias)SizeOfDimension(filter, 0)input->quantization.typekTfLiteAffineQuantizationfilter->quantization.typeaffine_quantizationaffine_quantization->scaleinput->type == kTfLiteInt8 || input->type == kTfLiteInt16(filter->type == kTfLiteInt8 || filter->type == kTfLiteInt4)affine_quantization->scale->sizeper_channel_quantization_sizefilter->dims->data[affine_quantization->quantized_dimension]filter->type == kTfLiteUInt8input->params.zero_point0output->params.zero_pointparams->quantized_bias_type == kTfLiteInt32 || params->quantized_bias_type == kTfLiteInt64(bias == nullptr) || bias->type == params->quantized_bias_type%s:%d %s != %s (%s != %s)input->typekTfLiteUInt8filter->typeoutput->typekTfLiteInt16is_optional_bias_inttruekTfLiteFloat32is_optional_bias_floatinput->type == kTfLiteUInt8 || input->type == kTfLiteInt8 || input->type == kTfLiteInt16output->type == kTfLiteUInt8 || output->type == kTfLiteInt8 || output->type == kTfLiteInt16vectorsparsity != nullptrFC_ledgertensor->quantization.typeparams->activation == kTfLiteActNone || params->activation == kTfLiteActRelu || params->activation == kTfLiteActReluN1To1 || params->activation == kTfLiteActRelu6/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/fully_connected.cc Unsupported filter quantization zero-point value.Unhandled fully-connected weights formatFilter data type %s currently not supported.Unexpected data typefilter->type != kTfLiteInt4Quantized and sparse fully-connected format supports symmetric weight quantization only.Invalid quantized and sparse fully-connected format.Unsupported sparse fully-connected weight format.Quantized FullyConnected expects output data type uint8, int8 or int16Invalid sparse fully-connected format./home/kerigan/projects/tflite/build/ruy/ruy/kernel_common.hRUY_CHECKmul_params.multiplier_exponent_perchannel()params->multiplier_fixedpointparams->multiplier_exponent%s:%d: %s condition not satisfied: %s allocation failuregemmlowp error: %s NEON, 4x2, depth 16, accumulating two within signed 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0S R 0S0K @PP# Kp0|`x"xŸP lB 0!0@ 0T`P"PŸP DB 0"0@@ `5/Kp0S70S@0SJ0 P0 P0 P`P0S=SQK SQH !`1 00906/Kp($!` P A 0'0@` P @ 0(0@` P @ 0)0@ @ ` 050`` P4/KpP 5/Kplhd\D@<4 pL-M0 P@P Kp0 `P 0 P0 P 4P P0 $`6/P0 P ``5/Kp0P0, `$ 6/Kp /CDŽCDŽT %s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/hashtable_find.ccNumInputs(node)3NumOutputs(node)1input_resource_id_tensor->typekTfLiteResourceNumDimensions(input_resource_id_tensor)SizeOfDimension(input_resource_id_tensor, 0)default_value_tensor->typeoutput_tensor->type%s:%d %s was not true.(key_tensor->type == kTfLiteInt64 && output_tensor->type == kTfLiteString) || (key_tensor->type == kTfLiteString && output_tensor->type == kTfLiteInt64)lookup != nullptrclang version 18.1.8A?aeabi5C2.09 A   "$&Smr}ZB90'(-1Eh\T{PcK%0T@T<k#L$@\       $ (,04 8<@DHLPp *** *"* 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hLo@_0@[VxpV@2Lo`  0/3908 1749669111 1000 1000 100644 4412 ` ELF(4(0H- M R 0S R0S 0K @PP" K00TP"PŸ@ DR 0 0PP 4/K0"Ÿ@ R 0!0P 0S20S;0SE0K P0 PQF Q0H RDQ|!Pt1 00605/K0!@ Q 0&0PP @ 0'0 P @ 0(0P P4/K00 R  P 305/K0D@<4pll||pL-M 0 P@P Kp 0 `P0 P 4P P0 $`6/P0 `6/Kp0J0, `$ 6/Kp /ACDŽ$ <%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/hashtable_import.ccNumInputs(node)3NumOutputs(node)0input_resource_id_tensor->typekTfLiteResourceNumDimensions(input_resource_id_tensor)1SizeOfDimension(input_resource_id_tensor, 0)%s:%d %s was not true.(key_tensor->type == kTfLiteInt64 && value_tensor->type == kTfLiteString) || (key_tensor->type == kTfLiteString && value_tensor->type == kTfLiteInt64)HaveSameShapes(key_tensor, value_tensor)lookup != nullptrclang version 18.1.8A?aeabi5C2.09 A   "$&wUeoM5 (-C)[1n$V0+><&H0:$~s$<H8p       @p048H*** *!* .rel.ARM.exidx_ZN6tflite3ops7builtin25Register_HASHTABLE_IMPORTEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin25Register_HASHTABLE_IMPORTEvE1r.note.GNU-stack_ZN6tflite8resource20GetHashtableResourceEPNSt3__113unordered_mapIiNS1_10unique_ptrINS0_12ResourceBaseENS1_14default_deleteIS4_EEEENS1_4hashIiEENS1_8equal_toIiEENS1_9allocatorINS1_4pairIKiS7_EEEEEEi.llvm_addrsig_ZN6tflite3ops7builtin9hashtable19EvalHashtableImportEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin9hashtable22PrepareHashtableImportEP13TfLiteContextP10TfLiteNodehashtable_import.cc.ARM.extab.strtab.symtab.rel.data_ZN6tflite14HaveSameShapesEPK12TfLiteTensorS2_.L.str.9.L.str.8.L.str.7.L.str.6.L.str.5$d.5.L.str.14.L.str.4$a.4.L.str.13.L.str.3$d.3.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.10$a.0 H4LD @` 0p @ @20 @ WLoN0gp@Lo @ /3931 1749669109 1000 1000 100644 6820 ` ELF( 4(/H-(M R 0S R 0S0K @PP# K0@$t` Tp070P 0p@l$lt` `Tp080PpP @6/K0S80SD0K P0SF0SR0 P0ST p `V\Sj Pg#s`@Sp0 PpPJ0<8#8s`@,Sp0 PpP<0 @#s` Rp0=0P"r`@Rp0 PpPA0@"r` Rp0B0P"p2 00F07/Khd"d2P XB0@H05/K0 pPQ0S;`0 pP>p0S;pS  0Q1p10Q03/p0 3/PpK($!$q` Q@0O0pPpP @6/pK `P @`0U0@`@ p5/pKx`\XP,$XTPPO-DM 0K @PP K$0K P(0K P,0K P00 P0Xk p`ppp(Pp1$ (0 @TJ` P$Pp(PW70,P@ @Q Q0C£0B X   R0 C   QP  0   *! P PKTs0P pH 7/KD@@ CF! 8|L-@ P P A%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/hashtable_lookup.ccNumInputs(node)3NumOutputs(node)2NumDimensions(lookup)1lookup->typekTfLiteInt32NumDimensions(key)key->type%s:%d %s was not true.NumDimensions(value) >= 1SizeOfDimension(key, 0)SizeOfDimension(value, 0)NumDimensions(value)hits->typekTfLiteUInt8value->typeoutput->typenum_rows != 0clang version 18.1.8A?aeabi5C2.09 A   "$& ^" 0k:UobJ2   X@(,F[ f s  S;p #  ,Ay<" W% \)()d)`*+*+    $ ( , 04 8 <@D H LPT X \`d h lptx |        **)8)T)-./012 34`4d5l4p5x4|5 "(*,* *** *6707,*$*& 65memcpy.rel.ARM.exidx__aeabi_uidiv_ZdlPv_ZN6tflite3ops7builtin25Register_HASHTABLE_LOOKUPEv.rel.ARM.exidx.text._ZN4mlir3TFL19SimpleDynamicBufferD2Ev.rel.text._ZN4mlir3TFL19SimpleDynamicBufferD2Ev.ARM.extab.text._ZN4mlir3TFL19SimpleDynamicBufferD2Ev.rel.text.commentmemset.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite13DynamicBuffer21WriteToTensorAsVectorEP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin25Register_HASHTABLE_LOOKUPEvE1r.group__cxa_end_cleanup.note.GNU-stack_Znwj_ZN6tflite13DynamicBuffer9AddStringEPKcj.llvm_addrsigTfLiteIntArrayCreate_ZN6tflite3ops7builtin12_GLOBAL__N_14EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin12_GLOBAL__N_17PrepareEP13TfLiteContextP10TfLiteNodehashtable_lookup.cc.rel.ARM.extab.strtab.symtab.rel.data_ZN6tflite13DynamicBuffer9AddStringERKN4mlir3TFL9StringRefE.L.str.19.L.str.9.L.str.18.L.str.8.L.str.17.L.str.7.L.str.16.L.str.6$a.6.L.str.15.L.str.5$d.5.L.str.14.L.str.4$a.4.L.str.13.L.str.3$d.3GCC_except_table2.