PROCESSOR-SDK-AM68A: TIDL_RT_OVX: ERROR: Verify OpenVX graph failed

Ahmed Mujtaba

Part Number: PROCESSOR-SDK-AM68A
Other Parts Discussed in Thread: AM68A

Hi,

I am running a segmentation model on TI-EVM for AM68A. The artifacts are successfully generated using edgeai-benchmark without any errors.

During the inference on TI board, I recieved this error,

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

APP: Init ... !!!
MEM: Init ... !!!
MEM: Initialized DMA HEAP (fd=4) !!!
MEM: Init ... Done !!!
IPC: Init ... !!!
IPC: Init ... Done !!!
REMOTE_SERVICE: Init ... !!!
REMOTE_SERVICE: Init ... Done !!!
14120.976291 s: GTC Frequency = 200 MHz
APP: Init ... Done !!!
14120.976366 s: VX_ZONE_INIT:Enabled
14120.976378 s: VX_ZONE_ERROR:Enabled
14120.976386 s: VX_ZONE_WARNING:Enabled
14120.977218 s: VX_ZONE_INIT:[tivxInitLocal:130] Initialization Done !!!
14120.978125 s: VX_ZONE_INIT:[tivxHostInitLocal:93] Initialization Done for HOST !!!
14121.132763 s: VX_ZONE_ERROR:[ownContextSendCmd:799] Command ack message returned failure cmd_status: -1
14121.132797 s: VX_ZONE_ERROR:[ownContextSendCmd:835] tivxEventWait() failed.
14121.132824 s: VX_ZONE_ERROR:[ownNodeKernelInit:527] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
14121.132835 s: VX_ZONE_ERROR:[ownNodeKernelInit:528] Please be sure the target callbacks have been registered for this core
14121.132843 s: VX_ZONE_ERROR:[ownNodeKernelInit:529] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
14121.132854 s: VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl:1:1 ... failed !!!
14121.132872 s: VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
14121.132882 s: VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
TIDL_RT_OVX: ERROR: Verify OpenVX graph failed

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

Can you guide me to solve this issue?

Thanks,

Ahmed

over 2 years ago

0 Nikhil Dasan over 2 years ago

TI__Guru* 88071 points

Hi Ahmed,

Could you please refer the below FAQ and check if it is the same issue?

https://e2e.ti.com/support/processors-group/processors/f/processors-forum/1227571/faq-sk-tda4vm-error-while-running-custom-compiled-model

Regards,

Nikhil

0 Ahmed Mujtaba over 2 years ago in reply to Nikhil Dasan

Prodigy 235 points

Hi Nikhil,

Yes, the issue seems to be related but the solutions that are provided are already tried from my side.

Another thing, I want to mention is that while I was generating artifacts, I received the warning shown below,

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

NC running for device: 1
Running with OTF buffer optimizations
Segmentation fault (core dumped)
Could not open /home/edgeai/code/edgeai-modelzoo/modelartifacts/AM68A/8bits/segmentation/artifacts/tempDir/output_tidl_net/perfSimInfo.bin
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.

/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////

This warning does not hinder the artifacts generation, and the artifacts are successfully emulated on PC environment. However, when ported to TI-EVM, the inference throws the error.

Thanks,

Ahmed

0 Pratik Kedar over 2 years ago in reply to Ahmed Mujtaba

TI__Mastermind 24041 points

Hi,

Can you please confirm my understanding on this thread,

1. You able to generate the model artifacts

2. Host side inference is fine

3. Target side inference is failing with above logs ?

Ahmed Mujtaba said:
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.

I suspect model compilation is not successful in this case.

Can you share model compilation logs with debug flag set to 2.

Also which flow you are using for model artifacts generation (TIDL-RT or OSRT), what sdk version you are using ?

0 Ahmed Mujtaba over 2 years ago in reply to Pratik Kedar

Prodigy 235 points

Hi,

Pratik Kedar said:
1. You able to generate the model artifacts

Yes, we are able to generate artifacts.

Pratik Kedar said:
2. Host side inference is fine

Yes.

Pratik Kedar said:
3. Target side inference is failing with above logs ?

While generating artifacts on PC, we got this warning,

NC running for device: 1
Running with OTF buffer optimizations
Segmentation fault (core dumped)
Could not open /home/edgeai/code/edgeai-modelzoo/modelartifacts/AM68A/8bits/segmentation/artifacts/tempDir/output_tidl_net/perfSimInfo.bin
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.

While inference on TI EVM, we got this error,

 APP: Init ... !!!
MEM: Init ... !!!
MEM: Initialized DMA HEAP (fd=4) !!!
MEM: Init ... Done !!!
IPC: Init ... !!!
IPC: Init ... Done !!!
REMOTE_SERVICE: Init ... !!!
REMOTE_SERVICE: Init ... Done !!!
14120.976291 s: GTC Frequency = 200 MHz
APP: Init ... Done !!!
14120.976366 s: VX_ZONE_INIT:Enabled
14120.976378 s: VX_ZONE_ERROR:Enabled
14120.976386 s: VX_ZONE_WARNING:Enabled
14120.977218 s: VX_ZONE_INIT:[tivxInitLocal:130] Initialization Done !!!
14120.978125 s: VX_ZONE_INIT:[tivxHostInitLocal:93] Initialization Done for HOST !!!
14121.132763 s: VX_ZONE_ERROR:[ownContextSendCmd:799] Command ack message returned failure cmd_status: -1
14121.132797 s: VX_ZONE_ERROR:[ownContextSendCmd:835] tivxEventWait() failed.
14121.132824 s: VX_ZONE_ERROR:[ownNodeKernelInit:527] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode
14121.132835 s: VX_ZONE_ERROR:[ownNodeKernelInit:528] Please be sure the target callbacks have been registered for this core
14121.132843 s: VX_ZONE_ERROR:[ownNodeKernelInit:529] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel
14121.132854 s: VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl:1:1 ... failed !!!
14121.132872 s: VX_ZONE_ERROR:[vxVerifyGraph:2055] Node kernel init failed
14121.132882 s: VX_ZONE_ERROR:[vxVerifyGraph:2109] Graph verify failed
TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!!
TIDL_RT_OVX: ERROR: Verify OpenVX graph failed

Pratik Kedar said:
Can you share model compilation logs with debug flag set to 2.

Yes.

target_device/SOC: AM68A
Pass the appropriate commandline argument to use another target_device
-------------------------------------------------------------------
argv: ['./scripts/benchmark_modelzoo.py', 'settings_import_on_pc.yaml', '--target_device', 'AM68A']
settings: {'include_files': None, 'pipeline_type': 'accuracy', 'num_frames': 1, 'calibration_frames': 1, 'calibration_iterations': 1, 'configs_path': './configs', 'models_path': './edgeai-modelzoo/models', 'modelartifacts_path': './edgeai-benchmark/work_dirs/modelartifacts/AM68A', 'datasets_path': './dependencies/datasets', 'target_device': 'AM68A', 'target_machine': 'pc', 'run_suffix': None, 'parallel_devices': 1, 'tensor_bits': 8, 'runtime_options': {'debug_level': 2}, 'run_import': True, 'run_inference': True, 'run_missing': True, 'detection_threshold': 0.3, 'detection_top_k': 200, 'detection_nms_threshold': None, 'detection_keep_top_k': None, 'save_output': True, 'num_output_frames': 50, 'model_selection': ['segmentation_unet'], 'model_shortlist': None, 'model_exclusion': None, 'task_selection': 'segmentation', 'runtime_selection': None, 'session_type_dict': {'onnx': 'onnxrt', 'tflite': 'tflitert', 'mxnet': 'tvmdlr'}, 'dataset_type_dict': {'ade20k': 'ade_20k'}, 'dataset_selection': 'ade20k32', 'dataset_loading': True, 'config_range': None, 'enable_logging': True, 'verbose': False, 'capture_log': False, 'experimental_models': False, 'rewrite_results': False, 'with_udp': False, 'flip_test': False, 'model_transformation_dict': None, 'report_perfsim': False, 'tidl_offload': True, 'input_optimization': None, 'run_dir_tree_depth': None, 'settings_file': 'settings_import_on_pc.yaml', 'basic_keys': ['include_files', 'pipeline_type', 'num_frames', 'calibration_frames', 'calibration_iterations', 'configs_path', 'models_path', 'modelartifacts_path', 'datasets_path', 'target_device', 'target_machine', 'run_suffix', 'parallel_devices', 'tensor_bits', 'runtime_options', 'run_import', 'run_inference', 'run_missing', 'detection_threshold', 'detection_top_k', 'detection_nms_threshold', 'detection_keep_top_k', 'save_output', 'num_output_frames', 'model_selection', 'model_shortlist', 'model_exclusion', 'task_selection', 'runtime_selection', 'session_type_dict', 'dataset_type_dict', 'dataset_selection', 'dataset_loading', 'config_range', 'enable_logging', 'verbose', 'capture_log', 'experimental_models', 'rewrite_results', 'with_udp', 'flip_test', 'model_transformation_dict', 'report_perfsim', 'tidl_offload', 'input_optimization', 'run_dir_tree_depth', 'settings_file'], 'dataset_cache': None}
work_dir: ./edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits
[34m
INFO:[33m20231129-015533: dataset exists - will reuse - [39m./dependencies/datasets/ADEChallengeData2016
download_ok: True
configs to run: ['segmentation_dev_Unet_V1.1_onnx']
number of configs: 1


TASKS                                                       |   0%|          || 0/1 [00:00<?, ?it/s][A
TASKS                                                       |          |     0% 0/1| [< ][34m
INFO:[33m20231129-015533: starting process on parallel_device - [39m0
[34m
INFO:[33m20231129-015533: starting - [39msegmentation_dev_Unet_V1.1_onnx
[34mINFO:[33m20231129-015533: model_path - [39m/home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-modelzoo/models/vision/segmentation/ade20k32/edgeai-tv/segmentation_DV_Segmentation_dev_Unet_V1.1.onnx
[34mINFO:[33m20231129-015533: model_file - [39m/home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/model/segmentation_DV_Segmentation_dev_Unet_V1.1.onnx
[34m
INFO:[33m20231129-015533: running - [39msegmentation_dev_Unet_V1.1_onnx[34m
INFO:[33m20231129-015533: pipeline_config - [39m{'task_type': 'segmentation', 'dataset_category': 'ade20k32', 'calibration_dataset': <edgeai_benchmark.datasets.ade20k.ADE20KSegmentation object at 0x7f96a8ee82b0>, 'input_dataset': <edgeai_benchmark.datasets.ade20k.ADE20KSegmentation object at 0x7f96a8ee8908>, 'preprocess': <edgeai_benchmark.preprocess.PreProcessTransforms object at 0x7f96a8ee8c18>, 'session': <edgeai_benchmark.sessions.onnxrt_session.ONNXRTSession object at 0x7f97123c5048>, 'postprocess': <edgeai_benchmark.postprocess.PostProcessTransforms object at 0x7f97123c50b8>, 'model_info': {'metric_reference': {'accuracy_mean_iou%': 50.85}, 'model_shortlist': None}}[34m
INFO:[33m20231129-015533: import  - [39msegmentation_dev_Unet_V1.1_onnx - this may take some time...tidl_tools_path                                 = /home/edgeai/code/edgeai-benchmark_v8.6_mod/tools/AM68A/tidl_tools 
artifacts_folder                                = /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts 
tidl_tensor_bits                                = 8 
debug_level                                     = 2 
num_tidl_subgraphs                              = 16 
tidl_denylist                                   = 
tidl_denylist_layer_name                        = 
tidl_denylist_layer_type                         = 
tidl_allowlist_layer_name                        = 
model_type                                      =  
tidl_calibration_accuracy_level                 = 7 
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                          = 3 
output_feature_16bit_names_list                 =  
m_params_16bit_names_list                       =  
reserved_compile_constraints_flag               = 1601 
ti_internal_reserved_1                          = 

 ****** WARNING : Network not identified as Object Detection network : (1) Ignore if network is not Object Detection network (2) If network is Object Detection network, please specify "model_type":"OD" as part of OSRT compilation options******

