[参考译文] TDA4VM：TIDL 推理在8.5中失败、但对于某些 TFLITE 模型来说是在8.4中有效的

tidl_tools_path                                 = /home/ti-proc-rtos-8-5/tidl_j721e_08_05_00_16/tidl_tools
artifacts_folder                                = ./ARTIF/artif_YDET
tidl_tensor_bits                                = 8
debug_level                                     = 0
num_tidl_subgraphs                              = 16
tidl_denylist                                   = 114   6
tidl_denylist_layer_name                        =
tidl_denylist_layer_type                         =
model_type                                      =
tidl_calibration_accuracy_level                 = 64
tidl_calibration_options:num_frames_calibration = 1
tidl_calibration_options:bias_calibration_iterations = 1
mixed_precision_factor = -1.000000
model_group_id = 0
power_of_2_quantization                         = 2
enable_high_resolution_optimization             = 0
pre_batchnorm_fold                              = 1
add_data_convert_ops                          = 0
output_feature_16bit_names_list                 =
m_params_16bit_names_list                       =
reserved_compile_constraints_flag               = 1601
ti_internal_reserved_1                          =

 Number of subgraphs:1 , 73 nodes delegated out of 77 nodes

WARNING : Pad layer won't be merged in the succeeding layer, it will be treated as a stand alone layer
WARNING : Pad layer won't be merged in the succeeding layer, it will be treated as a stand alone layer
WARNING : Pad layer won't be merged in the succeeding layer, it will be treated as a stand alone layer
WARNING : Pad layer won't be merged in the succeeding layer, it will be treated as a stand alone layer
WARNING : Pad layer won't be merged in the succeeding layer, it will be treated as a stand alone layer

 ************** Frame index 1 : Running float import *************
IMPORT nb operations : Total Giga Macs : 5.2293   , network file ./ARTIF/artif_YDET/tempDir/136_tidl_net.bin_netLog.txt
INFORMATION: [TIDL_ResizeLayer] model/lambda/resize/ResizeNearestNeighbor Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
INFORMATION: [TIDL_ResizeLayer] model/lambda_1/resize/ResizeNearestNeighbor Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
WARNING: [TIDL_E_DATAFLOW_INFO_NULL] Network compiler returned with error or didn't executed, this model can only be used on PC/Host emulation mode, it is not expected to work on target/EVM.
****************************************************
**          3 WARNINGS          0 ERRORS          **
****************************************************
The soft limit is 2048
The hard limit is 2048
MEM: Init ... !!!
MEM: Init ... Done !!!
 0.0s:  VX_ZONE_INIT:Enabled
 0.11s:  VX_ZONE_ERROR:Enabled
 0.15s:  VX_ZONE_WARNING:Enabled
 0.1689s:  VX_ZONE_INIT:[tivxInit:184] Initialization Done !!!
INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
------debug ---------
TENSOR details : input  name=inputs:0   index=137  shape=[  1 512 608   3]  type=<class 'numpy.float32'>  nb_of_elem=933888
TENSOR details : output  name=Identity_2:0   index=138  shape=[ 1 64 76  5]  type=<class 'numpy.float32'>  nb_of_elem=24320
TENSOR details : output  name=Identity_1:0   index=139  shape=[ 1 32 38  5]  type=<class 'numpy.float32'>  nb_of_elem=6080
TENSOR details : output  name=Identity:0   index=140  shape=[ 1 16 19  5]  type=<class 'numpy.float32'>  nb_of_elem=1520
TENSOR=input calibration tensor 0   size=933888 shape=(1, 512, 608, 3) min=0.000 max=1.000  :   0.1171 0.9406 0.0156 0.6484 0.5904  ... 0.1409 0.2720  ... 0.7644 0.8286 0.7213 0.8195

 ************ Frame index 1 : Running fixed point mode for calibration ****************
IMPORT nb operations : Total Giga Macs : 5.2293   , network file ./ARTIF/artif_YDET/tempDir/136_tidl_net.bin_netLog.txt
IMPORT nb operations : Total Giga Macs : 5.2293   , network file ./ARTIF/artif_YDET/tempDir/136_tidl_net.bin_netLog.txt

~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~

Processing config file #0 : /home/calll81z/jacinto/ARTIF/artif_YDET/tempDir/136_tidl_io_.qunat_stats_config.txt
 ----------------------- TIDL Process with REF_ONLY FLOW ------------------------

#    0 . .. T   15607.59  .... ..... ... .... .....IMPORT nb operations : Total Giga Macs : 5.2293   , network file ./ARTIF/artif_YDET/tempDir/136_tidl_net.bin_netLog.txt

~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~

Processing config file #0 : /home/calll81z/jacinto/ARTIF/artif_YDET/tempDir/136_tidl_io_.qunat_stats_config.txt
 ----------------------- TIDL Process with REF_ONLY FLOW ------------------------

#    0 . .. T   16733.15  .... ..... ... .... .....


 *****************   Calibration iteration number 0 completed ************************



IMPORT nb operations : Total Giga Macs : 5.2293   , network file ./ARTIF/artif_YDET/tempDir/136_tidl_net.bin_netLog.txt

------------------ Network Compiler Traces -----------------------------
successful Memory allocation
Rerunning network compiler

------------------ Network Compiler Traces -----------------------------
successful Memory allocation
INFORMATION: [TIDL_ResizeLayer] model/lambda/resize/ResizeNearestNeighbor Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
INFORMATION: [TIDL_ResizeLayer] model/lambda_1/resize/ResizeNearestNeighbor Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize.
****************************************************
**          2 WARNINGS          0 ERRORS          **
****************************************************
 import done ... copying model  ../SHARE/ydet/ydet_reduced_int8.tflite  to artifact dir ./ARTIF/artif_YDET

 end import
IMPORT num_of_calib_tensors=1  accuracy_level=0  calibration_iterations=1


MEM: Deinit ... !!!
MEM: Alloc's: 29 alloc's of 339652644 bytes
MEM: Free's : 29 free's  of 339652644 bytes
MEM: Open's : 0 allocs  of 0 bytes
MEM: Deinit ... Done !!!
... end tool ...