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.21.L.str.11.L.str.1$d.1.rodata.str1.1__gxx_personality_v0__aeabi_unwind_cpp_pr0.L.str.20.L.str.10$a.0'4 @ H p @h8v<r @P 4 <  P dp\  `  h 0 @2 Lo2  02 iH *pH @Lo '/3954 1749669113 1000 1000 100644 4104 ` ELF( 4(pL-M R 0S R 0S0 `P@P$ Kp0@!P a 00` 0@!P a 0 0`` @5/Kp0S0S/0S90 @P0S;@0 @3/@Kp !P` @ 0%0@@ P6/@Kp@ P ` 0&0`@ P ` 0'0`| Px` l@ 0,0@lhd\H-M 0 `@P K 0 pPPPp 4P 1/K4@00 p( 7/K$ /CDŽC %s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/hashtable_size.ccNumInputs(node)1NumOutputs(node)input_resource_id_tensor->typekTfLiteResourceNumDimensions(input_resource_id_tensor)SizeOfDimension(input_resource_id_tensor, 0)output_tensor->typekTfLiteInt64%s:%d %s was not true.lookup != nullptrclang version 18.1.8A?aeabi5C2.09 A   "$&tuSxm`}RD;2()- ( i5nL[M0|-BXL,Ttx|     ,T*** * * .rel.ARM.exidx_ZN6tflite3ops7builtin23Register_HASHTABLE_SIZEEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin23Register_HASHTABLE_SIZEEvE1r.note.GNU-stack_ZN6tflite8resource20GetHashtableResourceEPNSt3__113unordered_mapIiNS1_10unique_ptrINS0_12ResourceBaseENS1_14default_deleteIS4_EEEENS1_4hashIiEENS1_8equal_toIiEENS1_9allocatorINS1_4pairIKiS7_EEEEEEi.llvm_addrsigTfLiteIntArrayCreate_ZN6tflite3ops7builtin9hashtable17EvalHashtableSizeEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin9hashtable20PrepareHashtableSizeEP13TfLiteContextP10TfLiteNodehashtable_size.cc.ARM.extab.strtab.symtab.rel.data.L.str.9.L.str.8.L.str.7.L.str.6.L.str.5$d.5.L.str.4$a.4.L.str.3$d.3.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.10$a.0 F4B @8 p$ @H @2<^0 @ ULoL0Hep@Lo (if.cc.o/ 1749669114 1000 1000 100644 17440 ` ELF(;4(:L- @  Q/ O-\MP 0K PP K;0*p  7/K P  XYX0P`pBP)9p i0 `HC0 P7/K(1  ,O `$0`8K8` 1Z4p 0S'`0kP 2*2KY43[PĎ&p 4p d' !{ 1 Q$0+S, (`q!'X H0 RaOT#1'00P&J AAR:*A1QF*a0p)@G CBT 4@@* CBTpq A4@Q A@Tp4!,K0, (C0AC1@SQ@,`0P pddN0`'pX GX P`40O0,'p$ 74(,O `$80 P<0Y8 1kR'h2*2[T쑥4!3;T!s&c"{+! 1 Q$0+S,(4Pq!&0X H 0PSOt"#& p & 6 0 D0:/K@pAWL*At 1 `Qcs `$ (0$0(`S0, 3t`(0,`BTT%T5p He0 `HU0 B88%85p ,e0 `HV0@7/K@4@@@7A10 P  EBS+PE 0@ @@BT>* qw ` Qcp` P(0(0 S03wp,(0,` 0Bs#pc P`0-0 p`5/,QH @( KPڔ40 0S `v ,PpPWpsvp``V P,0 @%,P,00P @  400S40 pw 0`S03w0ppW P  , @$T"pP 0`P!QPS00u0rP , pTT8 P0`KppQk p  0P_P 0P ,  !Pr0 0 3/ PP ;9,P (  x TPP HD@8,($O-$M` P K@ @pP wp P PPP0  PP-P)@ pT @T @ T pp 0 T P P  0p @P Q @KP ``Q * p 0QrQsP O-$MP@  @pP w ` ``P0 0S @t p`Wpstp``V`V 0  Pi  0P]PK PC p0  q`@pS sp pR`ct@`p :Pp Rspp p Qspp P JT @TQ @KP K-M `@P q0 P KPQ  P P\PPPKK/AFN    4F<ppx X0F?X`  (4E(@  h |H-`R@ v P ppP C, d8$\ddO-,M `S@ E  CAX>*Pq!r 0p`0Pr W@cq( `$  P pqq( $ $@ P `P $P K S2 P @P PC@U!*pq 0p@ 0RCq@WpsppP 0S@KhPd d@ @pP`00`P P7/K P $XTTDF,O-$M0 @0  A0BS,Qq R9 P APBUg* !pw `@ Qcp `  0T 0#w@ 0 Bq!aP A` 0-0@`5/K`   @ ABZ&* !x p 0 @Q0p00 TPSx0P3/P K FH- 0H-P@  A 8 ,H- O-M` pCpAW*S; C@Y5* p p 0PR@sUPSp PqpPP A1LL L`P @@`0L0@`@ p5/KK@<80F%s:%d %s was not true./home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/if.ccnode->inputs->size > 0%s:%d %s != %s (%d != %d)cond->typekTfLiteBoolNumElements(cond)1op_data->then_subgraph_index < subgraphs->size()op_data->else_subgraph_index < subgraphs->size()num_inputssubgraph->inputs().size()num_outputssubgraph->outputs().size()vector/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/control_flow_common.hsrc_tensor_indices.size()dst_tensor_indices.size()dst_tensor->allocation_typekTfLiteCustomclang version 18.1.8A?aeabi5C2.09 A   "$& !"#$%&()*+-./0$\ U1G1^1Su1# 1 111u11W11 1'11oW11sA 1CM1a ,  1  pe1M1~`02}h1!M!D!# #(( (--o8-(c(@  |" \_MA"U l "9$"\ H"- %t6|L"!_0$"(Wx\=4@tCDDEHFFh@GGGGL H I J4 K @ L                              8 G = N Q R SD T\ G| U @ V< WP O| @ L = NQTTVtW[W[WR,SX@lO@LC P8Z\], *Mh*M*M>**A***** *$*(>(*,*0A0*4=LN`Ot@xL*M**=NX<@HG|YWO@L #$*M* *%FK  A*(_0A*-`a4b<c@LD`dH`e*M*1*4f `gA*6YW8 <@DA*9<?B \ PSPH0 P@   PF30"p  7/KP 5/KapQ0`P apQ0`P! ` p9/KPT 5/0 P0 P@P @P @P `\XP0,( HpL-M`P@pq  0 3/P Kp 0  P`0 ``P ` KpPQJH- !0  R` 0^H 0M-MP@`PQ J 1p0 pW` 0 R 0p! 0KO-MS  `0P `R >V- QO  R/ VpA Pp0#Q: * G*GVp 2@F!@T C Q @B `pR pWQq  `@Q B `VK@@qR  @Y V0  p 0P% R: * C*CP V 0 p  "0F!0S BQR/pL- Pj AQ``Va  P\pL/O-M-`M,0K p@PP (KЍ,00K PPP040K P`P4@8@,P`,`p(P`87/Kl`hP1 PD`@Pe? P \X00/FT8`F` l x4EB   HCDŽE߄CDŽI/0E(\%s:%d %s was not true./home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/irfft2d.ccnum_dims >= 2IsPowerOfTwo(fft_length_data[0])IsPowerOfTwo(fft_length_data[1])%s:%d %s != %s (%d != %d)NumInputs(node)2NumOutputs(node)1NumDimensions(input) >= 2Type '%s' for input is not supported by irfft2.NumDimensions(fft_length)fft_length_shape.Dims(0)Type '%s' for fft_length is not supported by irfft2.Type '%s' for output is not supported by irfft2.num_dims_outputNumDimensions(input)num_dims_output >= 2output_shape.Dims(num_dims_output - 2)fft_length_data[0]output_shape.Dims(num_dims_output - 1)fft_length_data[1]clang version 18.1.8A?aeabi5C2.09 A   "$&~lLcq!~!OJ<.t 0<Vto5X aSx$1W6'jpI'E70 @tMe _#Y0:=+'Yd8` x \`J4tg8+p+,-(.8/./`0lptx| 24++67@ `,*807x98..: :@:T9X;`9d;l9p;x9|;9;9;9;   $=,/..4@@B Dl D D +8 +h , 6L Gx G . .CDD@8BHH99;9 ;9; 9$;,90;P+t+,67 749@8l*F97H7p9t;x| !"# ')*)*)*)* *$*(>(*,*0)0*8>8*<*@)@*H>H*L*P*T*X*\*`)`**<x*<*<135 I135$0  @p 0[VP$ap W P 0   PPnPl p0 000` 0P @0 `@05/S{Gz?hd`\<840|||xx$  H- MS  * *+P* +a   0 00C1quantization.typekTfLiteAffineQuantizationfilter->quantization.type%s:%d %s was not true.affine_quantizationaffine_quantization->scaleinput->type == kTfLiteInt8 || input->type == kTfLiteInt16filter->type == kTfLiteInt8 || filter->type == kTfLiteInt4affine_quantization->scale->sizenum_channelsfilter->dims->data[affine_quantization->quantized_dimension]scale_diff / output_scale <= 0.02input_product_scale >= 0falseInvalid %dD input tensor (must be a 1D tensor).[,] data: {...} dims: }Given shapes, %s and %s, are not broadcastable.Given shapes, %s, %s and %s, are not broadcastable.Invalid tensor index %d (not in [0, %d)) Tensor at index %d was optional but was expected no_integer_overflow_from_quantization{ type: clang version 18.1.8A?aeabi5C2.09 A   "$& c O   *\ 2~ P d" l   H  ^ Pu jG     ? 