Supported TIDL layer type ---            Cast --  
Supported TIDL layer type ---             Add --  
Supported TIDL layer type ---             Mul --  
Supported TIDL layer type ---            Conv -- /backbone/net/p1/p1.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p1/p1.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p1/p1.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.1/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.1/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.1/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.1/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.1/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.1/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p2/p2.1/res_m.0/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p2/p2.1/res_m.1/Add 
Supported TIDL layer type ---          Concat -- /backbone/net/p2/p2.1/Concat 
Supported TIDL layer type ---            Conv -- /backbone/net/p2/p2.1/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p2/p2.1/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p2/p2.1/conv3/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p3/p3.1/res_m.0/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p3/p3.1/res_m.1/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p3/p3.1/res_m.2/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p3/p3.1/res_m.3/Add 
Supported TIDL layer type ---          Concat -- /backbone/net/p3/p3.1/Concat 
Supported TIDL layer type ---            Conv -- /backbone/net/p3/p3.1/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p3/p3.1/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p3/p3.1/conv3/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p4/p4.1/res_m.0/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p4/p4.1/res_m.1/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p4/p4.1/res_m.2/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p4/p4.1/res_m.3/Add 
Supported TIDL layer type ---          Concat -- /backbone/net/p4/p4.1/Concat 
Supported TIDL layer type ---            Conv -- /backbone/net/p4/p4.1/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p4/p4.1/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p4/p4.1/conv3/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.1/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.1/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.1/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.1/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.1/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.1/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p5/p5.1/res_m.0/Add 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---             Add -- /backbone/net/p5/p5.1/res_m.1/Add 
Supported TIDL layer type ---          Concat -- /backbone/net/p5/p5.1/Concat 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.1/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.1/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.1/conv3/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.2/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.2/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.2/conv1/relu/Mul 
Supported TIDL layer type ---         MaxPool -- /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0/MaxPool 
Supported TIDL layer type ---         MaxPool -- /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1/MaxPool 
Supported TIDL layer type ---         MaxPool -- /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0_1/MaxPool 
Supported TIDL layer type ---         MaxPool -- /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1_1/MaxPool 
Supported TIDL layer type ---         MaxPool -- /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0_2/MaxPool 
Supported TIDL layer type ---         MaxPool -- /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1_2/MaxPool 
Supported TIDL layer type ---          Concat -- /backbone/net/p5/p5.2/Concat 
Supported TIDL layer type ---            Conv -- /backbone/net/p5/p5.2/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/net/p5/p5.2/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/net/p5/p5.2/conv2/relu/Mul 
Supported TIDL layer type ---          Resize -- /backbone/fpn/up/Resize 
Supported TIDL layer type ---          Concat -- /backbone/fpn/Concat 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h1/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h1/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h1/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h1/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h1/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h1/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h1/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h1/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h1/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h1/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h1/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h1/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h1/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h1/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h1/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h1/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h1/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h1/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---          Concat -- /backbone/fpn/h1/Concat 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h1/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h1/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h1/conv3/relu/Mul 
Supported TIDL layer type ---          Resize -- /backbone/fpn/up_1/Resize 
Supported TIDL layer type ---          Concat -- /backbone/fpn/Concat_1 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h2/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h2/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h2/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h2/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h2/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h2/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h2/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h2/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h2/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h2/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h2/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h2/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h2/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h2/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h2/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h2/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h2/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h2/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---          Concat -- /backbone/fpn/h2/Concat 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h2/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h2/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h2/conv3/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h3/relu/Mul 
Supported TIDL layer type ---          Concat -- /backbone/fpn/Concat_2 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h4/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h4/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h4/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h4/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h4/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h4/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h4/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h4/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h4/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h4/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h4/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h4/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h4/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h4/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h4/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h4/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h4/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h4/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---          Concat -- /backbone/fpn/h4/Concat 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h4/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h4/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h4/conv3/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h5/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h5/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h5/relu/Mul 
Supported TIDL layer type ---          Concat -- /backbone/fpn/Concat_3 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h6/conv1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h6/conv1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h6/conv1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h6/conv2/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h6/conv2/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h6/conv2/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h6/res_m.0/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h6/res_m.0/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h6/res_m.0/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h6/res_m.0/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h6/res_m.0/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h6/res_m.0/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h6/res_m.1/res_m/res_m.0/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h6/res_m.1/res_m/res_m.0/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h6/res_m.1/res_m/res_m.0/relu/Mul 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h6/res_m.1/res_m/res_m.1/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h6/res_m.1/res_m/res_m.1/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h6/res_m.1/res_m/res_m.1/relu/Mul 
Supported TIDL layer type ---          Concat -- /backbone/fpn/h6/Concat 
Supported TIDL layer type ---            Conv -- /backbone/fpn/h6/conv3/conv/Conv 
Supported TIDL layer type ---         Sigmoid -- /backbone/fpn/h6/conv3/relu/Sigmoid 
Supported TIDL layer type ---             Mul -- /backbone/fpn/h6/conv3/relu/Mul 
Supported TIDL layer type ---            Conv -- /decoder/conv/conv1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/conv/conv_branch/conv_branch.0/Relu 
Supported TIDL layer type ---            Conv -- /decoder/conv/conv_branch/conv_branch.1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/conv/conv_branch/conv_branch.3/Relu 
Supported TIDL layer type ---            Conv -- /decoder/conv/conv_branch/conv_branch.4/Conv 
Supported TIDL layer type ---             Add -- /decoder/conv/Add 
Supported TIDL layer type ---            Relu -- /decoder/conv/relu/Relu 
Supported TIDL layer type ---            Conv -- /decoder/conv1/Conv 
Supported TIDL layer type ---          Resize -- /decoder/upsample/Resize 
Supported TIDL layer type ---            Conv -- /decoder/ffm2/ftb1/conv1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm2/ftb1/conv_branch/conv_branch.0/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm2/ftb1/conv_branch/conv_branch.1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm2/ftb1/conv_branch/conv_branch.3/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm2/ftb1/conv_branch/conv_branch.4/Conv 
Supported TIDL layer type ---             Add -- /decoder/ffm2/ftb1/Add 
Supported TIDL layer type ---            Relu -- /decoder/ffm2/ftb1/relu/Relu 
Supported TIDL layer type ---             Add -- /decoder/ffm2/Add 
Supported TIDL layer type ---            Conv -- /decoder/ffm2/ftb2/conv1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm2/ftb2/conv_branch/conv_branch.0/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm2/ftb2/conv_branch/conv_branch.1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm2/ftb2/conv_branch/conv_branch.3/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm2/ftb2/conv_branch/conv_branch.4/Conv 
Supported TIDL layer type ---             Add -- /decoder/ffm2/ftb2/Add 
Supported TIDL layer type ---            Relu -- /decoder/ffm2/ftb2/relu/Relu 
Supported TIDL layer type ---          Resize -- /decoder/ffm2/upsample/Resize 
Supported TIDL layer type ---            Conv -- /decoder/ffm1/ftb1/conv1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm1/ftb1/conv_branch/conv_branch.0/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm1/ftb1/conv_branch/conv_branch.1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm1/ftb1/conv_branch/conv_branch.3/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm1/ftb1/conv_branch/conv_branch.4/Conv 
Supported TIDL layer type ---             Add -- /decoder/ffm1/ftb1/Add 
Supported TIDL layer type ---            Relu -- /decoder/ffm1/ftb1/relu/Relu 
Supported TIDL layer type ---             Add -- /decoder/ffm1/Add 
Supported TIDL layer type ---            Conv -- /decoder/ffm1/ftb2/conv1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm1/ftb2/conv_branch/conv_branch.0/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm1/ftb2/conv_branch/conv_branch.1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm1/ftb2/conv_branch/conv_branch.3/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm1/ftb2/conv_branch/conv_branch.4/Conv 
Supported TIDL layer type ---             Add -- /decoder/ffm1/ftb2/Add 
Supported TIDL layer type ---            Relu -- /decoder/ffm1/ftb2/relu/Relu 
Supported TIDL layer type ---          Resize -- /decoder/ffm1/upsample/Resize 
Supported TIDL layer type ---            Conv -- /decoder/ffm0/ftb1/conv1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm0/ftb1/conv_branch/conv_branch.0/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm0/ftb1/conv_branch/conv_branch.1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm0/ftb1/conv_branch/conv_branch.3/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm0/ftb1/conv_branch/conv_branch.4/Conv 
Supported TIDL layer type ---             Add -- /decoder/ffm0/ftb1/Add 
Supported TIDL layer type ---            Relu -- /decoder/ffm0/ftb1/relu/Relu 
Supported TIDL layer type ---             Add -- /decoder/ffm0/Add 
Supported TIDL layer type ---            Conv -- /decoder/ffm0/ftb2/conv1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm0/ftb2/conv_branch/conv_branch.0/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm0/ftb2/conv_branch/conv_branch.1/Conv 
Supported TIDL layer type ---            Relu -- /decoder/ffm0/ftb2/conv_branch/conv_branch.3/Relu 
Supported TIDL layer type ---            Conv -- /decoder/ffm0/ftb2/conv_branch/conv_branch.4/Conv 
Supported TIDL layer type ---             Add -- /decoder/ffm0/ftb2/Add 
Supported TIDL layer type ---            Relu -- /decoder/ffm0/ftb2/relu/Relu 
Supported TIDL layer type ---          Resize -- /decoder/ffm0/upsample/Resize 
Supported TIDL layer type ---            Conv -- /decoder/outconv/conv/Conv 
Supported TIDL layer type ---          Resize -- /decoder/outconv/upsample/Resize 

