ripts/run_python_examples.sh X64 Architecture Running 3 Models - ['cl-tfl-mobilenet_v1_1.0_224', 'ss-tfl-deeplabv3_mnv2_ade20k_float', 'od-tfl-ssd_mobilenet_v2_300_float'] Running_Model : cl-tfl-mobilenet_v1_1.0_224 Running_Model : ss-tfl-deeplabv3_mnv2_ade20k_float Running_Model : od-tfl-ssd_mobilenet_v2_300_float TIDL Meta PipeLine (Proto) File : Number of OD backbone nodes = 0 Size of odBackboneNodeIds = 0 Number of subgraphs:1 , 81 nodes delegated out of 81 nodes Number of subgraphs:1 , 34 nodes delegated out of 34 nodes Warning : concat requires 4D input tensors - only 3 dims present.. Ignore if object detection network Number of subgraphs:1 , 107 nodes delegated out of 107 nodes Warning : concat requires 4D input tensors - only 3 dims present.. Ignore if object detection network WARNING: Batch Norm Layer scale_logits's coeff cannot be found(or not match) in coef file, Random bias will be generated! Only for evaluation usage! Results are all random! Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal ************** Frame index 1 : Running float import ************* ************** Frame index 1 : Running float import ************* Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal ************** Frame index 1 : Running float import ************* WARNING: [TIDL_E_DATAFLOW_INFO_NULL] ti_cnnperfsim.out fails to allocate memory in MSMC. Please look into perfsim log. This model can only be used on PC emulation, it will get fault on target. **************************************************** ** 1 WARNINGS 0 ERRORS ** **************************************************** 0.0s: VX_ZONE_INIT:Enabled 0.8s: VX_ZONE_ERROR:Enabled 0.10s: VX_ZONE_WARNING:Enabled 0.711s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! INFORMATION: [TIDL_ResizeLayer] ResizeBilinear_TIDL_0 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] ResizeBilinear_TIDL_1 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] ResizeBilinear 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/ResizeBilinear 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] ResizeBilinear_1 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] ti_cnnperfsim.out fails to allocate memory in MSMC. Please look into perfsim log. This model can only be used on PC emulation, it will get fault on target. **************************************************** ** 6 WARNINGS 0 ERRORS ** **************************************************** 0.0s: VX_ZONE_INIT:Enabled 0.11s: VX_ZONE_ERROR:Enabled 0.12s: VX_ZONE_WARNING:Enabled 0.402s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! WARNING: [TIDL_E_DATAFLOW_INFO_NULL] ti_cnnperfsim.out fails to allocate memory in MSMC. Please look into perfsim log. This model can only be used on PC emulation, it will get fault on target. **************************************************** ** 1 WARNINGS 0 ERRORS ** **************************************************** 0.0s: VX_ZONE_INIT:Enabled 0.9s: VX_ZONE_ERROR:Enabled 0.10s: VX_ZONE_WARNING:Enabled 0.339s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! ************ Frame index 1 : Running float inference **************** ************ Frame index 2 : Running fixed point mode for calibration **************** ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-tfl-mobilenet_v1_1.0_224/tempDir/86_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 474.26 .... ..... ... .... ..... # 1 . .. ************ Frame index 1 : Running float inference **************** T 487.03 .... ..... ... .... ..... ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-tfl-mobilenet_v1_1.0_224/tempDir/86_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 532.76 .... ..... ... .... ..... # 1 . .. ************ Frame index 2 : Running fixed point mode for calibration **************** T 527.97 .... ..... ... .... ..... ***************** Calibration iteration number 0 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-tfl-ssd_mobilenet_v2_300_float/tempDir/264_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-tfl-mobilenet_v1_1.0_224/tempDir/86_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 541.12 .... ..... ... .... ..... # 1 . .. T 542.12 .... ..... ... .... ..... ***************** Calibration iteration number 1 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-tfl-mobilenet_v1_1.0_224/tempDir/86_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 1580.68 .... ..... ... .... ..... # 1 . .. T 564.05 .... ..... ... .... ..... # 1 . .. T 542.60 .... ..... ... .... ..... ***************** Calibration iteration number 2 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-tfl-mobilenet_v1_1.0_224/tempDir/86_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ************ Frame index 1 : Running float inference **************** T 535.30 .... ..... ... .... ..... # 1 . .. T 1570.61 .... ..... ... .... ..... T 546.83 .... ..... ... .... ..... ***************** Calibration iteration number 3 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-tfl-ssd_mobilenet_v2_300_float/tempDir/264_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-tfl-mobilenet_v1_1.0_224/tempDir/86_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 523.36 .... ..... ... .... ..... # 1 . .. T 1016.06 .... ..... ... .... ..... # 1 . .. T 533.75 .... ..... ... .... ..... ***************** Calibration iteration number 4 completed ************************ ------------------ Network Compiler Traces ----------------------------- successful Memory allocation substitute string tidl_net_ not found **************************************************** ** ALL MODEL CHECK PASSED ** **************************************************** Completed_Model : 1, Name : cl-tfl-mobilenet_v1_1.0_224 , Total time : 4194.30, Offload Time : 0.00 , DDR RW MBs : 0.00, Output File : py_out_cl-tfl-mobilenet_v1_1.0_224_ADE_val_00001801.jpg T 1013.09 .... ..... ... .... ..... ***************** Calibration iteration number 0 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-tfl-ssd_mobilenet_v2_300_float/tempDir/264_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 1048.71 .... ..... ... .... ..... # 1 . .. T 1066.50 .... ..... ... .... ..... ***************** Calibration iteration number 1 completed ************************ ************ Frame index 2 : Running fixed point mode for calibration **************** ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-tfl-deeplabv3_mnv2_ade20k_float/tempDir/201_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-tfl-ssd_mobilenet_v2_300_float/tempDir/264_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 978.42 .... ..... ... .... ..... # 1 . .. T 973.17 .... ..... ... .... ..... ***************** Calibration iteration number 2 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-tfl-ssd_mobilenet_v2_300_float/tempDir/264_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 1033.09 .... ..... ... .... ..... # 1 . .. T 1030.79 .... ..... ... .... ..... ***************** Calibration iteration number 3 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-tfl-ssd_mobilenet_v2_300_float/tempDir/264_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 994.04 .... ..... ... .... ..... # 1 . .. T 999.78 .... ..... ... .... ..... ***************** Calibration iteration number 4 completed ************************ ------------------ Network Compiler Traces ----------------------------- successful Memory allocation substitute string tidl_net_ not found **************************************************** ** ALL MODEL CHECK PASSED ** **************************************************** Completed_Model : 3, Name : od-tfl-ssd_mobilenet_v2_300_float , Total time : 9786.46, Offload Time : 0.00 , DDR RW MBs : 0.00, Output File : py_out_od-tfl-ssd_mobilenet_v2_300_float_ADE_val_00001801.jpg T 13495.86 .... ..... ... .... ..... # 1 . .. T 13470.31 .... ..... ... .... ..... ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-tfl-deeplabv3_mnv2_ade20k_float/tempDir/201_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 5208.85 .... ..... ... .... ..... # 1 . .. T 5150.42 .... ..... ... .... ..... ***************** Calibration iteration number 0 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-tfl-deeplabv3_mnv2_ade20k_float/tempDir/201_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 5122.47 .... ..... ... .... ..... # 1 . .. T 5094.49 .... ..... ... .... ..... ***************** Calibration iteration number 1 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-tfl-deeplabv3_mnv2_ade20k_float/tempDir/201_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 5222.35 .... ..... ... .... ..... # 1 . .. T 5327.63 .... ..... ... .... ..... ***************** Calibration iteration number 2 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-tfl-deeplabv3_mnv2_ade20k_float/tempDir/201_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 5413.74 .... ..... ... .... ..... # 1 . .. T 5375.34 .... ..... ... .... ..... ***************** Calibration iteration number 3 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-tfl-deeplabv3_mnv2_ade20k_float/tempDir/201_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 5397.48 .... ..... ... .... ..... # 1 . .. T 5233.48 .... ..... ... .... ..... ***************** Calibration iteration number 4 completed ************************ ------------------ Network Compiler Traces ----------------------------- successful Memory allocation substitute string tidl_net_ not found INFORMATION: [TIDL_ResizeLayer] ResizeBilinear_TIDL_0 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] ResizeBilinear_TIDL_1 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] ResizeBilinear 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/ResizeBilinear 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] ResizeBilinear_1 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. **************************************************** ** 5 WARNINGS 0 ERRORS ** **************************************************** Completed_Model : 2, Name : ss-tfl-deeplabv3_mnv2_ade20k_float , Total time : 46160.62, Offload Time : 0.00 , DDR RW MBs : 0.00, Output File : py_out_ss-tfl-deeplabv3_mnv2_ade20k_float_ADE_val_00001801.jpg Running 3 Models - ['cl-tfl-mobilenet_v1_1.0_224', 'ss-tfl-deeplabv3_mnv2_ade20k_float', 'od-tfl-ssd_mobilenet_v2_300_float'] Running_Model : cl-tfl-mobilenet_v1_1.0_224 Running_Model : ss-tfl-deeplabv3_mnv2_ade20k_float Running_Model : od-tfl-ssd_mobilenet_v2_300_float Number of subgraphs:1 , 34 nodes delegated out of 34 nodes Number of subgraphs:1 , 81 nodes delegated out of 81 nodes Number of subgraphs:1 , 107 nodes delegated out of 107 nodes 0.0s: VX_ZONE_INIT:Enabled 0.9s: VX_ZONE_ERROR:Enabled 0.10s: VX_ZONE_WARNING:Enabled 0.0s: VX_ZONE_INIT:Enabled 0.27s: VX_ZONE_ERROR:Enabled 0.28s: VX_ZONE_WARNING:Enabled 0.346s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! 0.365s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! 0.0s: VX_ZONE_INIT:Enabled 0.12s: VX_ZONE_ERROR:Enabled 0.13s: VX_ZONE_WARNING:Enabled 0.401s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! , 0 0.511485 missile ,, 1 0.262215 warplane, military plane ,, 2 0.187196 projectile, missile ,, 3 0.025072 cannon ,, 4 0.007760 submarine, pigboat, sub, U-boat , Saving image to ../../../output_images/ Completed_Model : 1, Name : cl-tfl-mobilenet_v1_1.0_224 , Total time : 118.93, Offload Time : 118.93 , DDR RW MBs : 0.00, Output File : py_out_cl-tfl-mobilenet_v1_1.0_224_airshow.jpg Saving image to ../../../output_images/ Completed_Model : 3, Name : od-tfl-ssd_mobilenet_v2_300_float , Total time : 313.00, Offload Time : 312.99 , DDR RW MBs : 0.00, Output File : py_out_od-tfl-ssd_mobilenet_v2_300_float_image1.png Saving image to ../../../output_images/ Completed_Model : 2, Name : ss-tfl-deeplabv3_mnv2_ade20k_float , Total time : 1292.48, Offload Time : 1292.47 , DDR RW MBs : 0.00, Output File : py_out_ss-tfl-deeplabv3_mnv2_ade20k_float_ADE_val_00001801.jpg Available execution providers : ['TIDLExecutionProvider', 'TIDLCompilationProvider', 'CPUExecutionProvider'] Running 4 Models - ['cl-ort-resnet18-v1', 'cl-ort-caffe_squeezenet_v1_1', 'ss-ort-deeplabv3lite_mobilenetv2', 'od-ort-ssd-lite_mobilenetv2_fpn'] Running_Model : cl-ort-resnet18-v1 Downloading ../../../models/public/resnet18_opset9.onnx