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cell_clip >= 0params->proj_clip >= 0%s:%d %s != %s (%d != %d)input_to_forget_weights->dims->size2input_to_forget_weights->dims->data[0]n_cellinput_to_forget_weights->dims->data[1]n_input(input_to_forget_weights->type == kTfLiteFloat32) || (input_to_forget_weights->type == kTfLiteUInt8) || (input_to_forget_weights->type == kTfLiteInt8)input_to_input_weights->dims->sizeinput_to_input_weights->dims->data[0]input_to_input_weights->dims->data[1]%s:%d %s != %s (%s != %s)input_to_input_weights->typeinput_to_forget_weights->typeinput_to_cell_weights->dims->sizeinput_to_cell_weights->dims->data[0]input_to_cell_weights->dims->data[1]input_to_cell_weights->typerecurrent_to_input_weights->dims->sizerecurrent_to_input_weights->dims->data[0]recurrent_to_input_weights->dims->data[1]n_outputrecurrent_to_input_weights->typerecurrent_to_forget_weights->dims->sizerecurrent_to_forget_weights->dims->data[0]recurrent_to_forget_weights->dims->data[1]recurrent_to_forget_weights->typerecurrent_to_cell_weights->dims->sizerecurrent_to_cell_weights->dims->data[0]recurrent_to_cell_weights->dims->data[1]recurrent_to_cell_weights->typecifg_weights_all_or_none == truecell_to_input_weights->dims->size1cell_to_input_weights->dims->data[0]cell_to_input_weights->typeis_integer ? kTfLiteInt16 : input_to_forget_weights->typecell_to_forget_weights->dims->sizecell_to_forget_weights->dims->data[0]cell_to_forget_weights->typecell_to_output_weights->dims->sizecell_to_output_weights->dims->data[0]cell_to_output_weights->typepeephole_weights_all_or_none == trueinput_gate_biasnullptrinput_gate_bias->dims->sizeinput_gate_bias->dims->data[0]input_gate_bias->typekTfLiteInt32kTfLiteFloat32forget_gate_bias->dims->sizeforget_gate_bias->dims->data[0]forget_gate_bias->typecell_gate_bias->dims->sizecell_gate_bias->dims->data[0]cell_gate_bias->typeoutput_gate_bias->dims->sizeoutput_gate_bias->dims->data[0]output_gate_bias->typeprojection_weights->dims->sizeprojection_weights->dims->data[0]projection_weights->dims->data[1]projection_weights->typeprojection_bias->dims->sizeprojection_bias->dims->data[0]projection_bias->typeprojection_tensors_consistent == trueinput_layer_norm_coefficientsinput_layer_norm_coefficients != nullptrinput_layer_norm_coefficients->dims->sizeinput_layer_norm_coefficients->dims->data[0]input_layer_norm_coefficients->typekTfLiteInt16forget_layer_norm_coefficients != nullptrforget_layer_norm_coefficients->dims->sizeforget_layer_norm_coefficients->dims->data[0]forget_layer_norm_coefficients->typecell_layer_norm_coefficients != nullptrcell_layer_norm_coefficients->dims->sizecell_layer_norm_coefficients->dims->data[0]cell_layer_norm_coefficients->typeoutput_layer_norm_coefficients != nullptroutput_layer_norm_coefficients->dims->sizeoutput_layer_norm_coefficients->dims->data[0]output_layer_norm_coefficients->typeweight_shape.DimensionsCount()output_state != nullptrnode->outputs->sizeThe LSTM Full kernel expects 20 or 24 inputs. Got %d inputsinput->dims->size > 1input_to_output_weights->dims->sizeinput_to_output_weights->dims->data[1]recurrent_to_output_weights->dims->sizerecurrent_to_output_weights->dims->data[0]cell_state != nullptrNumElements(output_state)n_batch * n_outputNumElements(cell_state)n_batch * n_cellnum_intermediate_tensors == 5 || num_intermediate_tensors == 12Lstm_row_sumsType %d is not currently supported.node->inputs->size == kInputNumnode->outputs->size == kOutputNuminput->dims->sizeprev_activation->dims->sizeprev_activation->dims->data[0]num_batchesweights->dims->sizeweights->dims->data[0]4 * activation_depthweights->dims->data[1]total_depthbias->dims->sizebias->dims->data[0]prev_state->dims->sizeprev_state->dims->data[0]prev_state->dims->data[1]activation_depthThe internal state of a LSTM cell must have a power-of-two scale.The only case of quantized LstmCell currently supported is with StateIntegerBits==4Unsupported combination of data types for LstmCellLstm_ledgerCheckedLog2(cell_state->params.scale, &cell_scale)cell_scale <= -9vectorcell_state_params->scale->data[0]1.0 / 32768/home/kerigan/projects/tflite/build/ruy/ruy/kernel_common.hRUY_CHECKmul_params.multiplier_exponent_perchannel()params->multiplier_fixedpointparams->multiplier_exponent%s:%d: %s condition not satisfied: %s allocation failuregemmlowp error: %s NEON, 4x2, depth 16, accumulating two within signed int16N8gemmlowp4TaskEN6tflite16cpu_backend_gemm6detail14CustomGemvTaskIhhisLNS0_18QuantizationFlavorE1EEEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_20KernelSideFormatInt8INS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEhsNS_14BitDepthParamsINS_12OperandRangeILi1ELi255EEENSB_ILi0ELi255EEEEELNS_8MapOrderE1ELSF_0ELSF_1ENS_9VectorDupIKiLNS_11VectorShapeE1EEENSG_ISH_LSI_0EEENSt3__15tupleIJNS_23OutputStageBiasAdditionINS_9VectorMapISH_LSI_1EEEEENS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_32OutputStageSaturatingCastToInt16EEEENS_11GemmContextEEEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_20KernelSideFormatInt8INS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEhsNS_14BitDepthParamsINS_12OperandRangeILi1ELi255EEENSB_ILi0ELi255EEEEELNS_8MapOrderE1ELSF_0ELSF_0ENS_9VectorDupIKiLNS_11VectorShapeE0EEENSG_ISH_LSI_1EEENSt3__15tupleIJNS_23OutputStageBiasAdditionINS_9VectorMapISH_LSI_0EEEEENS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_32OutputStageSaturatingCastToInt16EEEENS_11GemmContextEEEN8gemmlowp13DefaultKernelINS_14BitDepthParamsINS_12OperandRangeILi1ELi255EEENS2_ILi0ELi255EEEEEEEN8gemmlowp17DefaultKernelImplILb0ELb1ELb1EEEN8gemmlowp39NEON_32bit_GEMM_Int8Operands_LhsNonzeroEN8gemmlowp10KernelBaseEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_20KernelSideFormatInt8INS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEhsNS_14BitDepthParamsINS_12OperandRangeILi1ELi255EEENSB_ILi0ELi255EEEEELNS_8MapOrderE1ELSF_0ELSF_1ENS_9VectorDupIKiLNS_11VectorShapeE1EEENSG_ISH_LSI_0EEENSt3__15tupleIJNS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_32OutputStageSaturatingCastToInt16EEEENS_11GemmContextEEEN8gemmlowp21GemmWithPackedRhsTaskINS_12KernelFormatINS_20KernelSideFormatInt8INS_10CellFormatILi4ELi16ELNS_9CellOrderE1EEELi1EEENS2_INS3_ILi2ELi16ELS4_1EEELi1EEEEEhsNS_14BitDepthParamsINS_12OperandRangeILi1ELi255EEENSB_ILi0ELi255EEEEELNS_8MapOrderE1ELSF_0ELSF_0ENS_9VectorDupIKiLNS_11VectorShapeE0EEENSG_ISH_LSI_1EEENSt3__15tupleIJNS_44OutputStageScaleInt32ByFixedPointAndExponentENS_16OutputStageClampENS_32OutputStageSaturatingCastToInt16EEEENS_11GemmContextEEEclang version 18.1.8A?aeabi5C2.09 A   "$& !"#$&'()+,-.012345789:<=>?ABCDFGHIJKMNOPQRTUVWYZ[\]_`abdefgijklnopqstuvwyz{|~     !"#%&'(*+,-.012356789;<=>@ABCDFGHIKLMOPQRTUVWXZ[\]_`abdefghjklmnpqrstuwxy{|}~    !"#$&'(*+,-/01245679:;<ACDFGIKLNPRSUWXZ[]_`bcegikmnpqstvwyz|~Y*8)t<=/)I='`='&&w=E%#<%=#$="="d![!'= = L'=*#=*\))+='#=Y&&=% &="='c&#1="K=2!h=%#@%=t*%="` =r$=) U(D!Tu==)=K(=& =%=[$=#6"=!X"= z====)=4(&=& =%( )=9$Q *="{ -=! $=k  =& *= +=). .=(\ %=& (=h% )="$ ,=" #=!! *=T K +=v .= %=&#%,%) =&e$<% #(( =!( p0G02& =Q% <=)2 =G|>(:#P =&:%p;"f $=! 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PLQ  0S KR \ GM|A:g>ctcW1C2Q`CjB*::0KQ   @/ /K ㏜ G]<7Nd EgTqG2<7~d edVAD2Q0D:0G@;:@KK;;s;@KP@ 5/K AC0hdd4Q Q Q 0 ?/ / ?