Preliminary subgraphs created = 1 
Final number of subgraphs created are : 1, - Offloaded Nodes - 314, Total Nodes - 314 
INFORMATION -- [TIDL_ResizeLayer]  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]  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]  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]  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]  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]  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]  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.  
Running runtimes graphviz - /home/edgeai/code/edgeai-benchmark_v8.6_mod/tools/AM68A/tidl_tools/tidl_graphVisualiser_runtimes.out /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts/allowedNode.txt /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts/tempDir/graphvizInfo.txt /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts/tempDir/runtimes_visualization.svg 
*** In TIDL_createStateImportFunc *** 
Compute on node : TIDLExecutionProvider_TIDL_0_0
  0,            Cast, 1, 1, inputNet_IN, TIDL_cast_in
  1,             Add, 2, 1, TIDL_cast_in, TIDL_Scale_In
  2,             Mul, 2, 1, TIDL_Scale_In, input
  3,            Conv, 3, 1, input, /backbone/net/p1/p1.0/conv/Conv_output_0
  4,         Sigmoid, 1, 1, /backbone/net/p1/p1.0/conv/Conv_output_0, /backbone/net/p1/p1.0/relu/Sigmoid_output_0
  5,             Mul, 2, 1, /backbone/net/p1/p1.0/conv/Conv_output_0, /backbone/net/p1/p1.0/relu/Mul_output_0
  6,            Conv, 3, 1, /backbone/net/p1/p1.0/relu/Mul_output_0, /backbone/net/p2/p2.0/conv/Conv_output_0
  7,         Sigmoid, 1, 1, /backbone/net/p2/p2.0/conv/Conv_output_0, /backbone/net/p2/p2.0/relu/Sigmoid_output_0
  8,             Mul, 2, 1, /backbone/net/p2/p2.0/conv/Conv_output_0, /backbone/net/p2/p2.0/relu/Mul_output_0
  9,            Conv, 3, 1, /backbone/net/p2/p2.0/relu/Mul_output_0, /backbone/net/p2/p2.1/conv1/conv/Conv_output_0
 10,         Sigmoid, 1, 1, /backbone/net/p2/p2.1/conv1/conv/Conv_output_0, /backbone/net/p2/p2.1/conv1/relu/Sigmoid_output_0
 11,             Mul, 2, 1, /backbone/net/p2/p2.1/conv1/conv/Conv_output_0, /backbone/net/p2/p2.1/conv1/relu/Mul_output_0
 12,            Conv, 3, 1, /backbone/net/p2/p2.0/relu/Mul_output_0, /backbone/net/p2/p2.1/conv2/conv/Conv_output_0
 13,         Sigmoid, 1, 1, /backbone/net/p2/p2.1/conv2/conv/Conv_output_0, /backbone/net/p2/p2.1/conv2/relu/Sigmoid_output_0
 14,             Mul, 2, 1, /backbone/net/p2/p2.1/conv2/conv/Conv_output_0, /backbone/net/p2/p2.1/conv2/relu/Mul_output_0
 15,            Conv, 3, 1, /backbone/net/p2/p2.1/conv2/relu/Mul_output_0, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/conv/Conv_output_0
 16,         Sigmoid, 1, 1, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
 17,             Mul, 2, 1, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/relu/Mul_output_0
 18,            Conv, 3, 1, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/conv/Conv_output_0
 19,         Sigmoid, 1, 1, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
 20,             Mul, 2, 1, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/relu/Mul_output_0
 21,             Add, 2, 1, /backbone/net/p2/p2.1/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p2/p2.1/res_m.0/Add_output_0
 22,            Conv, 3, 1, /backbone/net/p2/p2.1/res_m.0/Add_output_0, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/conv/Conv_output_0
 23,         Sigmoid, 1, 1, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
 24,             Mul, 2, 1, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/relu/Mul_output_0
 25,            Conv, 3, 1, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/conv/Conv_output_0
 26,         Sigmoid, 1, 1, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
 27,             Mul, 2, 1, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/relu/Mul_output_0
 28,             Add, 2, 1, /backbone/net/p2/p2.1/res_m.1/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p2/p2.1/res_m.1/Add_output_0
 29,          Concat, 4, 1, /backbone/net/p2/p2.1/conv1/relu/Mul_output_0, /backbone/net/p2/p2.1/Concat_output_0
 30,            Conv, 3, 1, /backbone/net/p2/p2.1/Concat_output_0, /backbone/net/p2/p2.1/conv3/conv/Conv_output_0
 31,         Sigmoid, 1, 1, /backbone/net/p2/p2.1/conv3/conv/Conv_output_0, /backbone/net/p2/p2.1/conv3/relu/Sigmoid_output_0
 32,             Mul, 2, 1, /backbone/net/p2/p2.1/conv3/conv/Conv_output_0, /backbone/net/p2/p2.1/conv3/relu/Mul_output_0
 33,            Conv, 3, 1, /backbone/net/p2/p2.1/conv3/relu/Mul_output_0, /backbone/net/p3/p3.0/conv/Conv_output_0
 34,         Sigmoid, 1, 1, /backbone/net/p3/p3.0/conv/Conv_output_0, /backbone/net/p3/p3.0/relu/Sigmoid_output_0
 35,             Mul, 2, 1, /backbone/net/p3/p3.0/conv/Conv_output_0, /backbone/net/p3/p3.0/relu/Mul_output_0
 36,            Conv, 3, 1, /backbone/net/p3/p3.0/relu/Mul_output_0, /backbone/net/p3/p3.1/conv1/conv/Conv_output_0
 37,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/conv1/conv/Conv_output_0, /backbone/net/p3/p3.1/conv1/relu/Sigmoid_output_0
 38,             Mul, 2, 1, /backbone/net/p3/p3.1/conv1/conv/Conv_output_0, /backbone/net/p3/p3.1/conv1/relu/Mul_output_0
 39,            Conv, 3, 1, /backbone/net/p3/p3.0/relu/Mul_output_0, /backbone/net/p3/p3.1/conv2/conv/Conv_output_0
 40,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/conv2/conv/Conv_output_0, /backbone/net/p3/p3.1/conv2/relu/Sigmoid_output_0
 41,             Mul, 2, 1, /backbone/net/p3/p3.1/conv2/conv/Conv_output_0, /backbone/net/p3/p3.1/conv2/relu/Mul_output_0
 42,            Conv, 3, 1, /backbone/net/p3/p3.1/conv2/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/conv/Conv_output_0
 43,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
 44,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/relu/Mul_output_0
 45,            Conv, 3, 1, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/conv/Conv_output_0
 46,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
 47,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/relu/Mul_output_0
 48,             Add, 2, 1, /backbone/net/p3/p3.1/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.0/Add_output_0
 49,            Conv, 3, 1, /backbone/net/p3/p3.1/res_m.0/Add_output_0, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/conv/Conv_output_0
 50,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
 51,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/relu/Mul_output_0
 52,            Conv, 3, 1, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/conv/Conv_output_0
 53,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
 54,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/relu/Mul_output_0
 55,             Add, 2, 1, /backbone/net/p3/p3.1/res_m.1/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.1/Add_output_0
 56,            Conv, 3, 1, /backbone/net/p3/p3.1/res_m.1/Add_output_0, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/conv/Conv_output_0
 57,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/relu/Sigmoid_output_0
 58,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/relu/Mul_output_0
 59,            Conv, 3, 1, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/conv/Conv_output_0
 60,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/relu/Sigmoid_output_0
 61,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/relu/Mul_output_0
 62,             Add, 2, 1, /backbone/net/p3/p3.1/res_m.2/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.2/Add_output_0
 63,            Conv, 3, 1, /backbone/net/p3/p3.1/res_m.2/Add_output_0, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/conv/Conv_output_0
 64,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/relu/Sigmoid_output_0
 65,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/relu/Mul_output_0
 66,            Conv, 3, 1, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/conv/Conv_output_0
 67,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/relu/Sigmoid_output_0
 68,             Mul, 2, 1, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/relu/Mul_output_0
 69,             Add, 2, 1, /backbone/net/p3/p3.1/res_m.3/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p3/p3.1/res_m.3/Add_output_0
 70,          Concat, 6, 1, /backbone/net/p3/p3.1/conv1/relu/Mul_output_0, /backbone/net/p3/p3.1/Concat_output_0
 71,            Conv, 3, 1, /backbone/net/p3/p3.1/Concat_output_0, /backbone/net/p3/p3.1/conv3/conv/Conv_output_0
 72,         Sigmoid, 1, 1, /backbone/net/p3/p3.1/conv3/conv/Conv_output_0, /backbone/net/p3/p3.1/conv3/relu/Sigmoid_output_0
 73,             Mul, 2, 1, /backbone/net/p3/p3.1/conv3/conv/Conv_output_0, /backbone/net/p3/p3.1/conv3/relu/Mul_output_0
 74,            Conv, 3, 1, /backbone/net/p3/p3.1/conv3/relu/Mul_output_0, /backbone/net/p4/p4.0/conv/Conv_output_0
 75,         Sigmoid, 1, 1, /backbone/net/p4/p4.0/conv/Conv_output_0, /backbone/net/p4/p4.0/relu/Sigmoid_output_0
 76,             Mul, 2, 1, /backbone/net/p4/p4.0/conv/Conv_output_0, /backbone/net/p4/p4.0/relu/Mul_output_0
 77,            Conv, 3, 1, /backbone/net/p4/p4.0/relu/Mul_output_0, /backbone/net/p4/p4.1/conv1/conv/Conv_output_0
 78,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/conv1/conv/Conv_output_0, /backbone/net/p4/p4.1/conv1/relu/Sigmoid_output_0
 79,             Mul, 2, 1, /backbone/net/p4/p4.1/conv1/conv/Conv_output_0, /backbone/net/p4/p4.1/conv1/relu/Mul_output_0
 80,            Conv, 3, 1, /backbone/net/p4/p4.0/relu/Mul_output_0, /backbone/net/p4/p4.1/conv2/conv/Conv_output_0
 81,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/conv2/conv/Conv_output_0, /backbone/net/p4/p4.1/conv2/relu/Sigmoid_output_0
 82,             Mul, 2, 1, /backbone/net/p4/p4.1/conv2/conv/Conv_output_0, /backbone/net/p4/p4.1/conv2/relu/Mul_output_0
 83,            Conv, 3, 1, /backbone/net/p4/p4.1/conv2/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/conv/Conv_output_0
 84,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
 85,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/relu/Mul_output_0
 86,            Conv, 3, 1, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/conv/Conv_output_0
 87,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
 88,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/relu/Mul_output_0
 89,             Add, 2, 1, /backbone/net/p4/p4.1/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.0/Add_output_0
 90,            Conv, 3, 1, /backbone/net/p4/p4.1/res_m.0/Add_output_0, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/conv/Conv_output_0
 91,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
 92,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/relu/Mul_output_0
 93,            Conv, 3, 1, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/conv/Conv_output_0
 94,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
 95,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/relu/Mul_output_0
 96,             Add, 2, 1, /backbone/net/p4/p4.1/res_m.1/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.1/Add_output_0
 97,            Conv, 3, 1, /backbone/net/p4/p4.1/res_m.1/Add_output_0, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/conv/Conv_output_0
 98,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/relu/Sigmoid_output_0
 99,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/relu/Mul_output_0
100,            Conv, 3, 1, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/conv/Conv_output_0
101,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/relu/Sigmoid_output_0
102,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/relu/Mul_output_0
103,             Add, 2, 1, /backbone/net/p4/p4.1/res_m.2/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.2/Add_output_0
104,            Conv, 3, 1, /backbone/net/p4/p4.1/res_m.2/Add_output_0, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/conv/Conv_output_0
105,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/relu/Sigmoid_output_0
106,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/relu/Mul_output_0
107,            Conv, 3, 1, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/conv/Conv_output_0
108,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/relu/Sigmoid_output_0
109,             Mul, 2, 1, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/relu/Mul_output_0
110,             Add, 2, 1, /backbone/net/p4/p4.1/res_m.3/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p4/p4.1/res_m.3/Add_output_0
111,          Concat, 6, 1, /backbone/net/p4/p4.1/conv1/relu/Mul_output_0, /backbone/net/p4/p4.1/Concat_output_0
112,            Conv, 3, 1, /backbone/net/p4/p4.1/Concat_output_0, /backbone/net/p4/p4.1/conv3/conv/Conv_output_0
113,         Sigmoid, 1, 1, /backbone/net/p4/p4.1/conv3/conv/Conv_output_0, /backbone/net/p4/p4.1/conv3/relu/Sigmoid_output_0
114,             Mul, 2, 1, /backbone/net/p4/p4.1/conv3/conv/Conv_output_0, /backbone/net/p4/p4.1/conv3/relu/Mul_output_0
115,            Conv, 3, 1, /backbone/net/p4/p4.1/conv3/relu/Mul_output_0, /backbone/net/p5/p5.0/conv/Conv_output_0
116,         Sigmoid, 1, 1, /backbone/net/p5/p5.0/conv/Conv_output_0, /backbone/net/p5/p5.0/relu/Sigmoid_output_0
117,             Mul, 2, 1, /backbone/net/p5/p5.0/conv/Conv_output_0, /backbone/net/p5/p5.0/relu/Mul_output_0
118,            Conv, 3, 1, /backbone/net/p5/p5.0/relu/Mul_output_0, /backbone/net/p5/p5.1/conv1/conv/Conv_output_0
119,         Sigmoid, 1, 1, /backbone/net/p5/p5.1/conv1/conv/Conv_output_0, /backbone/net/p5/p5.1/conv1/relu/Sigmoid_output_0
120,             Mul, 2, 1, /backbone/net/p5/p5.1/conv1/conv/Conv_output_0, /backbone/net/p5/p5.1/conv1/relu/Mul_output_0
121,            Conv, 3, 1, /backbone/net/p5/p5.0/relu/Mul_output_0, /backbone/net/p5/p5.1/conv2/conv/Conv_output_0
122,         Sigmoid, 1, 1, /backbone/net/p5/p5.1/conv2/conv/Conv_output_0, /backbone/net/p5/p5.1/conv2/relu/Sigmoid_output_0
123,             Mul, 2, 1, /backbone/net/p5/p5.1/conv2/conv/Conv_output_0, /backbone/net/p5/p5.1/conv2/relu/Mul_output_0
124,            Conv, 3, 1, /backbone/net/p5/p5.1/conv2/relu/Mul_output_0, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/conv/Conv_output_0
125,         Sigmoid, 1, 1, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
126,             Mul, 2, 1, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/relu/Mul_output_0
127,            Conv, 3, 1, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/conv/Conv_output_0
128,         Sigmoid, 1, 1, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
129,             Mul, 2, 1, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/relu/Mul_output_0
130,             Add, 2, 1, /backbone/net/p5/p5.1/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p5/p5.1/res_m.0/Add_output_0
131,            Conv, 3, 1, /backbone/net/p5/p5.1/res_m.0/Add_output_0, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/conv/Conv_output_0
132,         Sigmoid, 1, 1, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
133,             Mul, 2, 1, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/relu/Mul_output_0
134,            Conv, 3, 1, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/conv/Conv_output_0
135,         Sigmoid, 1, 1, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
136,             Mul, 2, 1, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/relu/Mul_output_0
137,             Add, 2, 1, /backbone/net/p5/p5.1/res_m.1/res_m/res_m.1/relu/Mul_output_0, /backbone/net/p5/p5.1/res_m.1/Add_output_0
138,          Concat, 4, 1, /backbone/net/p5/p5.1/conv1/relu/Mul_output_0, /backbone/net/p5/p5.1/Concat_output_0
139,            Conv, 3, 1, /backbone/net/p5/p5.1/Concat_output_0, /backbone/net/p5/p5.1/conv3/conv/Conv_output_0
140,         Sigmoid, 1, 1, /backbone/net/p5/p5.1/conv3/conv/Conv_output_0, /backbone/net/p5/p5.1/conv3/relu/Sigmoid_output_0
141,             Mul, 2, 1, /backbone/net/p5/p5.1/conv3/conv/Conv_output_0, /backbone/net/p5/p5.1/conv3/relu/Mul_output_0
142,            Conv, 3, 1, /backbone/net/p5/p5.1/conv3/relu/Mul_output_0, /backbone/net/p5/p5.2/conv1/conv/Conv_output_0
143,         Sigmoid, 1, 1, /backbone/net/p5/p5.2/conv1/conv/Conv_output_0, /backbone/net/p5/p5.2/conv1/relu/Sigmoid_output_0
144,             Mul, 2, 1, /backbone/net/p5/p5.2/conv1/conv/Conv_output_0, /backbone/net/p5/p5.2/conv1/relu/Mul_output_0
145,         MaxPool, 1, 1, /backbone/net/p5/p5.2/conv1/relu/Mul_output_0, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0/MaxPool_output_0
146,         MaxPool, 1, 1, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0/MaxPool_output_0, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1/MaxPool_output_0
147,         MaxPool, 1, 1, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1/MaxPool_output_0, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0_1/MaxPool_output_0
148,         MaxPool, 1, 1, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0_1/MaxPool_output_0, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1_1/MaxPool_output_0
149,         MaxPool, 1, 1, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1_1/MaxPool_output_0, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0_2/MaxPool_output_0
150,         MaxPool, 1, 1, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.0_2/MaxPool_output_0, /backbone/net/p5/p5.2/res_m_shared/res_m_shared.1_2/MaxPool_output_0
151,          Concat, 4, 1, /backbone/net/p5/p5.2/conv1/relu/Mul_output_0, /backbone/net/p5/p5.2/Concat_output_0
152,            Conv, 3, 1, /backbone/net/p5/p5.2/Concat_output_0, /backbone/net/p5/p5.2/conv2/conv/Conv_output_0
153,         Sigmoid, 1, 1, /backbone/net/p5/p5.2/conv2/conv/Conv_output_0, /backbone/net/p5/p5.2/conv2/relu/Sigmoid_output_0
154,             Mul, 2, 1, /backbone/net/p5/p5.2/conv2/conv/Conv_output_0, /backbone/net/p5/p5.2/conv2/relu/Mul_output_0
155,          Resize, 3, 1, /backbone/net/p5/p5.2/conv2/relu/Mul_output_0, /backbone/fpn/up/Resize_output_0
156,          Concat, 2, 1, /backbone/fpn/up/Resize_output_0, /backbone/fpn/Concat_output_0
157,            Conv, 3, 1, /backbone/fpn/Concat_output_0, /backbone/fpn/h1/conv1/conv/Conv_output_0
158,         Sigmoid, 1, 1, /backbone/fpn/h1/conv1/conv/Conv_output_0, /backbone/fpn/h1/conv1/relu/Sigmoid_output_0
159,             Mul, 2, 1, /backbone/fpn/h1/conv1/conv/Conv_output_0, /backbone/fpn/h1/conv1/relu/Mul_output_0
160,            Conv, 3, 1, /backbone/fpn/Concat_output_0, /backbone/fpn/h1/conv2/conv/Conv_output_0
161,         Sigmoid, 1, 1, /backbone/fpn/h1/conv2/conv/Conv_output_0, /backbone/fpn/h1/conv2/relu/Sigmoid_output_0
162,             Mul, 2, 1, /backbone/fpn/h1/conv2/conv/Conv_output_0, /backbone/fpn/h1/conv2/relu/Mul_output_0
163,            Conv, 3, 1, /backbone/fpn/h1/conv2/relu/Mul_output_0, /backbone/fpn/h1/res_m.0/res_m/res_m.0/conv/Conv_output_0