/O-M@T1 R$ R! `P=  pPp W*P011W00#p(3 000"p2 0007/K0pW00:/P  PQ Q Qp Рp   Q Q Q0P?Z!p1 000P0P?Z  RR*``Qp*apW b `R0k B! pQQ% Q Q2pu zV( P `VpV0P  Pa `Vp pV P Pa `VKP@4 5/H$  (//, <FH X E߄E Sn O-,M`D oP1 pAZ 1ZPPPzP@ Tt0'pY PPu@P%uTE! dT 1 $  0 $1  b *b @*@0ꔥ` @pE d 0$@(P*0KO/ FO- MZ" @0 Y*㏌K}  G]('7cecV1C2C\*  ^   Z:KK] , Gmq5cvcW1C2pCW* \0 Z* P R*K} L G=.'acaVA2 AR*` Z  K= K, GMpwadaVA2`AV* Z KFO-LMp` 0@ pPP#@P`PTk  pO oU  op `0pP6"#3'Q0S p@ p? B zc # "#&B J# @ TS@Tq3 p '$ @Z1 p$y@?P A t0t pS" S  0/G $@ (@@ D0K y?TI(*  T ST d 0!$T@ 01ꔉ` @@pI( d0@@D P * 0KFO-MpX1 ( 0p @S`  0,*㏜Kȭ < GIG*b\b U!B2B@X@* P @e0D @UQ@@S^ X:KK= \ GM#abQ!B2BP*\0p X*0 ` P`?R@,pp0**ᏬKȍ < G  *'Hg|d WAD2D ^ *p g0" WQ  S  R @K K, G=|AgsdWAD2pDW*X @KF%s:%d %s was not true./home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/random_uniform_custom.cctflite::NumInputs(node) >= 1%s:%d %s != %s (%d != %d)tflite::NumOutputs(node)1input->type == kTfLiteInt32 || input->type == kTfLiteInt64tflite::NumDimensions(input)params != nullptrUnsupported output datatype for RandomUniform: %stflite::NumInputs(node) >= 3min_value < max_valueUnsupported output datatype for RandomUniformInt: %sclang version 18.1.8A?aeabi5C2.09 A   "$&  m2l)Zq;v-2 ]_|5H T 0X d N00g#  F\g,xN0d< ""H cX $" N" '(*t,-./lptx|     -,.2x-,.,,X 5 6 5 2 $ ( , 0 4 8 < @ D T d (*(*0** 0** ( *(((*0(0*8(8*t999:\;;(*(* 9(9H9<:<(*"(*$&)+ 10&4)8+<4&)+14.rel.ARM.exidx__aeabi_uidiv_ZN6tflite3ops6custom14random_uniform4FreeEP13TfLiteContextPv_ZdlPv_ZN6tflite3ops6custom27Register_RANDOM_UNIFORM_INTEv_ZN6tflite3ops6custom23Register_RANDOM_UNIFORMEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite3ops6custom14random_uniform18IntValueFromTensorEPK12TfLiteTensor_ZZN6tflite3ops6custom27Register_RANDOM_UNIFORM_INTEvE1r_ZZN6tflite3ops6custom23Register_RANDOM_UNIFORMEvE1r.group.note.GNU-stack_Znwj_ZN6tflite3ops6custom14random_uniform4InitEP13TfLiteContextPKcj_ZN6tflite9GetOutputEP13TfLiteContextPK10TfLiteNodei_ZN6tflite8GetInputEPK13TfLiteContextPK10TfLiteNodei.llvm_addrsigTfLiteIntArrayCreateTfLiteTypeGetNameTfLiteTensorDataFree_ZN6tflite3ops6custom14random_uniform7EvalIntEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops6custom14random_uniform9EvalFloatEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops6custom14random_uniform7PrepareEP13TfLiteContextP10TfLiteNode__aeabi_uidivmodrandom_uniform_custom.cc.ARM.extab.strtab.symtab.rel.data.rel.ARM.exidx.text._ZNSt3__124uniform_int_distributionIxEclINS_26linear_congruential_engineIjLj48271ELj0ELj2147483647EEEEExRT_RKNS1_10param_typeE.rel.text._ZNSt3__124uniform_int_distributionIxEclINS_26linear_congruential_engineIjLj48271ELj0ELj2147483647EEEEExRT_RKNS1_10param_typeE.rel.ARM.exidx.text._ZNSt3__124uniform_int_distributionIiEclINS_26linear_congruential_engineIjLj48271ELj0ELj2147483647EEEEEiRT_RKNS1_10param_typeE.rel.text._ZNSt3__124uniform_int_distributionIiEclINS_26linear_congruential_engineIjLj48271ELj0ELj2147483647EEEEEiRT_RKNS1_10param_typeE.rel.ARM.exidx.text._ZNSt3__125__independent_bits_engineINS_26linear_congruential_engineIjLj48271ELj0ELj2147483647EEEyE6__evalENS_17integral_constantIbLb1EEE.rel.ARM.exidx.text._ZNSt3__125__independent_bits_engineINS_26linear_congruential_engineIjLj48271ELj0ELj2147483647EEEjE6__evalENS_17integral_constantIbLb1EEE.L.str.9$d.9.L.str.8$a.8.L.str.7$d.7.L.str.6$a.6.L.str.5$d.5$a.14.L.str.4$a.4$a.13.L.str.3$d.3.L.str.12$a.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11$d.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.10$a.10$a.0gr8h  @h!p @ @! P!5  0!"p  ! d!; $p  !t!6$ 0!p !!<H >p: !72` @ @!Lo0p@Lo`!&range.cc.o/ 1749669127 1000 1000 100644 7232 ` ELF(4(/Q/M- M R! 0S R) 0S'p0 @P P 0 P0 P# K0@#s` Sp00P 0@#s` |Sp00PpP @6/K0`V <8#83p@,S0 @Ph07/K`V @"2p R0 @Ph07/K ``V @"2p R0 @Ph07/K`V>0: QQ@0 PPY`PJ PE0P@PHNp@P1a!0`H P07/KP@X 5/Kp@P0010a,!0`H P07/KPP K`0 `PP 0PK|xtl,$L$  0H-M 0K P@P K00 P 0 PQ0 P0P  P 00P0  K0M-MPpUD U UR`Q@  0 0RQJRQm R` bBQaB@PY00`& ` @ `T`SJ`R`Q`x`N`R_# /!P/(/R?PP20 @   !p1 00007/K 03/K *A*@ JA*@ B1`   Z P0KM/88 p00 00207/K,(( K-\ \ \+P p0 P,P*0pԀ@ @PP*`(0`p R RS*p] 03/[0uaQ0*a0S b `P0; 1@`0PQz`Q!:a+yKƒj`># @[$#QdP0 !B(t`qHr*G!d0p p6 A@@PQLqQ`*a`V b `R0k 1 B0p RQ6*0QB0qQ`*c`V b `P;0k @q`pPS`S:|*`a@+!" d  D`PSm 0C  0S ( `$E߄AE߄E(%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/range.ccNumInputs(node)3NumOutputs(node)1NumDimensions(start)0NumDimensions(limit)NumDimensions(delta)Unknown index output data type: %s%s:%d %s != %s (%s != %s)limit->typedtypedelta->typeUnknown data type: %d%s:%d %s was not true.!std::equal_to()(delta, 0)(start >= limit && delta < 0) || (start <= limit && delta > 0)Unsupported data type: %dclang version 18.1.8A?aeabi5C2.09 A   "$& a0(st`p J d gt Ov 7     #  u  ] E  9X@<; R p? -% (`  ha$ )$*|+++,- -t--- .(.L t      +<+X+,  l0123< @D!H LP"T# &(*(*(*/** / *$*(/(*,*0/0*4*  .rel.ARM.exidx__aeabi_uidiv_ZN6tflite3ops7builtin5range12_GLOBAL__N_14FreeEP13TfLiteContextPv_ZdlPv_ZN6tflite3ops7builtin14Register_RANGEEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin14Register_RANGEEvE1r.note.GNU-stack_Znwj_ZN6tflite3ops7builtin5range12_GLOBAL__N_14InitEP13TfLiteContextPKcj.llvm_addrsigceilfTfLiteIntArrayCreateTfLiteTypeGetNameTfLiteTensorDataFree_ZN6tflite3ops7builtin5range12_GLOBAL__N_14EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin5range12_GLOBAL__N_17PrepareEP13TfLiteContextP10TfLiteNode__aeabi_uldivmodrange.cc.ARM.extab.strtab.symtab.rel.data_ZN6tflite3ops7builtin5range12_GLOBAL__N_18EvalImplEP13TfLiteContextPK12TfLiteTensorS8_PS6__ZN6tflite3ops7builtin5range12_GLOBAL__N_112ResizeOutputEP13TfLiteContextPK12TfLiteTensorS8_S8_PS6_.L.str.19.L.str.9.L.str.18.L.str.8.L.str.17.L.str.7$d.7.L.str.16.L.str.6$a.6.L.str.15.L.str.5$d.5.L.str.14.L.str.4$a.4.L.str.13.L.str.3$d.3.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.10$a.0@  @ p$ 8 @\ 0 0  @ 2 Lo0p@Lo@'rank.cc.o/ 1749669126 1000 1000 100644 2908 ` ELF(4(pL-M R/ 0S- R7 0S50 @`PP0 PPPP 0 3/PP$ Kp0P!@ a 00` 0P @ ` 0 0`` P4/Kp0S  `P @ 020@@ `5/PKpPQPKp|//CDŽ,4%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/rank.ccNumInputs(node)1NumOutputs(node)NumDimensions(output)0clang version 18.1.8A?aeabi5C2.09 A   "$&kxIScEs<u3*\,N@0,rgRa|,4Ll   $ ( @** ** .rel.ARM.exidx_ZN6tflite3ops7builtin13Register_RANKEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin13Register_RANKEvE1r.note.GNU-stack.llvm_addrsigTfLiteIntArrayCreateTfLiteTensorDataFree_ZN6tflite3ops7builtin4rank4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin4rank7PrepareEP13TfLiteContextP10TfLiteNoderank.cc.ARM.extab.strtab.symtab.rel.data.L.str.6.L.str.5.L.str.4.L.str.3$d.3.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0$a.0+<4D8 @Xx p @82$@0  @KLopB0p4[p@DLo(/4231 1749669129 1000 1000 100644 4676 ` ELF(4(O-DM 0S 0S 0K P`@P" K@#s` Sp0"0P l@h#hs` \Sp0#0PpP @6/K QQ YOY0`:"p2 00)07/@KA $/ b @@01;X4@T0`0kY'` 2*2[W!3kW!Ɗ#6# ;! 1 Q0+S q!