164,         Sigmoid, 1, 1, /backbone/fpn/h1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h1/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
165,             Mul, 2, 1, /backbone/fpn/h1/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h1/res_m.0/res_m/res_m.0/relu/Mul_output_0
166,            Conv, 3, 1, /backbone/fpn/h1/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h1/res_m.0/res_m/res_m.1/conv/Conv_output_0
167,         Sigmoid, 1, 1, /backbone/fpn/h1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h1/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
168,             Mul, 2, 1, /backbone/fpn/h1/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h1/res_m.0/res_m/res_m.1/relu/Mul_output_0
169,            Conv, 3, 1, /backbone/fpn/h1/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/fpn/h1/res_m.1/res_m/res_m.0/conv/Conv_output_0
170,         Sigmoid, 1, 1, /backbone/fpn/h1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h1/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
171,             Mul, 2, 1, /backbone/fpn/h1/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h1/res_m.1/res_m/res_m.0/relu/Mul_output_0
172,            Conv, 3, 1, /backbone/fpn/h1/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h1/res_m.1/res_m/res_m.1/conv/Conv_output_0
173,         Sigmoid, 1, 1, /backbone/fpn/h1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h1/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
174,             Mul, 2, 1, /backbone/fpn/h1/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h1/res_m.1/res_m/res_m.1/relu/Mul_output_0
175,          Concat, 4, 1, /backbone/fpn/h1/conv1/relu/Mul_output_0, /backbone/fpn/h1/Concat_output_0
176,            Conv, 3, 1, /backbone/fpn/h1/Concat_output_0, /backbone/fpn/h1/conv3/conv/Conv_output_0
177,         Sigmoid, 1, 1, /backbone/fpn/h1/conv3/conv/Conv_output_0, /backbone/fpn/h1/conv3/relu/Sigmoid_output_0
178,             Mul, 2, 1, /backbone/fpn/h1/conv3/conv/Conv_output_0, /backbone/fpn/h1/conv3/relu/Mul_output_0
179,          Resize, 3, 1, /backbone/fpn/h1/conv3/relu/Mul_output_0, /backbone/fpn/up_1/Resize_output_0
180,          Concat, 2, 1, /backbone/fpn/up_1/Resize_output_0, /backbone/fpn/Concat_1_output_0
181,            Conv, 3, 1, /backbone/fpn/Concat_1_output_0, /backbone/fpn/h2/conv1/conv/Conv_output_0
182,         Sigmoid, 1, 1, /backbone/fpn/h2/conv1/conv/Conv_output_0, /backbone/fpn/h2/conv1/relu/Sigmoid_output_0
183,             Mul, 2, 1, /backbone/fpn/h2/conv1/conv/Conv_output_0, /backbone/fpn/h2/conv1/relu/Mul_output_0
184,            Conv, 3, 1, /backbone/fpn/Concat_1_output_0, /backbone/fpn/h2/conv2/conv/Conv_output_0
185,         Sigmoid, 1, 1, /backbone/fpn/h2/conv2/conv/Conv_output_0, /backbone/fpn/h2/conv2/relu/Sigmoid_output_0
186,             Mul, 2, 1, /backbone/fpn/h2/conv2/conv/Conv_output_0, /backbone/fpn/h2/conv2/relu/Mul_output_0
187,            Conv, 3, 1, /backbone/fpn/h2/conv2/relu/Mul_output_0, /backbone/fpn/h2/res_m.0/res_m/res_m.0/conv/Conv_output_0
188,         Sigmoid, 1, 1, /backbone/fpn/h2/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h2/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
189,             Mul, 2, 1, /backbone/fpn/h2/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h2/res_m.0/res_m/res_m.0/relu/Mul_output_0
190,            Conv, 3, 1, /backbone/fpn/h2/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h2/res_m.0/res_m/res_m.1/conv/Conv_output_0
191,         Sigmoid, 1, 1, /backbone/fpn/h2/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h2/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
192,             Mul, 2, 1, /backbone/fpn/h2/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h2/res_m.0/res_m/res_m.1/relu/Mul_output_0
193,            Conv, 3, 1, /backbone/fpn/h2/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/fpn/h2/res_m.1/res_m/res_m.0/conv/Conv_output_0
194,         Sigmoid, 1, 1, /backbone/fpn/h2/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h2/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
195,             Mul, 2, 1, /backbone/fpn/h2/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h2/res_m.1/res_m/res_m.0/relu/Mul_output_0
196,            Conv, 3, 1, /backbone/fpn/h2/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h2/res_m.1/res_m/res_m.1/conv/Conv_output_0
197,         Sigmoid, 1, 1, /backbone/fpn/h2/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h2/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
198,             Mul, 2, 1, /backbone/fpn/h2/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h2/res_m.1/res_m/res_m.1/relu/Mul_output_0
199,          Concat, 4, 1, /backbone/fpn/h2/conv1/relu/Mul_output_0, /backbone/fpn/h2/Concat_output_0
200,            Conv, 3, 1, /backbone/fpn/h2/Concat_output_0, /backbone/fpn/h2/conv3/conv/Conv_output_0
201,         Sigmoid, 1, 1, /backbone/fpn/h2/conv3/conv/Conv_output_0, /backbone/fpn/h2/conv3/relu/Sigmoid_output_0
202,             Mul, 2, 1, /backbone/fpn/h2/conv3/conv/Conv_output_0, /backbone/fpn/h2/conv3/relu/Mul_output_0
203,            Conv, 3, 1, /backbone/fpn/h2/conv3/relu/Mul_output_0, /backbone/fpn/h3/conv/Conv_output_0
204,         Sigmoid, 1, 1, /backbone/fpn/h3/conv/Conv_output_0, /backbone/fpn/h3/relu/Sigmoid_output_0
205,             Mul, 2, 1, /backbone/fpn/h3/conv/Conv_output_0, /backbone/fpn/h3/relu/Mul_output_0
206,          Concat, 2, 1, /backbone/fpn/h3/relu/Mul_output_0, /backbone/fpn/Concat_2_output_0
207,            Conv, 3, 1, /backbone/fpn/Concat_2_output_0, /backbone/fpn/h4/conv1/conv/Conv_output_0
208,         Sigmoid, 1, 1, /backbone/fpn/h4/conv1/conv/Conv_output_0, /backbone/fpn/h4/conv1/relu/Sigmoid_output_0
209,             Mul, 2, 1, /backbone/fpn/h4/conv1/conv/Conv_output_0, /backbone/fpn/h4/conv1/relu/Mul_output_0
210,            Conv, 3, 1, /backbone/fpn/Concat_2_output_0, /backbone/fpn/h4/conv2/conv/Conv_output_0
211,         Sigmoid, 1, 1, /backbone/fpn/h4/conv2/conv/Conv_output_0, /backbone/fpn/h4/conv2/relu/Sigmoid_output_0
212,             Mul, 2, 1, /backbone/fpn/h4/conv2/conv/Conv_output_0, /backbone/fpn/h4/conv2/relu/Mul_output_0
213,            Conv, 3, 1, /backbone/fpn/h4/conv2/relu/Mul_output_0, /backbone/fpn/h4/res_m.0/res_m/res_m.0/conv/Conv_output_0
214,         Sigmoid, 1, 1, /backbone/fpn/h4/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h4/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
215,             Mul, 2, 1, /backbone/fpn/h4/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h4/res_m.0/res_m/res_m.0/relu/Mul_output_0
216,            Conv, 3, 1, /backbone/fpn/h4/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h4/res_m.0/res_m/res_m.1/conv/Conv_output_0
217,         Sigmoid, 1, 1, /backbone/fpn/h4/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h4/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
218,             Mul, 2, 1, /backbone/fpn/h4/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h4/res_m.0/res_m/res_m.1/relu/Mul_output_0
219,            Conv, 3, 1, /backbone/fpn/h4/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/fpn/h4/res_m.1/res_m/res_m.0/conv/Conv_output_0
220,         Sigmoid, 1, 1, /backbone/fpn/h4/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h4/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
221,             Mul, 2, 1, /backbone/fpn/h4/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h4/res_m.1/res_m/res_m.0/relu/Mul_output_0
222,            Conv, 3, 1, /backbone/fpn/h4/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h4/res_m.1/res_m/res_m.1/conv/Conv_output_0
223,         Sigmoid, 1, 1, /backbone/fpn/h4/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h4/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
224,             Mul, 2, 1, /backbone/fpn/h4/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h4/res_m.1/res_m/res_m.1/relu/Mul_output_0
225,          Concat, 4, 1, /backbone/fpn/h4/conv1/relu/Mul_output_0, /backbone/fpn/h4/Concat_output_0
226,            Conv, 3, 1, /backbone/fpn/h4/Concat_output_0, /backbone/fpn/h4/conv3/conv/Conv_output_0
227,         Sigmoid, 1, 1, /backbone/fpn/h4/conv3/conv/Conv_output_0, /backbone/fpn/h4/conv3/relu/Sigmoid_output_0
228,             Mul, 2, 1, /backbone/fpn/h4/conv3/conv/Conv_output_0, /backbone/fpn/h4/conv3/relu/Mul_output_0
229,            Conv, 3, 1, /backbone/fpn/h4/conv3/relu/Mul_output_0, /backbone/fpn/h5/conv/Conv_output_0
230,         Sigmoid, 1, 1, /backbone/fpn/h5/conv/Conv_output_0, /backbone/fpn/h5/relu/Sigmoid_output_0
231,             Mul, 2, 1, /backbone/fpn/h5/conv/Conv_output_0, /backbone/fpn/h5/relu/Mul_output_0
232,          Concat, 2, 1, /backbone/fpn/h5/relu/Mul_output_0, /backbone/fpn/Concat_3_output_0
233,            Conv, 3, 1, /backbone/fpn/Concat_3_output_0, /backbone/fpn/h6/conv1/conv/Conv_output_0
234,         Sigmoid, 1, 1, /backbone/fpn/h6/conv1/conv/Conv_output_0, /backbone/fpn/h6/conv1/relu/Sigmoid_output_0
235,             Mul, 2, 1, /backbone/fpn/h6/conv1/conv/Conv_output_0, /backbone/fpn/h6/conv1/relu/Mul_output_0
236,            Conv, 3, 1, /backbone/fpn/Concat_3_output_0, /backbone/fpn/h6/conv2/conv/Conv_output_0
237,         Sigmoid, 1, 1, /backbone/fpn/h6/conv2/conv/Conv_output_0, /backbone/fpn/h6/conv2/relu/Sigmoid_output_0
238,             Mul, 2, 1, /backbone/fpn/h6/conv2/conv/Conv_output_0, /backbone/fpn/h6/conv2/relu/Mul_output_0
239,            Conv, 3, 1, /backbone/fpn/h6/conv2/relu/Mul_output_0, /backbone/fpn/h6/res_m.0/res_m/res_m.0/conv/Conv_output_0
240,         Sigmoid, 1, 1, /backbone/fpn/h6/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h6/res_m.0/res_m/res_m.0/relu/Sigmoid_output_0
241,             Mul, 2, 1, /backbone/fpn/h6/res_m.0/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h6/res_m.0/res_m/res_m.0/relu/Mul_output_0
242,            Conv, 3, 1, /backbone/fpn/h6/res_m.0/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h6/res_m.0/res_m/res_m.1/conv/Conv_output_0
243,         Sigmoid, 1, 1, /backbone/fpn/h6/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h6/res_m.0/res_m/res_m.1/relu/Sigmoid_output_0
244,             Mul, 2, 1, /backbone/fpn/h6/res_m.0/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h6/res_m.0/res_m/res_m.1/relu/Mul_output_0
245,            Conv, 3, 1, /backbone/fpn/h6/res_m.0/res_m/res_m.1/relu/Mul_output_0, /backbone/fpn/h6/res_m.1/res_m/res_m.0/conv/Conv_output_0
246,         Sigmoid, 1, 1, /backbone/fpn/h6/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h6/res_m.1/res_m/res_m.0/relu/Sigmoid_output_0
247,             Mul, 2, 1, /backbone/fpn/h6/res_m.1/res_m/res_m.0/conv/Conv_output_0, /backbone/fpn/h6/res_m.1/res_m/res_m.0/relu/Mul_output_0
248,            Conv, 3, 1, /backbone/fpn/h6/res_m.1/res_m/res_m.0/relu/Mul_output_0, /backbone/fpn/h6/res_m.1/res_m/res_m.1/conv/Conv_output_0
249,         Sigmoid, 1, 1, /backbone/fpn/h6/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h6/res_m.1/res_m/res_m.1/relu/Sigmoid_output_0
250,             Mul, 2, 1, /backbone/fpn/h6/res_m.1/res_m/res_m.1/conv/Conv_output_0, /backbone/fpn/h6/res_m.1/res_m/res_m.1/relu/Mul_output_0
251,          Concat, 4, 1, /backbone/fpn/h6/conv1/relu/Mul_output_0, /backbone/fpn/h6/Concat_output_0
252,            Conv, 3, 1, /backbone/fpn/h6/Concat_output_0, /backbone/fpn/h6/conv3/conv/Conv_output_0
253,         Sigmoid, 1, 1, /backbone/fpn/h6/conv3/conv/Conv_output_0, /backbone/fpn/h6/conv3/relu/Sigmoid_output_0
254,             Mul, 2, 1, /backbone/fpn/h6/conv3/conv/Conv_output_0, /backbone/fpn/h6/conv3/relu/Mul_output_0
255,            Conv, 3, 1, /backbone/fpn/h6/conv3/relu/Mul_output_0, /decoder/conv/conv1/Conv_output_0
256,            Relu, 1, 1, /decoder/conv/conv1/Conv_output_0, /decoder/conv/conv_branch/conv_branch.0/Relu_output_0
257,            Conv, 3, 1, /decoder/conv/conv_branch/conv_branch.0/Relu_output_0, /decoder/conv/conv_branch/conv_branch.1/Conv_output_0
258,            Relu, 1, 1, /decoder/conv/conv_branch/conv_branch.1/Conv_output_0, /decoder/conv/conv_branch/conv_branch.3/Relu_output_0
259,            Conv, 3, 1, /decoder/conv/conv_branch/conv_branch.3/Relu_output_0, /decoder/conv/conv_branch/conv_branch.4/Conv_output_0
260,             Add, 2, 1, /decoder/conv/conv_branch/conv_branch.0/Relu_output_0, /decoder/conv/Add_output_0
261,            Relu, 1, 1, /decoder/conv/Add_output_0, /decoder/conv/relu/Relu_output_0
262,            Conv, 3, 1, /decoder/conv/relu/Relu_output_0, /decoder/conv1/Conv_output_0
263,          Resize, 3, 1, /decoder/conv1/Conv_output_0, /decoder/upsample/Resize_output_0
264,            Conv, 3, 1, /backbone/fpn/h4/conv3/relu/Mul_output_0, /decoder/ffm2/ftb1/conv1/Conv_output_0
265,            Relu, 1, 1, /decoder/ffm2/ftb1/conv1/Conv_output_0, /decoder/ffm2/ftb1/conv_branch/conv_branch.0/Relu_output_0
266,            Conv, 3, 1, /decoder/ffm2/ftb1/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm2/ftb1/conv_branch/conv_branch.1/Conv_output_0
267,            Relu, 1, 1, /decoder/ffm2/ftb1/conv_branch/conv_branch.1/Conv_output_0, /decoder/ffm2/ftb1/conv_branch/conv_branch.3/Relu_output_0
268,            Conv, 3, 1, /decoder/ffm2/ftb1/conv_branch/conv_branch.3/Relu_output_0, /decoder/ffm2/ftb1/conv_branch/conv_branch.4/Conv_output_0
269,             Add, 2, 1, /decoder/ffm2/ftb1/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm2/ftb1/Add_output_0
270,            Relu, 1, 1, /decoder/ffm2/ftb1/Add_output_0, /decoder/ffm2/ftb1/relu/Relu_output_0
271,             Add, 2, 1, /decoder/ffm2/ftb1/relu/Relu_output_0, /decoder/ffm2/Add_output_0
272,            Conv, 3, 1, /decoder/ffm2/Add_output_0, /decoder/ffm2/ftb2/conv1/Conv_output_0
273,            Relu, 1, 1, /decoder/ffm2/ftb2/conv1/Conv_output_0, /decoder/ffm2/ftb2/conv_branch/conv_branch.0/Relu_output_0
274,            Conv, 3, 1, /decoder/ffm2/ftb2/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm2/ftb2/conv_branch/conv_branch.1/Conv_output_0
275,            Relu, 1, 1, /decoder/ffm2/ftb2/conv_branch/conv_branch.1/Conv_output_0, /decoder/ffm2/ftb2/conv_branch/conv_branch.3/Relu_output_0
276,            Conv, 3, 1, /decoder/ffm2/ftb2/conv_branch/conv_branch.3/Relu_output_0, /decoder/ffm2/ftb2/conv_branch/conv_branch.4/Conv_output_0
277,             Add, 2, 1, /decoder/ffm2/ftb2/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm2/ftb2/Add_output_0
278,            Relu, 1, 1, /decoder/ffm2/ftb2/Add_output_0, /decoder/ffm2/ftb2/relu/Relu_output_0
279,          Resize, 3, 1, /decoder/ffm2/ftb2/relu/Relu_output_0, /decoder/ffm2/upsample/Resize_output_0
280,            Conv, 3, 1, /backbone/fpn/h2/conv3/relu/Mul_output_0, /decoder/ffm1/ftb1/conv1/Conv_output_0
281,            Relu, 1, 1, /decoder/ffm1/ftb1/conv1/Conv_output_0, /decoder/ffm1/ftb1/conv_branch/conv_branch.0/Relu_output_0
282,            Conv, 3, 1, /decoder/ffm1/ftb1/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm1/ftb1/conv_branch/conv_branch.1/Conv_output_0
283,            Relu, 1, 1, /decoder/ffm1/ftb1/conv_branch/conv_branch.1/Conv_output_0, /decoder/ffm1/ftb1/conv_branch/conv_branch.3/Relu_output_0
284,            Conv, 3, 1, /decoder/ffm1/ftb1/conv_branch/conv_branch.3/Relu_output_0, /decoder/ffm1/ftb1/conv_branch/conv_branch.4/Conv_output_0
285,             Add, 2, 1, /decoder/ffm1/ftb1/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm1/ftb1/Add_output_0
286,            Relu, 1, 1, /decoder/ffm1/ftb1/Add_output_0, /decoder/ffm1/ftb1/relu/Relu_output_0
287,             Add, 2, 1, /decoder/ffm1/ftb1/relu/Relu_output_0, /decoder/ffm1/Add_output_0
288,            Conv, 3, 1, /decoder/ffm1/Add_output_0, /decoder/ffm1/ftb2/conv1/Conv_output_0
289,            Relu, 1, 1, /decoder/ffm1/ftb2/conv1/Conv_output_0, /decoder/ffm1/ftb2/conv_branch/conv_branch.0/Relu_output_0
290,            Conv, 3, 1, /decoder/ffm1/ftb2/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm1/ftb2/conv_branch/conv_branch.1/Conv_output_0
291,            Relu, 1, 1, /decoder/ffm1/ftb2/conv_branch/conv_branch.1/Conv_output_0, /decoder/ffm1/ftb2/conv_branch/conv_branch.3/Relu_output_0
292,            Conv, 3, 1, /decoder/ffm1/ftb2/conv_branch/conv_branch.3/Relu_output_0, /decoder/ffm1/ftb2/conv_branch/conv_branch.4/Conv_output_0
293,             Add, 2, 1, /decoder/ffm1/ftb2/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm1/ftb2/Add_output_0
294,            Relu, 1, 1, /decoder/ffm1/ftb2/Add_output_0, /decoder/ffm1/ftb2/relu/Relu_output_0
295,          Resize, 3, 1, /decoder/ffm1/ftb2/relu/Relu_output_0, /decoder/ffm1/upsample/Resize_output_0
296,            Conv, 3, 1, /backbone/net/p2/p2.1/conv3/relu/Mul_output_0, /decoder/ffm0/ftb1/conv1/Conv_output_0
297,            Relu, 1, 1, /decoder/ffm0/ftb1/conv1/Conv_output_0, /decoder/ffm0/ftb1/conv_branch/conv_branch.0/Relu_output_0
298,            Conv, 3, 1, /decoder/ffm0/ftb1/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm0/ftb1/conv_branch/conv_branch.1/Conv_output_0
299,            Relu, 1, 1, /decoder/ffm0/ftb1/conv_branch/conv_branch.1/Conv_output_0, /decoder/ffm0/ftb1/conv_branch/conv_branch.3/Relu_output_0
300,            Conv, 3, 1, /decoder/ffm0/ftb1/conv_branch/conv_branch.3/Relu_output_0, /decoder/ffm0/ftb1/conv_branch/conv_branch.4/Conv_output_0
301,             Add, 2, 1, /decoder/ffm0/ftb1/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm0/ftb1/Add_output_0
302,            Relu, 1, 1, /decoder/ffm0/ftb1/Add_output_0, /decoder/ffm0/ftb1/relu/Relu_output_0
303,             Add, 2, 1, /decoder/ffm0/ftb1/relu/Relu_output_0, /decoder/ffm0/Add_output_0
304,            Conv, 3, 1, /decoder/ffm0/Add_output_0, /decoder/ffm0/ftb2/conv1/Conv_output_0
305,            Relu, 1, 1, /decoder/ffm0/ftb2/conv1/Conv_output_0, /decoder/ffm0/ftb2/conv_branch/conv_branch.0/Relu_output_0
306,            Conv, 3, 1, /decoder/ffm0/ftb2/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm0/ftb2/conv_branch/conv_branch.1/Conv_output_0
307,            Relu, 1, 1, /decoder/ffm0/ftb2/conv_branch/conv_branch.1/Conv_output_0, /decoder/ffm0/ftb2/conv_branch/conv_branch.3/Relu_output_0
308,            Conv, 3, 1, /decoder/ffm0/ftb2/conv_branch/conv_branch.3/Relu_output_0, /decoder/ffm0/ftb2/conv_branch/conv_branch.4/Conv_output_0
309,             Add, 2, 1, /decoder/ffm0/ftb2/conv_branch/conv_branch.0/Relu_output_0, /decoder/ffm0/ftb2/Add_output_0
310,            Relu, 1, 1, /decoder/ffm0/ftb2/Add_output_0, /decoder/ffm0/ftb2/relu/Relu_output_0
311,          Resize, 3, 1, /decoder/ffm0/ftb2/relu/Relu_output_0, /decoder/ffm0/upsample/Resize_output_0
312,            Conv, 3, 1, /decoder/ffm0/upsample/Resize_output_0, /decoder/outconv/conv/Conv_output_0
313,          Resize, 3, 1, /decoder/outconv/conv/Conv_output_0, output

Input tensor name -  inputNet_IN 
Output tensor name - output 
In TIDL_onnxRtImportInit subgraph_name=output
Layer 0, subgraph id output, name=output
Layer 1, subgraph id output, name=inputNet_IN
In TIDL_runtimesOptimizeNet: LayerIndex = 316, dataIndex = 315 

 ************** Frame index 1 : Running float import ************* 
In TIDL_runtimesPostProcessNet 
INFORMATION: [TIDL_ResizeLayer] /backbone/fpn/up/Resize 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] /backbone/fpn/up_1/Resize 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] /decoder/upsample/Resize 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] /decoder/ffm2/upsample/Resize 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] /decoder/ffm1/upsample/Resize 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] /decoder/ffm0/upsample/Resize 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] /decoder/outconv/upsample/Resize 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.
****************************************************
**          7 WARNINGS          0 ERRORS          **
****************************************************
************ in TIDL_subgraphRtCreate ************ 
 The soft limit is 2048
The hard limit is 2048
MEM: Init ... !!!
MEM: Init ... Done !!!
 0.0s:  VX_ZONE_INIT:Enabled
 0.3s:  VX_ZONE_ERROR:Enabled
 0.4s:  VX_ZONE_WARNING:Enabled
 0.990s:  VX_ZONE_INIT:[tivxInit:184] Initialization Done !!!
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Alg Alloc for Layer # -  142
Alg Alloc for Layer # -  143
Alg Alloc for Layer # -  144
Alg Alloc for Layer # -  145
Alg Alloc for Layer # -  146
Alg Alloc for Layer # -  147
Alg Alloc for Layer # -  148
Alg Alloc for Layer # -  149
Alg Alloc for Layer # -  150
Alg Alloc for Layer # -  151
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Alg Alloc for Layer # -  153
Alg Alloc for Layer # -  154
Alg Alloc for Layer # -  155
Alg Alloc for Layer # -  156
Alg Alloc for Layer # -  157
Alg Alloc for Layer # -  158
Alg Alloc for Layer # -  159
Alg Alloc for Layer # -  160
Alg Alloc for Layer # -  161
Alg Alloc for Layer # -  162
Alg Alloc for Layer # -  163
Alg Alloc for Layer # -  164
Alg Alloc for Layer # -  165
Alg Alloc for Layer # -  166
Alg Alloc for Layer # -  167
Alg Alloc for Layer # -  168
Alg Alloc for Layer # -  169
Alg Alloc for Layer # -  170
Alg Alloc for Layer # -  171
Alg Alloc for Layer # -  172
Alg Alloc for Layer # -  173
Alg Alloc for Layer # -  174
Alg Alloc for Layer # -  175
Alg Alloc for Layer # -  176
Alg Alloc for Layer # -  177
Alg Alloc for Layer # -  178
Alg Alloc for Layer # -  179
Alg Alloc for Layer # -  180
Alg Alloc for Layer # -  181
Alg Alloc for Layer # -  182
Alg Alloc for Layer # -  183
Alg Alloc for Layer # -  184
Alg Alloc for Layer # -  185
Alg Alloc for Layer # -  186
Alg Alloc for Layer # -  187
Alg Alloc for Layer # -  188
Alg Alloc for Layer # -  189
Alg Alloc for Layer # -  190
Alg Alloc for Layer # -  191
Alg Alloc for Layer # -  192
Alg Alloc for Layer # -  193
Alg Alloc for Layer # -  194
Alg Alloc for Layer # -  195
Alg Alloc for Layer # -  196
Alg Alloc for Layer # -  197
Alg Alloc for Layer # -  198
Alg Alloc for Layer # -  199
Alg Alloc for Layer # -  200
Alg Alloc for Layer # -  201
Alg Alloc for Layer # -  202
Alg Alloc for Layer # -  203
Alg Alloc for Layer # -  204
Alg Alloc for Layer # -  205
Alg Alloc for Layer # -  206
Alg Alloc for Layer # -  207
Alg Alloc for Layer # -  208
Alg Alloc for Layer # -  209
Alg Alloc for Layer # -  210
Alg Alloc for Layer # -  211
Alg Alloc for Layer # -  212
Alg Alloc for Layer # -  213
Alg Alloc for Layer # -  214
Alg Alloc for Layer # -  215
Alg Alloc for Layer # -  216
Alg Alloc for Layer # -  217
Alg Alloc for Layer # -  218
Alg Alloc for Layer # -  219
Alg Alloc for Layer # -  220
Alg Alloc for Layer # -  221
Alg Alloc for Layer # -  222
Alg Alloc for Layer # -  223
Alg Alloc for Layer # -  224
Alg Alloc for Layer # -  225
Alg Alloc for Layer # -  226
Alg Alloc for Layer # -  227
Alg Alloc for Layer # -  228
Alg Alloc for Layer # -  229
Alg Alloc for Layer # -  230
Alg Alloc for Layer # -  231
Alg Alloc for Layer # -  232
Alg Alloc for Layer # -  233
Alg Alloc for Layer # -  234
Alg Alloc for Layer # -  235
Alg Alloc for Layer # -  236
Alg Alloc for Layer # -  237
Alg Alloc for Layer # -  238
Alg Alloc for Layer # -  239
Alg Alloc for Layer # -  240
Alg Alloc for Layer # -  241
Alg Alloc for Layer # -  242
Alg Alloc for Layer # -  243
Alg Alloc for Layer # -  244
Alg Alloc for Layer # -  245
Alg Alloc for Layer # -  246
Alg Alloc for Layer # -  247
Alg Alloc for Layer # -  248
Alg Alloc for Layer # -  249
Alg Alloc for Layer # -  250
Alg Alloc for Layer # -  251
Alg Alloc for Layer # -  252
Alg Alloc for Layer # -  253
Alg Alloc for Layer # -  254
Alg Alloc for Layer # -  255
Alg Alloc for Layer # -  256
Alg Alloc for Layer # -  257
Alg Alloc for Layer # -  258
Alg Alloc for Layer # -  259
Alg Alloc for Layer # -  260
Alg Alloc for Layer # -  261
Alg Alloc for Layer # -  262
Alg Alloc for Layer # -  263
Alg Alloc for Layer # -  264
Alg Alloc for Layer # -  265
Alg Alloc for Layer # -  266
Alg Alloc for Layer # -  267
Alg Alloc for Layer # -  268
Alg Alloc for Layer # -  269
Alg Alloc for Layer # -  270
Alg Alloc for Layer # -  271
Alg Alloc for Layer # -  272
Alg Alloc for Layer # -  273
Alg Alloc for Layer # -  274
Alg Alloc for Layer # -  275
Alg Alloc for Layer # -  276
Alg Alloc for Layer # -  277
Alg Alloc for Layer # -  278
Alg Alloc for Layer # -  279
Alg Alloc for Layer # -  280
Alg Alloc for Layer # -  281
Alg Alloc for Layer # -  282
Alg Alloc for Layer # -  283
Alg Alloc for Layer # -  284
Alg Alloc for Layer # -  285
Alg Alloc for Layer # -  286
Alg Alloc for Layer # -  287
Alg Alloc for Layer # -  288
Alg Alloc for Layer # -  289
Alg Alloc for Layer # -  290
Alg Alloc for Layer # -  291
Alg Alloc for Layer # -  292
Alg Alloc for Layer # -  293

--------------------------------------------
TIDL Memory size requiement (record wise):
MemRecNum   , Space       , Attribute   , Size(KBytes) 
0           , DDR Cacheable, Persistent  , 14.84    
1           , DDR Cacheable, Persistent  , 0.14     
2           , DDR Cacheable, Scratch     , 16.00    
3           , DDR Cacheable, Scratch     , 4.00     
4           , DDR Cacheable, Scratch     , 56.00    
5           , DDR Cacheable, Persistent  , 624.29   
6           , DDR Cacheable, Scratch     , 258231.33 
7           , DDR Cacheable, Scratch     , 0.12     
8           , DDR Cacheable, Scratch     , 230400.12 
9           , DDR Cacheable, Scratch     , 230403.00 
10          , DDR Cacheable, Scratch     , 0.12     
11          , DDR Cacheable, Persistent  , 2865.12  
12          , DDR Cacheable, Scratch     , 512.25   
13          , DDR Cacheable, Persistent  , 0.12     
14          , DDR Cacheable, Persistent  , 102989.97 
--------------------------------------------
Total memory size requirement (space wise):
Mem Space , Size(KBytes)
DDR Cacheable, 826117.44
--------------------------------------------
NOTE: Memory requirement in host emulation can be different from the same on EVM
      To get the actual TIDL memory requirement make sure to run on EVM with 
      debugTraceLevel = 2