&0$Y  I10 P@ RĊᕧ%T& P , $0K @Pz$PPuPr KYP+1 $( `0 0S,0Z( 1KR'i2*2[Vu 3V $A!{! 1 Q0+S q!%$Y  I 0` RƇOt#6% 0|@x xpt0 pp0 P*0@:/K|xp\XTLlhhdH-M0 P@ `P K4P# 0D`p V`PPP!P p 7/PP KC0 ` 6/K`PHH0HpD 0p PJ06/K|xx<884/F,C%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/read_variable.ccnode->inputs->size1node->outputs->size%s:%d %s was not true.(input_resource_id_tensor->type == kTfLiteResource || input_resource_id_tensor->type == kTfLiteInt32)NumElements(input_resource_id_tensor)variable != nullptr%s:%d %s != %s (%s != %s)variable_tensor->typeoutput->typeclang version 18.1.8A?aeabi5C2.09 A   "$&RlvhZQfH&,?86Lf| qc+0,Vk,pD*<P    $ (LpH X  *!* ** TfLiteIntArrayCopymemcpy.rel.ARM.exidx_ZN6tflite3ops7builtin22Register_READ_VARIABLEEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin22Register_READ_VARIABLEEvE1r.note.GNU-stack_ZN6tflite8resource19GetResourceVariableEPNSt3__113unordered_mapIiNS1_10unique_ptrINS0_12ResourceBaseENS1_14default_deleteIS4_EEEENS1_4hashIiEENS1_8equal_toIiEENS1_9allocatorINS1_4pairIKiS7_EEEEEEi.llvm_addrsigTfLiteTypeGetNameTfLiteTensorDataFree_ZN6tflite3ops7builtin13read_variable4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin13read_variable7PrepareEP13TfLiteContextP10TfLiteNoderead_variable.cc.ARM.extab.strtab.symtab.rel.data.L.str.9.L.str.8.L.str.7.L.str.6.L.str.5$d.5.L.str.4$a.4.L.str.3$d.3.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.10$a.0 _@[ @x p  @ 8$ 2000, @ nLoe0`~p@6Lo $H0reduce.cc.o/ 1749669138 1000 1000 100644 437192 ` ELF(64(T 0H-@PP0  B3/0Q/M-P`p `QQ*@ AQ0*`0S b `Q 0; A0Pp0M/M-P`p `QQ*@ AQ0*`0S b `Q 0; A0Pp0M/O-M@0pWW*` `!QP*cPU b `W;0k 0G!p 0S PU \Q UV6 !p!Qp 0@pT@T 0SKV'   BQ2 1S0@S JSQ pAT@@S pQUp @ Q#F*0 E1p RpTU,OHH!p@1 0007/KEU>V   Q5 0p@T@T pWpA1q00Q#U @ R#* 1qU0q 0 cQ BU  0p0S gp GUK<880H-M P@PK0  0K0H/pL-`@P 0pL/H-MP `@p 0  P K  0 3/P0  P0  00  P@Q <0$0,H$,$ 0 P  KO-,M R) 0S' R1 0S/ P @p  `$ P(P) P9 K0@#s` Sp00P 0@#s` tSp00PpP @6/KP@4434s0#0p 0@5/KPPo  PQ*Q**05 RD0S l@h"hr` \Rp01P0S1 <@8"8r` ,Rp01PQ0 *c R b ` Q+0; ! 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Q  0Q 0Sp 00SPW'p 0P0S'@` 2/P P)!0R0R1@ p`2/Y PA`D Q!1 pSpSqA  2/KFO-DM,  `pWW*@P@QQ *f R b `W 0+ !G pPP pUR `p^$p p* S`0\P (` ``PUP0$$(A@ p@ PQ 00 , p 00017/K$$FO-DM,  `pWW*@P@QQ *f R b `W 0+ !G pPP pUR `p^$p p* S`0\P (` ``PUP0$$(A@ p@ PQ 00 , p 00017/K$$FH-MP @p `  AP5$T<l 0" 0 0 0 0 0 0`KCO-M-8M\ P@xVP\pW pW`@PU> @T,@(P$ 0,`@@0?,P(P `P) ,4P* (& '0Ap@o 0   00, 0RpU RSRPP@KЍW W * 0= 1Q*aP b `S 0 aG0PRPR: P PQ 0 @ `p`V p?0 0 D0R 1 Bp Rp0n8@ `PP ( X :@ )I    P#XX J@CD:@I    0  X  mOO-$Mp@P 0W<Q G`pP 0   p 0W KW@0   0 p 0W KS T @pTJT P 1 ! QK@pTT* $PPK D+0 P`PU`?(2*2*``\0{ 0Dp0SKFO-M-8M\ P@xVP\pW pW`@PU> @T,@(P$ 0,`@@0?,P(P `P) ,4P* (& '0Ap@o 0   00, 0RpU RSRPP@KЍW W * 0= 1Q*aP b `S 0 aG0PRPR: P PQ 0 @ `p`V p?0 0 D0R 1 Bp Rp0n8@ `PP ( X :@ )I   X  X J@BD:@I    0  X  oOO-$Mp@P 0W<Q G`pP 0   p 0W KW@0   0 p 0W KS T @pTLT P0!0 ! QK@pTT* %PPK D+0 P`PU`?(2*2*``\0{ 0Dp0SKFpL-M@ P`  0 Q R R KpKpL Kp03/Kp CDŽO-M-M@PL0pWW .7<H@!W/P b!8p4 1{\ RT0P0X'j2*2 V@V!3[V &e'K{! 1 Q<0+SH@咀q!8p4 *W! G 0Q⒃ov"#* L`,0K P00K P 40K P80K P (KЍ ` 0P R P8pL0P  03/PLpP:0 PP4 PTpKHTKLpTKHPe Wl  Lp  0+S1 Q 0 1 A 0 QLHTK`DX 0`R0P, p`RUp 4PU !(VD`XLH$ T K` p,PPXTKU\3 p 7/(KЍ(KЍx3t pl `>>\ pT TKTKXTKTKhddPLLI.   H O-M-M@PL0pWW .7<H@!W/P b!8p4 1{\ RT0P0X'j2*2 V@V!3[V &e'K{! 1 Q<0+SH@咀q!8p4 *W! G 0Q⒃ov"#* L`,0K P00K P 40K P80K P (KЍ ` 0P R P8pL0P  03/PLpP:0 PP4 PTpKHTKLpTKHPe Wl  Lp  0+S1 Q 0 1 A 0 QLHTK`DX 0`R0P, p`RUp 4PU !(VD`XLH$ T K` p,PPXTKU\3 p 7/(KЍ(KЍx3t pl `>>\ pT TKTKXTKTKhddPLLI.   H H-MP @p `  AP5$T<l 0" 0 0 0 0 0 0`KCO-\M(p0$^  !S @`@`T P@P JP QPX PQK0 8K( ( P@ K4 a`8`8` 4`4`0`0`,,`($S  TP$ `p8( P" P!(8 KP$ P#W& P@P400  PUK 1/(8 KP 1/WK88@KQ Q 1/( Q  Q@ 1/F @O-MS ! @` A Z"`P!1`Z5% Q" Q+` !18( Q  0pQ 0SPV !& V !  0`0Spx(  0p0S`h( ` V 01S RP-  @ 2/! P  @03/`Z @ PU 1!p0R0R1PE {KF/L-@0  A  0 / /A/ 00R/ //L-@    A     //H- P @0 H 00R/ /O-\M(p0$^  !S `P`PV P@P JP Q@X @QK0 `8K( (P K4 A@8@8@ 4@4@0@0@,,@($S  YP$ p@p8( P" P!(8 KP$ P#W& PPp400 pWK 1/(8 KP 1/WK88@KQ Q 1/( Q  Q@ 1/F DO-MS ! @` A Z"`P!1`Z5% Q" Q+` !18( Q  0pQ 0SPV !& V !  0`0Spx(  0p0S`h( ` V 01S RP.  @ 2/  P  @03/`Z @ PU 1!p0R0R1PE yKF/L-@0  A  0 / /A/ 00R/ //L-@    A     //H- P @0 H 00R/ /%s:%d %s was not true./home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/reduce.cccurrent >= 0 && current < input_num_dims%s:%d %s != %s (%d != %d)NumInputs(node)2NumOutputs(node)1%s:%d %s != %s (%s != %s)op_context.axis->typekTfLiteInt32op_context.input->params.zero_point0op_context.output->params.zero_pointinput->typekTfLiteBoolUnsupported quantized data type: %dinput_size != 0output_size != 0optimized_ops::QuantizedReduceProd( GetTensorData(input), input->params.zero_point, GetTensorShape(input), GetTensorData(output), output->params.zero_point, GetTensorShape(output), GetTensorData(op_context->axis), num_axis, GetTensorData(resolved_axis), GetTensorData(normalized_dims), GetTensorData(temp_prod), data->multiplier, data->shift)input->params.scaleop_context->output->params.scaleinput->params.zero_pointop_context->output->params.zero_pointoptimized_ops::ReduceGeneric( GetTensorData(input), input->dims->data, input->dims->size, GetTensorData(op_context->output), op_context->output->dims->data, op_context->output->dims->size, GetTensorData(op_context->axis), num_axis, GetTensorData(resolved_axis), GetTensorData(normalized_dims), reduce_type)vectorstd::apply(optimized_ops::Mean, args)reference_ops::QuantizedMeanOrSum( GetTensorData(input), input->params.zero_point, input->dims->data, input->dims->size, GetTensorData(output), data->multiplier, data->shift, output->params.zero_point, output->dims->data, output->dims->size, GetTensorData(op_context.axis), num_axis, op_context.params->keep_dims, GetTensorData(temp_index), GetTensorData(resolved_axis), GetTensorData(temp_sum), false)std::apply(reference_ops::Mean, args)reference_ops::QuantizedMeanOrSum( GetTensorData(op_context.input), op_context.input->params.zero_point, op_context.input->dims->data, op_context.input->dims->size, GetTensorData(op_context.output), op_data->multiplier, op_data->shift, op_context.output->params.zero_point, op_context.output->dims->data, op_context.output->dims->size, GetTensorData(op_context.axis), num_axis, op_context.params->keep_dims, GetTensorData(temp_index), GetTensorData(resolved_axis), GetTensorData(temp_sum), compute_sum)Unsupported ReduceType: %d/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/reduce.cc Invalid axis