--------------------------------------------
Alg Init for Layer # -    0 out of  293
Alg Init for Layer # -    1 out of  293
Alg Init for Layer # -    2 out of  293
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Alg Init for Layer # -    4 out of  293
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Alg Init for Layer # -   30 out of  293
Alg Init for Layer # -   31 out of  293
Alg Init for Layer # -   32 out of  293
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Alg Init for Layer # -   44 out of  293
Alg Init for Layer # -   45 out of  293
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Alg Init for Layer # -   47 out of  293
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Alg Init for Layer # -   50 out of  293
Alg Init for Layer # -   51 out of  293
Alg Init for Layer # -   52 out of  293
Alg Init for Layer # -   53 out of  293
Alg Init for Layer # -   54 out of  293
Alg Init for Layer # -   55 out of  293
Alg Init for Layer # -   56 out of  293
Alg Init for Layer # -   57 out of  293
Alg Init for Layer # -   58 out of  293
Alg Init for Layer # -   59 out of  293
Alg Init for Layer # -   60 out of  293
Alg Init for Layer # -   61 out of  293
Alg Init for Layer # -   62 out of  293
Alg Init for Layer # -   63 out of  293
Alg Init for Layer # -   64 out of  293
Alg Init for Layer # -   65 out of  293
Alg Init for Layer # -   66 out of  293
Alg Init for Layer # -   67 out of  293
Alg Init for Layer # -   68 out of  293
Alg Init for Layer # -   69 out of  293
Alg Init for Layer # -   70 out of  293
Alg Init for Layer # -   71 out of  293
Alg Init for Layer # -   72 out of  293
Alg Init for Layer # -   73 out of  293
Alg Init for Layer # -   74 out of  293
Alg Init for Layer # -   75 out of  293
Alg Init for Layer # -   76 out of  293
Alg Init for Layer # -   77 out of  293
Alg Init for Layer # -   78 out of  293
Alg Init for Layer # -   79 out of  293
Alg Init for Layer # -   80 out of  293
Alg Init for Layer # -   81 out of  293
Alg Init for Layer # -   82 out of  293
Alg Init for Layer # -   83 out of  293
Alg Init for Layer # -   84 out of  293
Alg Init for Layer # -   85 out of  293
Alg Init for Layer # -   86 out of  293
Alg Init for Layer # -   87 out of  293
Alg Init for Layer # -   88 out of  293
Alg Init for Layer # -   89 out of  293
Alg Init for Layer # -   90 out of  293
Alg Init for Layer # -   91 out of  293
Alg Init for Layer # -   92 out of  293
Alg Init for Layer # -   93 out of  293
Alg Init for Layer # -   94 out of  293
Alg Init for Layer # -   95 out of  293
Alg Init for Layer # -   96 out of  293
Alg Init for Layer # -   97 out of  293
Alg Init for Layer # -   98 out of  293
Alg Init for Layer # -   99 out of  293
Alg Init for Layer # -  100 out of  293
Alg Init for Layer # -  101 out of  293
Alg Init for Layer # -  102 out of  293
Alg Init for Layer # -  103 out of  293
Alg Init for Layer # -  104 out of  293
Alg Init for Layer # -  105 out of  293
Alg Init for Layer # -  106 out of  293
Alg Init for Layer # -  107 out of  293
Alg Init for Layer # -  108 out of  293
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Alg Init for Layer # -  110 out of  293
Alg Init for Layer # -  111 out of  293
Alg Init for Layer # -  112 out of  293
Alg Init for Layer # -  113 out of  293
Alg Init for Layer # -  114 out of  293
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Alg Init for Layer # -  116 out of  293
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Alg Init for Layer # -  118 out of  293
Alg Init for Layer # -  119 out of  293
Alg Init for Layer # -  120 out of  293
Alg Init for Layer # -  121 out of  293
Alg Init for Layer # -  122 out of  293
Alg Init for Layer # -  123 out of  293
Alg Init for Layer # -  124 out of  293
Alg Init for Layer # -  125 out of  293
Alg Init for Layer # -  126 out of  293
Alg Init for Layer # -  127 out of  293
Alg Init for Layer # -  128 out of  293
Alg Init for Layer # -  129 out of  293
Alg Init for Layer # -  130 out of  293
Alg Init for Layer # -  131 out of  293
Alg Init for Layer # -  132 out of  293
Alg Init for Layer # -  133 out of  293
Alg Init for Layer # -  134 out of  293
Alg Init for Layer # -  135 out of  293
Alg Init for Layer # -  136 out of  293
Alg Init for Layer # -  137 out of  293
Alg Init for Layer # -  138 out of  293
Alg Init for Layer # -  139 out of  293
Alg Init for Layer # -  140 out of  293
Alg Init for Layer # -  141 out of  293
Alg Init for Layer # -  142 out of  293
Alg Init for Layer # -  143 out of  293
Alg Init for Layer # -  144 out of  293
Alg Init for Layer # -  145 out of  293
Alg Init for Layer # -  146 out of  293
Alg Init for Layer # -  147 out of  293
Alg Init for Layer # -  148 out of  293
Alg Init for Layer # -  149 out of  293
Alg Init for Layer # -  150 out of  293
Alg Init for Layer # -  151 out of  293
Alg Init for Layer # -  152 out of  293
Alg Init for Layer # -  153 out of  293
Alg Init for Layer # -  154 out of  293
Alg Init for Layer # -  155 out of  293
Alg Init for Layer # -  156 out of  293
Alg Init for Layer # -  157 out of  293
Alg Init for Layer # -  158 out of  293
Alg Init for Layer # -  159 out of  293
Alg Init for Layer # -  160 out of  293
Alg Init for Layer # -  161 out of  293
Alg Init for Layer # -  162 out of  293
Alg Init for Layer # -  163 out of  293
Alg Init for Layer # -  164 out of  293
Alg Init for Layer # -  165 out of  293
Alg Init for Layer # -  166 out of  293
Alg Init for Layer # -  167 out of  293
Alg Init for Layer # -  168 out of  293
Alg Init for Layer # -  169 out of  293
Alg Init for Layer # -  170 out of  293
Alg Init for Layer # -  171 out of  293
Alg Init for Layer # -  172 out of  293
Alg Init for Layer # -  173 out of  293
Alg Init for Layer # -  174 out of  293
Alg Init for Layer # -  175 out of  293
Alg Init for Layer # -  176 out of  293
Alg Init for Layer # -  177 out of  293
Alg Init for Layer # -  178 out of  293
Alg Init for Layer # -  179 out of  293
Alg Init for Layer # -  180 out of  293
Alg Init for Layer # -  181 out of  293
Alg Init for Layer # -  182 out of  293
Alg Init for Layer # -  183 out of  293
Alg Init for Layer # -  184 out of  293
Alg Init for Layer # -  185 out of  293
Alg Init for Layer # -  186 out of  293
Alg Init for Layer # -  187 out of  293
Alg Init for Layer # -  188 out of  293
Alg Init for Layer # -  189 out of  293
Alg Init for Layer # -  190 out of  293
Alg Init for Layer # -  191 out of  293
Alg Init for Layer # -  192 out of  293
Alg Init for Layer # -  193 out of  293
Alg Init for Layer # -  194 out of  293
Alg Init for Layer # -  195 out of  293
Alg Init for Layer # -  196 out of  293
Alg Init for Layer # -  197 out of  293
Alg Init for Layer # -  198 out of  293
Alg Init for Layer # -  199 out of  293
Alg Init for Layer # -  200 out of  293
Alg Init for Layer # -  201 out of  293
Alg Init for Layer # -  202 out of  293
Alg Init for Layer # -  203 out of  293
Alg Init for Layer # -  204 out of  293
Alg Init for Layer # -  205 out of  293
Alg Init for Layer # -  206 out of  293
Alg Init for Layer # -  207 out of  293
Alg Init for Layer # -  208 out of  293
Alg Init for Layer # -  209 out of  293
Alg Init for Layer # -  210 out of  293
Alg Init for Layer # -  211 out of  293
Alg Init for Layer # -  212 out of  293
Alg Init for Layer # -  213 out of  293
Alg Init for Layer # -  214 out of  293
Alg Init for Layer # -  215 out of  293
Alg Init for Layer # -  216 out of  293
Alg Init for Layer # -  217 out of  293
Alg Init for Layer # -  218 out of  293
Alg Init for Layer # -  219 out of  293
Alg Init for Layer # -  220 out of  293
Alg Init for Layer # -  221 out of  293
Alg Init for Layer # -  222 out of  293
Alg Init for Layer # -  223 out of  293
Alg Init for Layer # -  224 out of  293
Alg Init for Layer # -  225 out of  293
Alg Init for Layer # -  226 out of  293
Alg Init for Layer # -  227 out of  293
Alg Init for Layer # -  228 out of  293
Alg Init for Layer # -  229 out of  293
Alg Init for Layer # -  230 out of  293
Alg Init for Layer # -  231 out of  293
Alg Init for Layer # -  232 out of  293
Alg Init for Layer # -  233 out of  293
Alg Init for Layer # -  234 out of  293
Alg Init for Layer # -  235 out of  293
Alg Init for Layer # -  236 out of  293
Alg Init for Layer # -  237 out of  293
Alg Init for Layer # -  238 out of  293
Alg Init for Layer # -  239 out of  293
Alg Init for Layer # -  240 out of  293
Alg Init for Layer # -  241 out of  293
Alg Init for Layer # -  242 out of  293
Alg Init for Layer # -  243 out of  293
Alg Init for Layer # -  244 out of  293
Alg Init for Layer # -  245 out of  293
Alg Init for Layer # -  246 out of  293
Alg Init for Layer # -  247 out of  293
Alg Init for Layer # -  248 out of  293
Alg Init for Layer # -  249 out of  293
Alg Init for Layer # -  250 out of  293
Alg Init for Layer # -  251 out of  293
Alg Init for Layer # -  252 out of  293
Alg Init for Layer # -  253 out of  293
Alg Init for Layer # -  254 out of  293
Alg Init for Layer # -  255 out of  293
Alg Init for Layer # -  256 out of  293
Alg Init for Layer # -  257 out of  293
Alg Init for Layer # -  258 out of  293
Alg Init for Layer # -  259 out of  293
Alg Init for Layer # -  260 out of  293
Alg Init for Layer # -  261 out of  293
Alg Init for Layer # -  262 out of  293
Alg Init for Layer # -  263 out of  293
Alg Init for Layer # -  264 out of  293
Alg Init for Layer # -  265 out of  293
Alg Init for Layer # -  266 out of  293
Alg Init for Layer # -  267 out of  293
Alg Init for Layer # -  268 out of  293
Alg Init for Layer # -  269 out of  293
Alg Init for Layer # -  270 out of  293
Alg Init for Layer # -  271 out of  293
Alg Init for Layer # -  272 out of  293
Alg Init for Layer # -  273 out of  293
Alg Init for Layer # -  274 out of  293
Alg Init for Layer # -  275 out of  293
Alg Init for Layer # -  276 out of  293
Alg Init for Layer # -  277 out of  293
Alg Init for Layer # -  278 out of  293
Alg Init for Layer # -  279 out of  293
Alg Init for Layer # -  280 out of  293
Alg Init for Layer # -  281 out of  293
Alg Init for Layer # -  282 out of  293
Alg Init for Layer # -  283 out of  293
Alg Init for Layer # -  284 out of  293
Alg Init for Layer # -  285 out of  293
Alg Init for Layer # -  286 out of  293
Alg Init for Layer # -  287 out of  293
Alg Init for Layer # -  288 out of  293
Alg Init for Layer # -  289 out of  293
Alg Init for Layer # -  290 out of  293
Alg Init for Layer # -  291 out of  293
Alg Init for Layer # -  292 out of  293
Alg Init for Layer # -  293 out of  293
PREEMPTION: Adding a new priority object for targetPriority = 1, handle = 0x7f9767c72000
PREEMPTION: Now total number of priority objects = 1 at priorityId = 1,    with new memRec of base = 0x7f9754478000 and size = 128
PREEMPTION: Requesting context memory addr for handle 0x7f9767c72000, return Addr = 0x7f9754478000
************ TIDL_subgraphRtCreate done ************ 
 *******   In TIDL_subgraphRtInvoke  ******** 
TIDL_activate is called with handle : 67c72000 
Starting Layer # -    1
Processing Layer # -    1
End of Layer # -    1 with outPtrs[0] = 0x7f962df3e000
Starting Layer # -    2
Processing Layer # -    2
End of Layer # -    2 with outPtrs[0] = 0x7f962e2c9100
Starting Layer # -    3
Processing Layer # -    3
End of Layer # -    3 with outPtrs[0] = 0x7f962f0d9100
Starting Layer # -    4
Processing Layer # -    4
End of Layer # -    4 with outPtrs[0] = 0x7f962fee9100
Starting Layer # -    5
Processing Layer # -    5
End of Layer # -    5 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -    6
Processing Layer # -    6
End of Layer # -    6 with outPtrs[0] = 0x7f9631439780
Starting Layer # -    7
Processing Layer # -    7
End of Layer # -    7 with outPtrs[0] = 0x7f9631b41780
Starting Layer # -    8
Processing Layer # -    8
End of Layer # -    8 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -    9
Processing Layer # -    9
End of Layer # -    9 with outPtrs[0] = 0x7f9631439780
Starting Layer # -   10
Processing Layer # -   10
End of Layer # -   10 with outPtrs[0] = 0x7f9632249780
Starting Layer # -   11
Processing Layer # -   11
End of Layer # -   11 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -   12
Processing Layer # -   12
End of Layer # -   12 with outPtrs[0] = 0x7f9631439780
Starting Layer # -   13
Processing Layer # -   13
End of Layer # -   13 with outPtrs[0] = 0x7f96325cd780
Starting Layer # -   14
Processing Layer # -   14
End of Layer # -   14 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -   15
Processing Layer # -   15
End of Layer # -   15 with outPtrs[0] = 0x7f9631439780
Starting Layer # -   16
Processing Layer # -   16
End of Layer # -   16 with outPtrs[0] = 0x7f963296dc00
Starting Layer # -   17
Processing Layer # -   17
End of Layer # -   17 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -   18
Processing Layer # -   18
End of Layer # -   18 with outPtrs[0] = 0x7f9631439780
Starting Layer # -   19
Processing Layer # -   19
End of Layer # -   19 with outPtrs[0] = 0x7f9631b41780
Starting Layer # -   20
Processing Layer # -   20
End of Layer # -   20 with outPtrs[0] = 0x7f963296dc00
Starting Layer # -   21
Processing Layer # -   21
End of Layer # -   21 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -   22
Processing Layer # -   22
End of Layer # -   22 with outPtrs[0] = 0x7f9631439780
Starting Layer # -   23
Processing Layer # -   23
End of Layer # -   23 with outPtrs[0] = 0x7f9632d0e080
Starting Layer # -   24
Processing Layer # -   24
End of Layer # -   24 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -   25
Processing Layer # -   25
End of Layer # -   25 with outPtrs[0] = 0x7f9631439780
Starting Layer # -   26
Processing Layer # -   26
End of Layer # -   26 with outPtrs[0] = 0x7f9631b41780
Starting Layer # -   27
Processing Layer # -   27
End of Layer # -   27 with outPtrs[0] = 0x7f96330ae500
Starting Layer # -   28
Processing Layer # -   28
End of Layer # -   28 with outPtrs[0] = 0x7f9633432500
Starting Layer # -   29
Processing Layer # -   29
End of Layer # -   29 with outPtrs[0] = 0x7f9630d31780
Starting Layer # -   30
Processing Layer # -   30
End of Layer # -   30 with outPtrs[0] = 0x7f9631439780
Starting Layer # -   31
Processing Layer # -   31
End of Layer # -   31 with outPtrs[0] = 0x7f9634242500
Starting Layer # -   32
Processing Layer # -   32
End of Layer # -   32 with outPtrs[0] = 0x7f9634982d80
Starting Layer # -   33
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TIDL_process is completed with handle : 67c72000 
 Layer,   Layer Cycles,kernelOnlyCycles, coreLoopCycles,LayerSetupCycles,dmaPipeupCycles, dmaPipeDownCycles, PrefetchCycles,copyKerCoeffCycles,LayerDeinitCycles,LastBlockCycles, paddingTrigger,    paddingWait,LayerWithoutPad,LayerHandleCopy,   BackupCycles,  RestoreCycles,

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Processing config file #0 : /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts/tempDir/output_tidl_io_.qunat_stats_config.txt 
 Freeing memory for user provided Net
 ----------------------- TIDL Process with REF_ONLY FLOW ------------------------

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 Sum of Layer Cycles 0 
Sub Graph Stats 396.000000 85485456.000000 3045.000000 
*******  TIDL_subgraphRtInvoke done  ******** 

**********  Frame Index 1 : Running fixed point mode for calibration **********
In TIDL_runtimesPostProcessNet 

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

~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer
Processing config file #0 : /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts/tempDir/output_tidl_io_.qunat_stats_config.txt 
 Freeing memory for user provided Net
 ----------------------- TIDL Process with REF_ONLY FLOW ------------------------

#    0 . .. T   45265.13  .... ..... ... .... .....
------------------ Network Compiler Traces -----------------------------
NC running for device: 1
Running with OTF buffer optimizations
[34m
INFO:[33m20231129-015922: import completed  - [39msegmentation_dev_Unet_V1.1_onnx - 229 sec[34m
INFO:[33m20231129-015922: infer  - [39msegmentation_dev_Unet_V1.1_onnx - this may take some time...~~~~~

 
 
 *****************   Calibration iteration number 0 completed ************************ 
 
 
 
Could not open /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts/tempDir/output_tidl_net/perfSimInfo.bin
INFORMATION: [TIDL_ResizeLayer] /backbone/fpn/up/Resize 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] /backbone/fpn/up_1/Resize 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] /decoder/upsample/Resize 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] /decoder/ffm2/upsample/Resize 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] /decoder/ffm1/upsample/Resize 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] /decoder/ffm0/upsample/Resize 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] /decoder/outconv/upsample/Resize 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.
****************************************************
**          8 WARNINGS          0 ERRORS          **
****************************************************
libtidl_onnxrt_EP loaded 0x5638ca55bcd0 
artifacts_folder                                = /home/edgeai/code/edgeai-benchmark_v8.6_mod/edgeai-benchmark/work_dirs/modelartifacts/AM68A/8bits/segmentation_dev_Unet_V1.1_onnx/artifacts 
debug_level                                     = 2 
target_priority                                 = 0 
max_pre_empt_delay                              = 340282346638528859811704183484516925440.000000 
Final number of subgraphs created are : 1, - Offloaded Nodes - 314, Total Nodes - 314 
In TIDL_createStateInfer 
Compute on node : TIDLExecutionProvider_TIDL_0_0
************ in TIDL_subgraphRtCreate ************ 
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--------------------------------------------
TIDL Memory size requiement (record wise):
MemRecNum   , Space       , Attribute   , Size(KBytes) 
0           , DDR Cacheable, Persistent  , 14.84    
1           , DDR Cacheable, Persistent  , 0.14     
2           , DDR Cacheable, Scratch     , 16.00    
3           , DDR Cacheable, Scratch     , 4.00     
4           , DDR Cacheable, Scratch     , 56.00    
5           , DDR Cacheable, Persistent  , 580.27   
6           , DDR Cacheable, Scratch     , 67273.30 
7           , DDR Cacheable, Scratch     , 0.12     
8           , DDR Cacheable, Scratch     , 28800.12 
9           , DDR Cacheable, Scratch     , 86403.00 
10          , DDR Cacheable, Scratch     , 0.12     
11          , DDR Cacheable, Persistent  , 2865.12  
12          , DDR Cacheable, Scratch     , 512.25   
13          , DDR Cacheable, Persistent  , 0.12     
14          , DDR Cacheable, Persistent  , 27588.33 
--------------------------------------------
Total memory size requirement (space wise):
Mem Space , Size(KBytes)
DDR Cacheable, 214113.75
--------------------------------------------
NOTE: Memory requirement in host emulation can be different from the same on EVM
      To get the actual TIDL memory requirement make sure to run on EVM with 
      debugTraceLevel = 2

--------------------------------------------
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Alg Init for Layer # -   37 out of  293
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Alg Init for Layer # -   50 out of  293
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Alg Init for Layer # -   62 out of  293
Alg Init for Layer # -   63 out of  293
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Alg Init for Layer # -   71 out of  293
Alg Init for Layer # -   72 out of  293
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Alg Init for Layer # -   75 out of  293
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Alg Init for Layer # -   79 out of  293
Alg Init for Layer # -   80 out of  293
Alg Init for Layer # -   81 out of  293
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Alg Init for Layer # -   83 out of  293
Alg Init for Layer # -   84 out of  293
Alg Init for Layer # -   85 out of  293
Alg Init for Layer # -   86 out of  293
Alg Init for Layer # -   87 out of  293
Alg Init for Layer # -   88 out of  293
Alg Init for Layer # -   89 out of  293
Alg Init for Layer # -   90 out of  293
Alg Init for Layer # -   91 out of  293
Alg Init for Layer # -   92 out of  293
Alg Init for Layer # -   93 out of  293
Alg Init for Layer # -   94 out of  293
Alg Init for Layer # -   95 out of  293
Alg Init for Layer # -   96 out of  293
Alg Init for Layer # -   97 out of  293
Alg Init for Layer # -   98 out of  293
Alg Init for Layer # -   99 out of  293
Alg Init for Layer # -  100 out of  293
Alg Init for Layer # -  101 out of  293
Alg Init for Layer # -  102 out of  293
Alg Init for Layer # -  103 out of  293
Alg Init for Layer # -  104 out of  293
Alg Init for Layer # -  105 out of  293
Alg Init for Layer # -  106 out of  293
Alg Init for Layer # -  107 out of  293
Alg Init for Layer # -  108 out of  293
Alg Init for Layer # -  109 out of  293
Alg Init for Layer # -  110 out of  293
Alg Init for Layer # -  111 out of  293
Alg Init for Layer # -  112 out of  293
Alg Init for Layer # -  113 out of  293
Alg Init for Layer # -  114 out of  293
Alg Init for Layer # -  115 out of  293
Alg Init for Layer # -  116 out of  293
Alg Init for Layer # -  117 out of  293
Alg Init for Layer # -  118 out of  293
Alg Init for Layer # -  119 out of  293
Alg Init for Layer # -  120 out of  293
Alg Init for Layer # -  121 out of  293
Alg Init for Layer # -  122 out of  293
Alg Init for Layer # -  123 out of  293
Alg Init for Layer # -  124 out of  293
Alg Init for Layer # -  125 out of  293
Alg Init for Layer # -  126 out of  293
Alg Init for Layer # -  127 out of  293
Alg Init for Layer # -  128 out of  293
Alg Init for Layer # -  129 out of  293
Alg Init for Layer # -  130 out of  293
Alg Init for Layer # -  131 out of  293
Alg Init for Layer # -  132 out of  293
Alg Init for Layer # -  133 out of  293
Alg Init for Layer # -  134 out of  293
Alg Init for Layer # -  135 out of  293
Alg Init for Layer # -  136 out of  293
Alg Init for Layer # -  137 out of  293
Alg Init for Layer # -  138 out of  293
Alg Init for Layer # -  139 out of  293
Alg Init for Layer # -  140 out of  293
Alg Init for Layer # -  141 out of  293
Alg Init for Layer # -  142 out of  293
Alg Init for Layer # -  143 out of  293
Alg Init for Layer # -  144 out of  293
Alg Init for Layer # -  145 out of  293
Alg Init for Layer # -  146 out of  293
Alg Init for Layer # -  147 out of  293
Alg Init for Layer # -  148 out of  293
Alg Init for Layer # -  149 out of  293
Alg Init for Layer # -  150 out of  293
Alg Init for Layer # -  151 out of  293
Alg Init for Layer # -  152 out of  293
Alg Init for Layer # -  153 out of  293
Alg Init for Layer # -  154 out of  293
Alg Init for Layer # -  155 out of  293
Alg Init for Layer # -  156 out of  293
Alg Init for Layer # -  157 out of  293
Alg Init for Layer # -  158 out of  293
Alg Init for Layer # -  159 out of  293
Alg Init for Layer # -  160 out of  293
Alg Init for Layer # -  161 out of  293
Alg Init for Layer # -  162 out of  293
Alg Init for Layer # -  163 out of  293
Alg Init for Layer # -  164 out of  293
Alg Init for Layer # -  165 out of  293
Alg Init for Layer # -  166 out of  293
Alg Init for Layer # -  167 out of  293
Alg Init for Layer # -  168 out of  293
Alg Init for Layer # -  169 out of  293
Alg Init for Layer # -  170 out of  293
Alg Init for Layer # -  171 out of  293
Alg Init for Layer # -  172 out of  293
Alg Init for Layer # -  173 out of  293
Alg Init for Layer # -  174 out of  293
Alg Init for Layer # -  175 out of  293
Alg Init for Layer # -  176 out of  293
Alg Init for Layer # -  177 out of  293
Alg Init for Layer # -  178 out of  293
Alg Init for Layer # -  179 out of  293
Alg Init for Layer # -  180 out of  293
Alg Init for Layer # -  181 out of  293
Alg Init for Layer # -  182 out of  293
Alg Init for Layer # -  183 out of  293
Alg Init for Layer # -  184 out of  293
Alg Init for Layer # -  185 out of  293
Alg Init for Layer # -  186 out of  293
Alg Init for Layer # -  187 out of  293
Alg Init for Layer # -  188 out of  293
Alg Init for Layer # -  189 out of  293
Alg Init for Layer # -  190 out of  293
Alg Init for Layer # -  191 out of  293
Alg Init for Layer # -  192 out of  293
Alg Init for Layer # -  193 out of  293
Alg Init for Layer # -  194 out of  293
Alg Init for Layer # -  195 out of  293
Alg Init for Layer # -  196 out of  293
Alg Init for Layer # -  197 out of  293
Alg Init for Layer # -  198 out of  293
Alg Init for Layer # -  199 out of  293
Alg Init for Layer # -  200 out of  293
Alg Init for Layer # -  201 out of  293
Alg Init for Layer # -  202 out of  293
Alg Init for Layer # -  203 out of  293
Alg Init for Layer # -  204 out of  293
Alg Init for Layer # -  205 out of  293
Alg Init for Layer # -  206 out of  293
Alg Init for Layer # -  207 out of  293
Alg Init for Layer # -  208 out of  293
Alg Init for Layer # -  209 out of  293
Alg Init for Layer # -  210 out of  293
Alg Init for Layer # -  211 out of  293
Alg Init for Layer # -  212 out of  293
Alg Init for Layer # -  213 out of  293
Alg Init for Layer # -  214 out of  293
Alg Init for Layer # -  215 out of  293
Alg Init for Layer # -  216 out of  293
Alg Init for Layer # -  217 out of  293
Alg Init for Layer # -  218 out of  293
Alg Init for Layer # -  219 out of  293
Alg Init for Layer # -  220 out of  293
Alg Init for Layer # -  221 out of  293
Alg Init for Layer # -  222 out of  293
Alg Init for Layer # -  223 out of  293
Alg Init for Layer # -  224 out of  293
Alg Init for Layer # -  225 out of  293
Alg Init for Layer # -  226 out of  293
Alg Init for Layer # -  227 out of  293
Alg Init for Layer # -  228 out of  293
Alg Init for Layer # -  229 out of  293
Alg Init for Layer # -  230 out of  293
Alg Init for Layer # -  231 out of  293
Alg Init for Layer # -  232 out of  293
Alg Init for Layer # -  233 out of  293
Alg Init for Layer # -  234 out of  293
Alg Init for Layer # -  235 out of  293
Alg Init for Layer # -  236 out of  293
Alg Init for Layer # -  237 out of  293
Alg Init for Layer # -  238 out of  293
Alg Init for Layer # -  239 out of  293
Alg Init for Layer # -  240 out of  293
Alg Init for Layer # -  241 out of  293
Alg Init for Layer # -  242 out of  293
Alg Init for Layer # -  243 out of  293
Alg Init for Layer # -  244 out of  293
Alg Init for Layer # -  245 out of  293
Alg Init for Layer # -  246 out of  293
Alg Init for Layer # -  247 out of  293
Alg Init for Layer # -  248 out of  293
Alg Init for Layer # -  249 out of  293
Alg Init for Layer # -  250 out of  293
Alg Init for Layer # -  251 out of  293
Alg Init for Layer # -  252 out of  293
Alg Init for Layer # -  253 out of  293
Alg Init for Layer # -  254 out of  293
Alg Init for Layer # -  255 out of  293
Alg Init for Layer # -  256 out of  293
Alg Init for Layer # -  257 out of  293
Alg Init for Layer # -  258 out of  293
Alg Init for Layer # -  259 out of  293
Alg Init for Layer # -  260 out of  293
Alg Init for Layer # -  261 out of  293
Alg Init for Layer # -  262 out of  293
Alg Init for Layer # -  263 out of  293
Alg Init for Layer # -  264 out of  293
Alg Init for Layer # -  265 out of  293
Alg Init for Layer # -  266 out of  293
Alg Init for Layer # -  267 out of  293
Alg Init for Layer # -  268 out of  293
Alg Init for Layer # -  269 out of  293
Alg Init for Layer # -  270 out of  293
Alg Init for Layer # -  271 out of  293
Alg Init for Layer # -  272 out of  293
Alg Init for Layer # -  273 out of  293
Alg Init for Layer # -  274 out of  293
Alg Init for Layer # -  275 out of  293
Alg Init for Layer # -  276 out of  293
Alg Init for Layer # -  277 out of  293
Alg Init for Layer # -  278 out of  293
Alg Init for Layer # -  279 out of  293
Alg Init for Layer # -  280 out of  293
Alg Init for Layer # -  281 out of  293
Alg Init for Layer # -  282 out of  293
Alg Init for Layer # -  283 out of  293
Alg Init for Layer # -  284 out of  293
Alg Init for Layer # -  
infer : segmentation|   0%|          || 0/1 [00:00<?, ?it/s]
infer : segmentation|          |     0% 0/1| [< ]285 out of  293
Alg Init for Layer # -  286 out of  293
Alg Init for Layer # -  287 out of  293
Alg Init for Layer # -  288 out of  293
Alg Init for Layer # -  289 out of  293
Alg Init for Layer # -  290 out of  293
Alg Init for Layer # -  291 out of  293
Alg Init for Layer # -  292 out of  293
Alg Init for Layer # -  293 out of  293
PREEMPTION: Adding a new priority object for targetPriority = 1, handle = 0x7f972b476000
PREEMPTION: Now total number of priority objects = 2 at priorityId = 1,    with new memRec of base = 0x7f9743c74000 and size = 128
PREEMPTION: Requesting context memory addr for handle 0x7f972b476000, return Addr = 0x7f9754478000
************ TIDL_subgraphRtCreate done ************ 
 ************ in TIDL_subgraphRtDelete ************ 
 TIDL_deactivate is called with handle : 67c72000 
PREEMPTION: Removing priroty object with handle = 0x7f9767c72000 and targetPriority = 1,      Number of obejcts left are = 1, removed object with base  = 0x7f9743c74000 and size =128
*******   In TIDL_subgraphRtInvoke  ******** 
TIDL_activate is called with handle : 2b476000 
Starting Layer # -    1
Processing Layer # -    1
End of Layer # -    1 with outPtrs[0] = 0x7f95e1c2f000
Starting Layer # -    2
Processing Layer # -    2
End of Layer # -    2 with outPtrs[0] = 0x7f95e1d11c80
Starting Layer # -    3
Processing Layer # -    3
End of Layer # -    3 with outPtrs[0] = 0x7f95e2095c80
Starting Layer # -    4
Processing Layer # -    4
End of Layer # -    4 with outPtrs[0] = 0x7f95e2419c80
Starting Layer # -    5
Processing Layer # -    5
End of Layer # -    5 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -    6
Processing Layer # -    6
End of Layer # -    6 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -    7
Processing Layer # -    7
End of Layer # -    7 with outPtrs[0] = 0x7f95e2b2fe80
Starting Layer # -    8
Processing Layer # -    8
End of Layer # -    8 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -    9
Processing Layer # -    9
End of Layer # -    9 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -   10
Processing Layer # -   10
End of Layer # -   10 with outPtrs[0] = 0x7f95e2cf1e80
Starting Layer # -   11
Processing Layer # -   11
End of Layer # -   11 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -   12
Processing Layer # -   12
End of Layer # -   12 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -   13
Processing Layer # -   13
End of Layer # -   13 with outPtrs[0] = 0x7f95e2dd2e80
Starting Layer # -   14
Processing Layer # -   14
End of Layer # -   14 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -   15
Processing Layer # -   15
End of Layer # -   15 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -   16
Processing Layer # -   16
End of Layer # -   16 with outPtrs[0] = 0x7f95e2ebb000
Starting Layer # -   17
Processing Layer # -   17
End of Layer # -   17 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -   18
Processing Layer # -   18
End of Layer # -   18 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -   19
Processing Layer # -   19
End of Layer # -   19 with outPtrs[0] = 0x7f95e2b2fe80
Starting Layer # -   20
Processing Layer # -   20
End of Layer # -   20 with outPtrs[0] = 0x7f95e2ebb000
Starting Layer # -   21
Processing Layer # -   21
End of Layer # -   21 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -   22
Processing Layer # -   22
End of Layer # -   22 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -   23
Processing Layer # -   23
End of Layer # -   23 with outPtrs[0] = 0x7f95e2fa3180
Starting Layer # -   24
Processing Layer # -   24
End of Layer # -   24 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -   25
Processing Layer # -   25
End of Layer # -   25 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -   26
Processing Layer # -   26
End of Layer # -   26 with outPtrs[0] = 0x7f95e2b2fe80
Starting Layer # -   27
Processing Layer # -   27
End of Layer # -   27 with outPtrs[0] = 0x7f95e308b300
Starting Layer # -   28
Processing Layer # -   28
End of Layer # -   28 with outPtrs[0] = 0x7f95e316c300
Starting Layer # -   29
Processing Layer # -   29
End of Layer # -   29 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -   30
Processing Layer # -   30
End of Layer # -   30 with outPtrs[0] = 0x7f95e296de80
Starting Layer # -   31
Processing Layer # -   31
End of Layer # -   31 with outPtrs[0] = 0x7f95e34f0300
Starting Layer # -   32
Processing Layer # -   32
End of Layer # -   32 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   33
Processing Layer # -   33
End of Layer # -   33 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   34
Processing Layer # -   34
End of Layer # -   34 with outPtrs[0] = 0x7f95e3882580
Starting Layer # -   35
Processing Layer # -   35
End of Layer # -   35 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   36
Processing Layer # -   36
End of Layer # -   36 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   37
Processing Layer # -   37
End of Layer # -   37 with outPtrs[0] = 0x7f95e3963580
Starting Layer # -   38
Processing Layer # -   38
End of Layer # -   38 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   39
Processing Layer # -   39
End of Layer # -   39 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   40
Processing Layer # -   40
End of Layer # -   40 with outPtrs[0] = 0x7f95e39d3d80
Starting Layer # -   41
Processing Layer # -   41
End of Layer # -   41 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   42
Processing Layer # -   42
End of Layer # -   42 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   43
Processing Layer # -   43
End of Layer # -   43 with outPtrs[0] = 0x7f95e3a4b780
Starting Layer # -   44
Processing Layer # -   44
End of Layer # -   44 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   45
Processing Layer # -   45
End of Layer # -   45 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   46
Processing Layer # -   46
End of Layer # -   46 with outPtrs[0] = 0x7f95e3882580
Starting Layer # -   47
Processing Layer # -   47
End of Layer # -   47 with outPtrs[0] = 0x7f95e3a4b780
Starting Layer # -   48
Processing Layer # -   48
End of Layer # -   48 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   49
Processing Layer # -   49
End of Layer # -   49 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   50
Processing Layer # -   50
End of Layer # -   50 with outPtrs[0] = 0x7f95e3ac3180
Starting Layer # -   51
Processing Layer # -   51
End of Layer # -   51 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   52
Processing Layer # -   52
End of Layer # -   52 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   53
Processing Layer # -   53
End of Layer # -   53 with outPtrs[0] = 0x7f95e3882580
Starting Layer # -   54
Processing Layer # -   54
End of Layer # -   54 with outPtrs[0] = 0x7f95e3ac3180
Starting Layer # -   55
Processing Layer # -   55
End of Layer # -   55 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   56
Processing Layer # -   56
End of Layer # -   56 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   57
Processing Layer # -   57
End of Layer # -   57 with outPtrs[0] = 0x7f95e3b3ab80
Starting Layer # -   58
Processing Layer # -   58
End of Layer # -   58 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   59
Processing Layer # -   59
End of Layer # -   59 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   60
Processing Layer # -   60
End of Layer # -   60 with outPtrs[0] = 0x7f95e3882580
Starting Layer # -   61
Processing Layer # -   61
End of Layer # -   61 with outPtrs[0] = 0x7f95e3b3ab80
Starting Layer # -   62
Processing Layer # -   62
End of Layer # -   62 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   63
Processing Layer # -   63
End of Layer # -   63 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   64
Processing Layer # -   64
End of Layer # -   64 with outPtrs[0] = 0x7f95e3bb2580
Starting Layer # -   65
Processing Layer # -   65
End of Layer # -   65 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   66
Processing Layer # -   66
End of Layer # -   66 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   67
Processing Layer # -   67
End of Layer # -   67 with outPtrs[0] = 0x7f95e3882580
Starting Layer # -   68
Processing Layer # -   68
End of Layer # -   68 with outPtrs[0] = 0x7f95e3c29f80
Starting Layer # -   69
Processing Layer # -   69
End of Layer # -   69 with outPtrs[0] = 0x7f95e3c9a780
Starting Layer # -   70
Processing Layer # -   70
End of Layer # -   70 with outPtrs[0] = 0x7f95e36c0580
Starting Layer # -   71
Processing Layer # -   71
End of Layer # -   71 with outPtrs[0] = 0x7f95e37a1580
Starting Layer # -   72
Processing Layer # -   72
End of Layer # -   72 with outPtrs[0] = 0x7f95e3f3d780
Starting Layer # -   73
Processing Layer # -   73
End of Layer # -   73 with outPtrs[0] = 0x7f95e402cb00
Starting Layer # -   74
Processing Layer # -   74
End of Layer # -   74 with outPtrs[0] = 0x7f95e409d300
Starting Layer # -   75
Processing Layer # -   75
End of Layer # -   75 with outPtrs[0] = 0x7f95e410db00
Starting Layer # -   76
Processing Layer # -   76
End of Layer # -   76 with outPtrs[0] = 0x7f95e402cb00
Starting Layer # -   77
Processing Layer # -   77
End of Layer # -   77 with outPtrs[0] = 0x7f95e409d300
Starting Layer # -   78
Processing Layer # -   78
End of Layer # -   78 with outPtrs[0] = 0x7f95e417e300
Starting Layer # -   79
Processing Layer # -   79
End of Layer # -   79 with outPtrs[0] = 0x7f95e402cb00
Starting Layer # -   80
Processing Layer # -   80
End of Layer # -   80 with outPtrs[0] = 0x7f95e409d300
Starting Layer # -   81
Processing Layer # -   81
End of Layer # -   81 with outPtrs[0] = 0x7f95e41b6700
Starting Layer # -   82
Processing Layer # -   82
End of Layer # -   82 with outPtrs[0] = 0x7f95e402cb00
Starting Layer # -   83
Processing Layer # -   83
End of Layer # -   83 with outPtrs[0] = 0x7f95e409d300
Starting Layer # -   84
Processing Layer # -   84
End of Layer # -   84 with outPtrs[0] = 0x7f95e41f5e00
Starting Layer # -   85
Processing Layer # -   85
End of Layer # -   85 with outPtrs[0] = 0x7f95e402cb00
Starting Layer # -   86
Processing Layer # -   86
End of Layer # -   86 with outPtrs[0] = 0x7f95e409d300
Starting Layer # -   87
Processing Layer # -   87
End of Layer # -   87 with outPtrs[0] = 0x7f95e410db00
Starting Layer # -   88
Processing Layer # -   88
End of Layer # -   88 with outPtrs[0] = 0x7f95e41f5e00
Starting Layer # -   89
Processing Layer # -   89
End of Layer # -   89 with outPtrs[0] = 0x7f95e402cb00
Starting Layer # -   90
Processing Layer # -   90
End of Layer # -   90 with outPtrs[0] = 0x7f95e409d300
Starting Layer # -   91
Processing Layer # -   91
End of Layer # -   91 with outPtrs[0] = 0x7f95e4235500
Starting Layer # -   92
Processing Layer # -   92
End of Layer # -   92 with outPtrs[0] = 0x7f95e402cb00
Starting Layer # -   93
Processing Layer # -   93
End of Layer # -   93 with outPtrs[0] = 0x7f95e409d300
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Starting Layer # -  287
Processing Layer # -  287
End of Layer # -  287 with outPtrs[0] = 0x7f95e27abe80
Starting Layer # -  288
Processing Layer # -  288
End of Layer # -  288 with outPtrs[0] = 0x7f95e34f0300
Starting Layer # -  289
Processing Layer # -  289
End of Layer # -  289 with outPtrs[0] = 0x7f95e5002580
Starting Layer # -  290
Processing Layer # -  290
End of Layer # -  290 with outPtrs[0] = 0x7f95e570a580
Starting Layer # -  291
Processing Layer # -  291
End of Layer # -  291 with outPtrs[0] = 0x7f95e57b5c00
Starting Layer # -  292
Processing Layer # -  292
End of Layer # -  292 with outPtrs[0] = 0x7f966241f000
TIDL_process is completed with handle : 2b476000 
 Layer,   Layer Cycles,kernelOnlyCycles, coreLoopCycles,LayerSetupCycles,dmaPipeupCycles, dmaPipeDownCycles, PrefetchCycles,copyKerCoeffCycles,LayerDeinitCycles,LastBlockCycles, paddingTrigger,    paddingWait,LayerWithoutPad,LayerHandleCopy,   BackupCycles,  RestoreCycles,