index.reference_ops::ReduceGeneric( GetTensorData(input), input->dims->data, input->dims->size, GetTensorData(op_context->output), op_context->output->dims->data, op_context->output->dims->size, GetTensorData(op_context->axis), num_axis, op_context->params->keep_dims, GetTensorData(temp_index), GetTensorData(resolved_axis), init_value, reducer)optimized_ops::QuantizedMeanOrSum( GetTensorData(op_context.input), op_context.input->params.zero_point, op_context.input->params.scale, op_context.input->dims->data, op_context.input->dims->size, GetTensorData(op_context.output), op_context.output->params.zero_point, op_context.output->params.scale, op_context.output->dims->data, op_context.output->dims->size, GetTensorData(op_context.axis), num_axis, op_context.params->keep_dims, GetTensorData(temp_index), GetTensorData(resolved_axis), GetTensorData(temp_sum), compute_sum)reference_ops::QuantizedReduceProd( GetTensorData(input), input->params.zero_point, GetTensorShape(input), GetTensorData(output), output->params.zero_point, GetTensorShape(output), GetTensorData(op_context->axis), num_axis, op_context->params->keep_dims, GetTensorData(temp_index), GetTensorData(resolved_axis), GetTensorData(temp_prod), data->multiplier, data->shift)N6tflite21optimized_integer_ops14MeanWorkerTaskEN8gemmlowp4TaskEN6tflite13optimized_ops14MeanWorkerTaskENSt3__110__function6__funcIPFfffENS_9allocatorIS3_EES2_EENSt3__110__function6__baseIFfffEEEPFfffEFfffEN6tflite3ops7builtin6reduce16ReduceWorkerTaskIfEENSt3__117bad_function_callENSt3__110__function6__funcIPFiiiENS_9allocatorIS3_EES2_EENSt3__110__function6__baseIFiiiEEEPFiiiEFiiiEN6tflite3ops7builtin6reduce16ReduceWorkerTaskIiEENSt3__110__function6__funcIPFxxxENS_9allocatorIS3_EES2_EENSt3__110__function6__baseIFxxxEEEPFxxxEFxxxEN6tflite3ops7builtin6reduce16ReduceWorkerTaskIxEENSt3__110__function6__funcIPFhhhENS_9allocatorIS3_EES2_EENSt3__110__function6__baseIFhhhEEEPFhhhEFhhhEN6tflite3ops7builtin6reduce16ReduceWorkerTaskIhEENSt3__110__function6__funcIPFaaaENS_9allocatorIS3_EES2_EENSt3__110__function6__baseIFaaaEEEPFaaaEFaaaEN6tflite3ops7builtin6reduce16ReduceWorkerTaskIaEENSt3__110__function6__funcIPFsssENS_9allocatorIS3_EES2_EENSt3__110__function6__baseIFsssEEEPFsssEFsssEN6tflite3ops7builtin6reduce16ReduceWorkerTaskIsEENSt3__110__function6__funcIPFbbbENS_9allocatorIS3_EES2_EENSt3__110__function6__baseIFbbbEEEPFbbbEFbbbEN6tflite3ops7builtin6reduce16ReduceWorkerTaskIbEENSt3__110__function6__funcIZN6tflite13reference_ops19QuantizedReduceProdIaEEbPKT_iRKNS2_12RuntimeShapeEPS5_iSA_PKixbPiSE_SE_iiEUlaE_NS_9allocatorISF_EEFiaEEENSt3__110__function6__baseIFiaEEEZN6tflite13reference_ops19QuantizedReduceProdIaEEbPKT_iRKNS_12RuntimeShapeEPS2_iS7_PKixbPiSB_SB_iiEUlaE_NSt3__110__function6__funcIZN6tflite13reference_ops19QuantizedReduceProdIaEEbPKT_iRKNS2_12RuntimeShapeEPS5_iSA_PKixbPiSE_SE_iiEUliaE_NS_9allocatorISF_EEFiiaEEENSt3__110__function6__baseIFiiaEEEZN6tflite13reference_ops19QuantizedReduceProdIaEEbPKT_iRKNS_12RuntimeShapeEPS2_iS7_PKixbPiSB_SB_iiEUliaE_NSt3__110__function6__funcIZN6tflite13reference_ops19QuantizedReduceProdIsEEbPKT_iRKNS2_12RuntimeShapeEPS5_iSA_PKixbPiSE_SE_iiEUlsE_NS_9allocatorISF_EEFisEEENSt3__110__function6__baseIFisEEEZN6tflite13reference_ops19QuantizedReduceProdIsEEbPKT_iRKNS_12RuntimeShapeEPS2_iS7_PKixbPiSB_SB_iiEUlsE_NSt3__110__function6__funcIZN6tflite13reference_ops19QuantizedReduceProdIsEEbPKT_iRKNS2_12RuntimeShapeEPS5_iSA_PKixbPiSE_SE_iiEUlisE_NS_9allocatorISF_EEFiisEEENSt3__110__function6__baseIFiisEEEZN6tflite13reference_ops19QuantizedReduceProdIsEEbPKT_iRKNS_12RuntimeShapeEPS2_iS7_PKixbPiSB_SB_iiEUlisE_???clang 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; @L1}|pD (x @5X}l 8 @\5}p'}a< p d5} 2<. 6} .pP *  6} p(}lXph 6}p$(}g1p- ,6(}p4 T6}p8(}b<x" d6}< 7}p  7}pT(}mp  7}!pd(}h ,7(}$*p$& T7}&px(}`x d7})nx<j 8}+jp)f  8}-p(}ne[p0W 8}1p(}em i ,8(}4p4 T8}6p(}_ ^ d8}9 0< 9}; pl9  9}=p(}otp@ 9}Ap(}d  ,9(}Df p\Db T9}Fp(}cZ d d9}IP <L :}KL p IH  :}Mp)}p(p8P :}Qp$)}iO@K ,:(}T pT T:}Vp8)}^ @ d:}Y!< ;}[p!Y  ;}]pT)}qU!Kp!`G ;}apd)}f! ,;(}dHp"dD T;}fpx)}t"e d;}iH%P ;}kp%i ;}mp)}y%o  <@}p@& pL&p  L<}s2T&p'0 @d< }vTLo'K0''dp'@Lo< })O/4363 1749669131 1000 1000 100644 6220 ` ELF(4(pL- M R 0S R! 0S0K @P`P+ Kp0`"Ÿ@ R 0B0PP `4/Kp0``\"\ŸP PB 0C0@@ `5/`Kp0 S:0SC0 `P0 SEPO 0 3/`P0 `PQG 0 @B 0 3/`Kp$ ! `P A 0I0@` @ P 0J0P `P @ 0O0@ `0 00P06/`Kp| `t0 00Z0PLH@ pll O-LM@ Pp`  Q g0$p 7/K,` R>R0.(@A0 $? c @ 1Y0 @T400+S'j2*2[Vu,3kP#&  +{ !; 1 Q(@0+S$ 咠q! 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KF%s:%d %s != %s (%d != %d)/home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/sparse_to_dense.ccNumElements(indices)NumElements(values)NumElements(output_shape)1SizeOfDimension(indices, 1)SizeOfDimension(indices, 0)Wrong indices dimensions %d, should be less than 3.Dense shape type %d not supported.NumInputs(node)4NumOutputs(node)%s NumDimensions(indices) >= 0%s:%d %s was not true.NumDimensions(indices) < 3NumDimensions(output_shape) >= 0NumDimensions(output_shape)NumDimensions(values) >= 0NumDimensions(values) < 2NumElements(default_value)indices->type == kTfLiteInt32 || indices->type == kTfLiteInt64output_shape->type == kTfLiteInt32 || output_shape->type == kTfLiteInt64values->type == kTfLiteInt32 || values->type == kTfLiteInt64 || values->type == kTfLiteInt8 || values->type == kTfLiteUInt8 || values->type == kTfLiteFloat32%s:%d %s != %s (%s != %s)values->typedefault_value->typeValue type %s is currently not supported by sparse to dense.Indice type %s is currently not 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I p!`@`V@ Pg0 AP @R_@ H l P 4  K,  PDP\|(FFF4uFwFxFtypeoutput_tensor->typeinit_value_tensor->type%s:%d %s was not true.input_tensor->dims != nullptrinput_tensor->dims->size > 0input_tensor->dims->size <= kMaxReduceWindowRankAllGtThanZero(base_dilations)AllGtThanZero(window_dimensions)AllGtThanZero(window_strides)AllGtThanZero(window_dilations)dilated_tensor != nullptrpadded_tensor != nullptrBody subgraph not found for stablehlo.reduce_window: %d.Only one kernel is allowed within stablehlo.reduce_window body. 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K@'w` Wp00P @&v` Vp00PpP @6/K 0S$0K  P$0S0S(0K` P(0S0S ^,0K P,0S0 S00 P+00S0S0S",0 P,0S&0S9(0 P0 ( `3/P$0 P$$` 6/P ` 0  P  `0 3/P 0    P   0 pp3/#s`@Sp0 PpP0!`\#\s`@PSp0 PpP000#0s` $Sp00PpP 6/K"r`@Rp0 PpP0@"r` Rp00P0"r` RppP @6/Kpl"lr`@`Rp0 PpP0@<"inputs->sizekInputNumnode->outputs->sizekOutputNuminput->dims->size3input_state->dims->size2input_state->dims->data[0]n_batchgate_weight->dims->sizegate_weight->dims->data[0]2 * n_outputgate_weight->dims->data[1]n_input + n_outputgate_bias->dims->size1gate_bias->dims->data[0]candidate_weight->dims->sizecandidate_weight->dims->data[0]n_outputcandidate_weight->dims->data[1]candidate_bias->dims->sizecandidate_bias->dims->data[0]Unsupported combination of data types for GruCellclang version 18.1.8A?aeabi5C2.09 A   "$&B`Rz0  zH&: Gbupw >   '[=T 9P E2T  0Y0 4`#4nD`3IF-u$)@,/H////h/010$2L3X1x4141       $(,048<@DHLPTX\`dhlptx|// / /8 /T /p 0 0 4 4 6 !P # 7 7 7 7( 7H 7 7 8L 8d 9l 9t 9| 9 9 9 9 9 9 9 : 9 9 9 9 99 999 :0'*;***-*-**** *$*(-(*(+. 