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infer : segmentation| 100%|##########|| 1/1 [00:54<00:00, 54.00s/it]
infer : segmentation| 100%|##########|| 1/1 [00:54<00:00, 54.00s/it]
[34m
INFO:[33m20231129-020016: infer completed  - [39msegmentation_dev_Unet_V1.1_onnx - 54 sec[32m

SUCCESS:[33m20231129-020016: benchmark results - [39m{'infer_path': 'segmentation_dev_Unet_V1.1_onnx', 'accuracy_mean_iou%': 6.071408, 'num_subgraphs': 1, 'infer_time_core_ms': 53984.311582, 'infer_time_subgraph_ms': 53984.199606, 'ddr_transfer_mb': 0.0, 'perfsim_time_ms': 0.0, 'perfsim_ddr_transfer_mb': 0.0, 'perfsim_gmacs': 0.0}


TASKS                                                       | 100%|##########|| 1/1 [04:43<00:00, 283.46s/it][A
TASKS                                                       | 100%|##########|| 1/1 [04:43<00:00, 283.46s/it]


-------------------------------------------------------------------
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settings: {'include_files': None, 'pipeline_type': 'accuracy', 'num_frames': 1, 'calibration_frames': 1, 'calibration_iterations': 1, 'configs_path': './configs', 'models_path': './edgeai-modelzoo/models', 'modelartifacts_path': './edgeai-benchmark/work_dirs/modelartifacts/AM68A', 'datasets_path': './dependencies/datasets', 'target_device': 'AM68A', 'target_machine': 'pc', 'run_suffix': None, 'parallel_devices': 1, 'tensor_bits': 8, 'runtime_options': {'debug_level': 2}, 'run_import': True, 'run_inference': True, 'run_missing': True, 'detection_threshold': 0.3, 'detection_top_k': 200, 'detection_nms_threshold': None, 'detection_keep_top_k': None, 'save_output': True, 'num_output_frames': 50, 'model_selection': ['segmentation_unet'], 'model_shortlist': None, 'model_exclusion': None, 'task_selection': 'segmentation', 'runtime_selection': None, 'session_type_dict': {'onnx': 'onnxrt', 'tflite': 'tflitert', 'mxnet': 'tvmdlr'}, 'dataset_type_dict': {'ade20k': 'ade_20k'}, 'dataset_selection': 'ade20k32', 'dataset_loading': True, 'config_range': None, 'enable_logging': True, 'verbose': False, 'capture_log': False, 'experimental_models': False, 'rewrite_results': False, 'with_udp': False, 'flip_test': False, 'model_transformation_dict': None, 'report_perfsim': False, 'tidl_offload': True, 'input_optimization': None, 'run_dir_tree_depth': None, 'settings_file': 'settings_import_on_pc.yaml', 'basic_keys': ['include_files', 'pipeline_type', 'num_frames', 'calibration_frames', 'calibration_iterations', 'configs_path', 'models_path', 'modelartifacts_path', 'datasets_path', 'target_device', 'target_machine', 'run_suffix', 'parallel_devices', 'tensor_bits', 'runtime_options', 'run_import', 'run_inference', 'run_missing', 'detection_threshold', 'detection_top_k', 'detection_nms_threshold', 'detection_keep_top_k', 'save_output', 'num_output_frames', 'model_selection', 'model_shortlist', 'model_exclusion', 'task_selection', 'runtime_selection', 'session_type_dict', 'dataset_type_dict', 'dataset_selection', 'dataset_loading', 'config_range', 'enable_logging', 'verbose', 'capture_log', 'experimental_models', 'rewrite_results', 'with_udp', 'flip_test', 'model_transformation_dict', 'report_perfsim', 'tidl_offload', 'input_optimization', 'run_dir_tree_depth', 'settings_file'], 'dataset_cache': None}
results found for 6 models
Report generated at ./edgeai-benchmark/work_dirs/modelartifacts/AM68A
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Pratik Kedar said:
Also which flow you are using for model artifacts generation (TIDL-RT or OSRT), what sdk version you are using ?

We are using OSRT, specifically ONNX runtime. And, our SDK version is 8.6.

Thanks,

Ahmed

0 Pratik Kedar over 2 years ago in reply to Ahmed Mujtaba

TI__Mastermind 24041 points

Thanks for sharing the logs.

Can you share SDK tag you are using for tidl tools repo and if its possible to share the model for our debugging purpose.

0 Ahmed Mujtaba over 2 years ago in reply to Pratik Kedar

Prodigy 235 points

We are using edgeai-benchmark for artifacts generation with version 8.6. In the documentation, it is mentioned has edgeai-benchmark internally downloads and uses tidl-tools.

You can access the model on this drive link,

https://drive.google.com/file/d/1v1EZUXn_gaA4mui6ajmec6UQ7cLYKkh1/view?usp=sharing

Thanks,

Ahmed