5(+.5;:'TfLiteIntArrayCopy.rel.ARM.exidx_ZN6tflite3ops6custom27unidirectional_sequence_gru4FreeEP13TfLiteContextPv_ZdlPv_ZN6tflite3ops6custom36Register_UNIDIRECTIONAL_SEQUENCE_GRUEv_ZN6tflite12RuntimeShapeD1Ev_ZN6tflite17CpuBackendContext14GetFromContextEP13TfLiteContext.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite16GetTemporarySafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZN6tflite14GetTensorShapeEPK12TfLiteTensor_ZZN6tflite3ops6custom36Register_UNIDIRECTIONAL_SEQUENCE_GRUEvE1r__cxa_end_cleanup.note.GNU-stack_Znwj_ZN6tflite3ops6custom27unidirectional_sequence_gru4InitEP13TfLiteContextPKcj.llvm_addrsigTfLiteIntArrayCreateTfLiteIntArrayFree_ZN6tflite3ops6custom27unidirectional_sequence_gru4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops6custom27unidirectional_sequence_gru7PrepareEP13TfLiteContextP10TfLiteNodeunidirectional_sequence_gru.cc.rel.ARM.extab.strtab.symtab.rel.data_ZN6tflite3ops6custom27unidirectional_sequence_gru12_GLOBAL__N_17GruImplEPK12TfLiteTensorS6_S6_S6_S6_S6_PS4_S7_S7_S7_PNS_17CpuBackendContextE_ZN6tflite3ops6custom8gru_cell7GruCellERKNS_12RuntimeShapeEPKfS5_S7_S5_S7_S5_S7_S5_S7_S5_S7_S5_PfS8_S5_S8_S5_S8_RKNS_20FullyConnectedParamsEPNS_17CpuBackendContextE.L.str.19.L.str.9.L.str.18.L.str.8.L.str.17.L.str.7.L.str.26.L.str.16.L.str.6.L.str.25.L.str.15.L.str.5$d.5GCC_except_table4.L.str.24.L.str.14.L.str.4$a.4.L.str.23.L.str.13.L.str.3$d.3.L.str.22.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.21.L.str.11.L.str.1$d.1.rodata.str1.1__gxx_personality_v0__aeabi_unwind_cpp_pr0.L.str.20.L.str.10$a.0#744 @h` @p0 @p2w7p03 @  "Lo02p@Lo0+(/4902 1749669149 1000 1000 100644 47896 ` ELF((4(F0H-@RR/P0  3/0Q/L-@LO-7/Kp @PP 0S0 S0S 0K P K/`@_p0 PpP1 0S0 S`V$0K P$0S0 S0S `P 0S S0S  P0 S(0K P(0S S0S  P,0 pP,0S S 0S. PVZV4 pPo 0S80 SWQ` Pb `P/` _p01P1/`@_p0 PpP1 @6/K/oP O`01@`@ p5/K/` _p0=PpP 6/K0/P Op 01@pP5/K/`@_p0 PpP1/` _p0r?Pxx/xoP lO`01@XT/T`@H_p0 PpPu?/` _p01P/` _p01P2/`@_p0 PpPz?a`P ?/0p Pv?6/K/` _p01PpP 6/K`P ?/0p P{?6/K/`@_p0 PpP~? @/` _p01PpP /p? 0027/pK`\/\` _p@0 2P`P ?/0p P?/` _p0?P P3 `PD 0S 0 SQ5 P7 `Py/` _p@02PJ/` _p02PQ`P ``/`?\ 0 pP2@ PA PS 0S0 S  RD QF `P/` _p@02PppP @6/K/` _p0">PpP 6/pK`P /? 0 pP2  Q`W VP/p? 00/2ZVP' Z# 0S10 SQQZ PZ `P?/0p P:2 PA P/?p o0`H52 P/` _p@072Pj`P /? 0 pP#2l/` _p0?P\P6(0 pPW(0S0 S=QF PF `P((?($/0p PG24.~` ^p@0?P`Ppp>pΟp0l.  ?P6/KLH.H~` <^p0E2PP($0 pP$0S.0 S<QH PH `P=}-0p PS2`Ppt=t͟t0p-  I2PL-L}` @]p@0%>P-}` ]p0Q2PP, 0 pP 0S20 S=QF PF `P<|,0p P_2x`Pp(<(̟(0$,  U2L,|` [p@0?P<+{` [p0]2PCP6 `P 0S>0SS0 Ss P 0SX0SxQ P `P||;|{x+0p Pr2 `Pp:ʟ0*  a2*z`@Zp0 PpPg2 @XT*Tz` HZp0?PpP 0,*,z` Zp@0o2P)y` Yp0i2P)y` Yp0'>PpP |lhd\H4@8PlV} pP  Z( P= 0SH0 SyQ P `P9y)0p P2ZPt P|(|8p ph0`H2 P<8(p08 002p (x` Wp@0?P`Ppt7tǟt0p'  ?PL'pD7 002<LH'Hw` t%u` Up02Py|TPPLP(0 pPh0S.0 S=QN PN `PDD5Du@%0p P2E`Pp4ğ0$  2$t` Tp@02P hd$dt` XTp02P||xP+0 pP0S10 S@QI PI `P3s#0p P2`Ppd3dßd0`#  2@<#D 0pn@`H3 P.>p _0P(3 `0 P@ SD A o 0pP\,0K  PT  $P(D   P H (P,J,PR@yP/p o03`A P/p o0?`A /p o03`A s3/p h/D p?00?]<8PE D`L `,A00S hhlp'`0 Q2*2X8(3 Z41Q00`z'p 8p4嗌' !{ 1\,0;WP,"!( ,0 @ R#0(0<8.( P,,P!@HDL,PiH`<$8PM D`L O `,A00S XX\p'`0 Q2*2X8|(3P4p1W0p0`q  8{4p呌!{ ! 1\,0;WP,"!( ,0 @ R#0(0<$8.(Q  ,pDq0P3/P'@ PP $ PP  Q @ QL00K  DP  0D   $Zqq 00<3/P$ PP PW @ PPHP D@  t0  Pt` K$\ <` P Ht0  D Pt` K$\ <` P Ht0  p D Pt` Kp$\ <` P Ht0  D Pvt` K$\ <` P Ht0  D PZt` K $\ <` P Ht0  D P>t` K$\ <` P D HPK>@ ``,HQ@dp1{Y` 0+X'n2*2kU6 3+U Š%R";+! 1 Q0+Sa!&,HP H ,@0P#W's&+ ; `0 3JDL,PH`%+@ `P,HQ@Tp1{YP 0+X'n2*2kU6 3+U Š%R";+! 1 Q0+Sa!&,HP H ,@0P#W's&) 9 `0 38DLp)D p900?KH  40K LD Pw p4 $00p0PR 80KL  D P_(8 $00p0P[ <0KL D PH < $00p0Pa H@0K  D Pk K D` t<0$pp3/P\  D403/P D` t<0$pp3/P\( D803/PD` t<0$pp3/PW  D<03/P @D K<D PN HH0K  D PH  D KPV L0KL D PL  D KPh P0KL  D Pr KD` t<0$pp3/PjDp @<03/P KD` t<0$pp3/PJDp H<03/P<D` t<0$pp3/P(Dp L<03/PPT K$T P X0KL $D P KDp P$03/P KX` K<\ $` P> Hd0K  (D Pd  D KP8 Hh0K  ,D Ph  D KP. l0KL 0D P1 KD` X<0$pp3/P KDp d<03/PsDp h<03/Pel   DpZpP $Z  z  1 zlt $xtpP\ tDlxp0p3/PO K   O-M-xM`@ PP d0Kp P `KЍA0+p  7/`KЍ0P d0P @ 4   A A NA A *4@(  A A NA A  h0K P l0 Ph0 Pd0 P `0 P\0 PX0 P   4  ( $  0 P,u ZTPLHD@w <0 P<0Q 4L@<0 P<0Q 4L@<0 P<0Q 4L@<0 P<0Q 4L@FH0'p| pL0l'pd FP0L'pD B<L<<@<<L<<@<<L<<@<<L<<@<<0 Pc<0Q- 4PL@Y8, 4P5 4Z    0     Ap% 07/1p% 07/%4P 4ZHH    Z    HZH  $  (   0Xh0PlP0,   Pڒʜ  8P hLY8  II (,*.I I4 P* Y 0 Q 8 1 AL a  0[VL8 p 1GL :  a*1 A a* 0 Q0 0 Q 0 0 Q 0, * 0 Q 0 - 0 Q $0 0 Q( ,0 . 0 Q0 40* - 0 Q8 <0 (- 0 Q@ D0 -- 0 QH L0 0 QP T0  0 QX \0 | ` 0 Q` d0 0 Qh l0 0 Qp t0 0 Qx |0 0 Q 0@Y W  !  PӔO *:*"! #* :*QR S p$$!$ C?7/@P DLP7 P`KЍ@PLPDLP P?@F xtt`\\@<<O-4M 0KP` @P K P  p$0K P(0 P$0 P 0 P0 P0 P   0 R pg40 Q 0$ pQpj 0Pc P (  0PR 0PH P $  0P7 0P- P  0P 0P9  KT2P pH 7/K(3$ p D@@O-{M$0KP `p P K (0K@ P,0K P00K P |@ 40K@ P80K @ P<0K P    @0K@ PD0K PH0K P    W       L0K  Ph0`K p PPPpK$d0KPf PSh0K PLh d H  4D 0 @ , < ( 8 $          L  P8P<  hp@oR4  Z `K`xPTX\ (0@holpt|@@DoHL$,4@8o< |0PЀpܐ删d@KPd0K PgL d H D @ 0 , ( $ 4pP8P< @o `K\  0KZ$(,`  @l o p  t @ ox H  @L o P T h@048<|X d|D@ PK Ph0K Pl0K Pp0K Pt0K Px0K P, ( $ 0 4 8 < @ D H l p t x LPdph|T`` KXZ\ $(,48<lp0 t@00xD00KL|H  P0@K@ 4/K /AAF)<< H(p(TW                @ hFP!FX9PEFIFhT0H-@PPP PP PP PP PP PP PP PP P 0AO-MԀ@ X*KPpHGaVA*IV`1pa#V V:* G!0X GQ:HP* 2 RU  KU!pH`C!H0C gQ C\FO-MԀ@ X*KPpHGaVA*IV`1pa#V V:* G!0X GQ:HP* 2 RU  KU!pH`C!H0C gQ C\FO-MԀ@ X*KPpHGaVA*IV`1pa#V V:* G!0X GQ:HP* 2 RU  KU!pH`C!H0C gQ C\FO-MԀ@ X*KPpHGaVA*IV`1pa#V V:* G!0X GQ:HP* 2 RU  KU!pH`C!H0C gQ C\FH- 0H-P@  A 8 ,H- H-    H- %s:%d %s was not true./home/kerigan/projects/tflite/tensorflow/tensorflow/lite/kernels/unidirectional_sequence_lstm.ccparams->cell_clip >= 0params->proj_clip >= 0%s:%d %s != %s (%d != %d)input_to_input_weights->dims->size2input_to_input_weights->dims->data[0]n_cellinput_to_input_weights->dims->data[1]n_inputinput_to_forget_weights->dims->sizeinput_to_forget_weights->dims->data[0]input_to_forget_weights->dims->data[1]input_to_cell_weights->dims->sizeinput_to_cell_weights->dims->data[0]input_to_cell_weights->dims->data[1]recurrent_to_input_weights->dims->size1recurrent_to_input_weights->dims->data[1]n_output%s:%d %s != %s (%s != %s)recurrent_to_input_weights->typeinput_to_forget_weights->typerecurrent_to_input_weights->dims->data[0]recurrent_to_forget_weights->dims->sizerecurrent_to_forget_weights->dims->data[1]recurrent_to_forget_weights->typerecurrent_to_cell_weights->dims->sizerecurrent_to_cell_weights->dims->data[1]recurrent_to_cell_weights->typecifg_weights_all_or_none == truecell_to_input_weights->dims->sizecell_to_input_weights->dims->data[0]cell_to_input_weights->typeis_integer ? kTfLiteInt16 : input_to_forget_weights->typecell_to_forget_weights->dims->sizecell_to_forget_weights->dims->data[0]cell_to_forget_weights->typecell_to_output_weights->dims->sizecell_to_output_weights->dims->data[0]cell_to_output_weights->typepeephole_weights_all_or_none == trueinput_gate_biasnullptrinput_gate_bias->dims->sizeinput_gate_bias->dims->data[0]input_gate_bias->typekTfLiteInt32kTfLiteFloat32forget_gate_bias->dims->sizeforget_gate_bias->dims->data[0]forget_gate_bias->typecell_gate_bias->dims->sizecell_gate_bias->dims->data[0]cell_gate_bias->typeoutput_gate_bias->dims->sizeoutput_gate_bias->dims->data[0]output_gate_bias->typeprojection_weights->dims->sizeprojection_weights->dims->data[0]projection_weights->dims->data[1]projection_bias->dims->sizeprojection_bias->dims->data[0]projection_bias->typeprojecton_tensors_consistent == trueinput_layer_norm_coefficientsinput_layer_norm_coefficients != nullptrinput_layer_norm_coefficients->dims->sizeinput_layer_norm_coefficients->dims->data[0]input_layer_norm_coefficients->typekTfLiteInt16forget_layer_norm_coefficients->dims->sizeforget_layer_norm_coefficients->dims->data[0]forget_layer_norm_coefficients->typecell_layer_norm_coefficients->dims->sizecell_layer_norm_coefficients->dims->data[0]cell_layer_norm_coefficients->typeoutput_layer_norm_coefficients->dims->sizeoutput_layer_norm_coefficients->dims->data[0]output_layer_norm_coefficients->typeweight_shape.DimensionsCount()The LSTM Full kernel expects 20 or 24 inputs. Got %d inputsnode->outputs->sizeinput->dims->size > 1input_to_output_weights->dims->sizeinput_to_output_weights->dims->data[1]recurrent_to_output_weights->dims->sizerecurrent_to_output_weights->typeinput_to_output_weights->typerecurrent_to_output_weights->dims->data[0]output_state != nullptrcell_state != nullptrNumElements(output_state)n_batch * n_outputNumElements(cell_state)n_batch * n_cellnum_intermediate_tensors == 5Lstm_row_sumsType %s is not currently supported.cell_state->quantization.type != kTfLiteNoQuantizationoutput_tensor->quantization.type != kTfLiteNoQuantizationintermediate->quantization.type != kTfLiteNoQuantizationhidden->quantization.type != kTfLiteNoQuantizationCheckedLog2(cell_state->params.scale, &cell_scale)vectorclang version 18.1.8A?aeabi5C2.09 A   "$&  !#$%&()*+,-/01245679:;< t=a= x=)w=l=#=K=T|&= =@$=$ D&=8=Pfd'=\'="=%=;%='=E$*=sG*=}Hq =(=\z=!=L=V+%+=XP"=5hr&=c)=!="=m E= =<$%=F\#=&=I=e:=S#=%y(&== ]k%=\s= =l6,=q={=N= =C=i=2 =R=i=a===c ==3 =Y*"=uL"=n= =Q=%==S)=+*=#U-=I$=e =+=.=A %=1 )=Z ,=C #= += .=9 %=}8!U' = P!M's'X9p  E 101&1 =k1 2F <=$2m21 =u $= '=2=3c343 (=445)_ += "=[P55A =E = =5](9 =! =k = =) =, =X9-8>S@>od>l>hE^ 7= := 9=l 3=; 3=Y\KEIIMdT: $=hTtT!0> C  _;###n =(=(D(* */ /3 /4O4(499+9@g.P@("  hDA C + r P!jS ,  . \"o \"X \"\"bef I 1hTS"#0"4"9y L"( $"/D    Xd`4\HX8    h  h x , p |  P `  4@\tx| $0lptxH,DHL!"# $% P()H,LPT-X0125,X0\8`2d;<,=>8DA0B2E\`dHhAlptIx|0JK<LNAQ 0RK8U\0`XdYh\]` 0$(a,K0A48<b@DXHcL0PTX\d`Adhlept0xf|Yfc0gAh0iYic0jAk0lYlc 0m $(,n0,48<o@DHLpPATX\q`,d0hrlYptrxc|0st]uvAw0xyxc0zA{ 0|y| c$0(,04}8A<@D~HL0PTyX\`cd0hlptxA|0yc0  4 L     !!!!$!(!0!4!8!>>>>>>??H?X?AAAAHB\BpBBBBBBC0CDChCCCCCCDDDELE`EdEtExE|EEEEEEEEEEEEEEEEEEEE F0FHFdFFFFFFGGlGGGGH,HPHpHHHHI$IIIIIIIIIJ$J@J\JtJJJJJJKK8KTKlKKKKKKKL,LLLM 0M DM XM lM M M M M M @N  P 0PP R R8RTRpRRR4S 0T @TdTtT*P**** **** *(*,*00*88*@@* 4H\p**tTX*tTX*tTX*tTX**4<@D`H`*** `* $(`,`** 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@4~@ET @tE9pUH5 @EkkEU: $HE V pV  lE kkE V\  E p8X EkkEi @X\e  E pY ԔEkkER Y\N  E p[ EkkE[\  Epd\~ 4E kkEMl\I DE#p\# TE%kkEs \L- d8E(i \e E* p\( E,klE \$ E/ p ]/ ĕE1k,lE(]0 ԕ(E4pX]4 E6k@lE`]  E9Cpx]9? E;2]u j0 @, E>nLo(k^0(k>k~p>k@ LoLETl/4937 1749669147 1000 1000 100644 10884 ` ELF((4(0H-@0P 3/0Q/O-\M 0S) 0S2 0K @PP$0K P(0K P,0K P00K pP! Kt@p(px` dXp0=0P P@L(Lx` @Xp0>0PpP @6/K $ 0Xp`SJ0,`SV(`\b`Vp0\}P0`V 0 S0S40K` PX   `04 `3/P$ PP P K&vP Fp0Y0@p@ `5/Kpp&pFp dV@0Z0P0 `7/K<<&inputs->size5node->outputs->size1input->dims->data[2]input_weights->dims->data[1]input_weights->dims->data[0]bias->dims->data[0]recurrent_weights->dims->data[0]recurrent_weights->dims->data[1]%s:%d %s != %s (%s != %s)input->typekTfLiteFloat32input_weights->typerecurrent_weights->typeNumDimensions(hidden_state)2hidden_state->dims->data[0]batch_sizehidden_state->dims->data[1]num_units%s:%d %s was not true.hidden_state != nullptrType %s not currently supported.clang version 18.1.8A?aeabi5C2.09 A   "$&0 `zkI,&!)!d apJ?"   @ yW-5E!tR0Z@T=@P W 0@ \-&L),,,,,t-. /,/x//0.1$2P12133D4p1.418.41.@ 4P .                                     $ ( , 0 4 8 < X 6X 6$ 6 68880,T,p,,:-1101L1h117\5p/ !$'******** ' *$*(*(*0*0*%(+ 9%(+9$TfLiteIntArrayCopyTfLiteIntArrayEqualsArray.rel.ARM.exidx_ZN6tflite3ops7builtin27unidirectional_sequence_rnn4FreeEP13TfLiteContextPv_ZdlPv_ZN6tflite3ops7builtin36Register_UNIDIRECTIONAL_SEQUENCE_RNNEv.rel.text.comment.linker-options.ARM.attributes.L.str_ZN6tflite16GetTemporarySafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite13GetOutputSafeEPK13TfLiteContextPK10TfLiteNodeiPP12TfLiteTensor_ZN6tflite12GetInputSafeEPK13TfLiteContextPK10TfLiteNodeiPPK12TfLiteTensor_ZZN6tflite3ops7builtin36Register_UNIDIRECTIONAL_SEQUENCE_RNNEvE1rTfLiteIntArrayEqual.note.GNU-stack_Znwj_ZN6tflite3ops7builtin27unidirectional_sequence_rnn4InitEP13TfLiteContextPKcj_ZN6tflite16GetVariableInputEP13TfLiteContextPK10TfLiteNodei.llvm_addrsigTfLiteIntArrayCreateTfLiteTypeGetNameTfLiteIntArrayFree_ZN6tflite3ops7builtin27unidirectional_sequence_rnn4EvalEP13TfLiteContextP10TfLiteNode_ZN6tflite3ops7builtin27unidirectional_sequence_rnn7PrepareEP13TfLiteContextP10TfLiteNodeunidirectional_sequence_rnn.cc.ARM.extab.strtab.symtab_ZN6tflite3ops7builtin27unidirectional_sequence_rnn10EvalHybridEPK12TfLiteTensorS5_S5_S5_PK23TfLiteSequenceRNNParamsPS3_S9_S9_S9_S9_S9_S9_S9_Pb_ZN6tflite12kernel_utils12RnnBatchStepEPKfPKafS4_fS2_iiii21TfLiteFusedActivationPaS6_PfS7_S7_bPiS8_S8_Pb.rel.data_ZN6tflite3ops7builtin27unidirectional_sequence_rnn9EvalFloatEPK12TfLiteTensorS5_S5_S5_PK23TfLiteSequenceRNNParamsPS3_S9__ZN6tflite12kernel_utils12RnnBatchStepEPKfS2_S2_S2_iiii21TfLiteFusedActivationPfS4_.L.str.19.L.str.9.L.str.18.L.str.8.L.str.17.L.str.7.L.str.16.L.str.6.L.str.25.L.str.15.L.str.5$d.5.L.str.24.L.str.14.L.str.4$a.4.L.str.23.L.str.13.L.str.3$d.3.L.str.22.L.str.12.L.str.2$a.2__aeabi_unwind_cpp_pr1.L.str.21.L.str.11.L.str.1$d.1.rodata.str1.1__aeabi_unwind_cpp_pr0.L.str.20.L.str.10$a.0 54 @@2p8. @( 28f0 @ Lo0Dp@Lo (%unique.cc.o/ 1749669150 1000 1000 100644 38132 ` ELF(4(i//pL- M R# 0S! 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