Running_Model : cl-ort-caffe_squeezenet_v1_1 Downloading ../../../models/public/caffe_squeezenet_v1_1.prototxt Running_Model : ss-ort-deeplabv3lite_mobilenetv2 Downloading ../../../models/public/deeplabv3lite_mobilenetv2.onnx Running_Model : od-ort-ssd-lite_mobilenetv2_fpn Downloading ../../../models/public/ssd-lite_mobilenetv2_fpn.onnx Downloading ../../../models/public/caffe_squeezenet_v1_1.caffemodel Converted model is valid! Preliminary subgraphs created = 1 Final number of subgraphs created are : 1, - Offloaded Nodes - 124, Total Nodes - 124 Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal ************** Frame index 1 : Running float import ************* INFORMATION: [TIDL_ResizeLayer] 571 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] 576 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] ti_cnnperfsim.out fails to allocate memory in MSMC. Please look into perfsim log. This model can only be used on PC emulation, it will get fault on target. **************************************************** ** 3 WARNINGS 0 ERRORS ** **************************************************** 0.0s: VX_ZONE_INIT:Enabled 0.6s: VX_ZONE_ERROR:Enabled 0.7s: VX_ZONE_WARNING:Enabled 0.332s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! caffemodel was successfully loaded add model input information add model output information and model intermediate output information *.onnx model conversion completed removing not constant initializers from model frozen graph has been created Converted model is valid! Downloading ../../../models/public/ssd-lite_mobilenetv2_fpn.prototxt the model has been successfully saved to ../../../models/public/caffe_squeezenet_v1_1.onnx TIDL Meta PipeLine (Proto) File : ../../../models/public/ssd-lite_mobilenetv2_fpn.prototxt ssd Number of OD backbone nodes = 159 Size of odBackboneNodeIds = 159 Preliminary subgraphs created = 1 Final number of subgraphs created are : 1, - Offloaded Nodes - 494, Total Nodes - 494 ********** Frame Index 1 : Running float inference ********** Converted model is valid! Preliminary subgraphs created = 1 Final number of subgraphs created are : 1, - Offloaded Nodes - 68, Total Nodes - 68 TIDL Meta PipeLine (Proto) File : ../../../models/public/ssd-lite_mobilenetv2_fpn.prototxt ssd Warning :: img_w & img_h or img_size is not provided as part of prior_box_param, hence using img_w = 512 and img_h = 512 in prior box decoding Warning :: img_w & img_h or img_size is not provided as part of prior_box_param, hence using img_w = 512 and img_h = 512 in prior box decoding Warning :: img_w & img_h or img_size is not provided as part of prior_box_param, hence using img_w = 512 and img_h = 512 in prior box decoding Warning :: img_w & img_h or img_size is not provided as part of prior_box_param, hence using img_w = 512 and img_h = 512 in prior box decoding Warning :: img_w & img_h or img_size is not provided as part of prior_box_param, hence using img_w = 512 and img_h = 512 in prior box decoding Warning :: img_w & img_h or img_size is not provided as part of prior_box_param, hence using img_w = 512 and img_h = 512 in prior box decoding Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal ************** Frame index 1 : Running float import ************* WARNING: [TIDL_E_DATAFLOW_INFO_NULL] ti_cnnperfsim.out fails to allocate memory in MSMC. Please look into perfsim log. This model can only be used on PC emulation, it will get fault on target. **************************************************** ** 1 WARNINGS 0 ERRORS ** **************************************************** 0.0s: VX_ZONE_INIT:Enabled 0.8s: VX_ZONE_ERROR:Enabled 0.9s: VX_ZONE_WARNING:Enabled 0.439s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal Warning : Requested Output Data Convert Layer is not Added to the network, It is currently not Optimal ************** Frame index 1 : Running float import ************* INFORMATION: [TIDL_ResizeLayer] Resize_153 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] Resize_156 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] ti_cnnperfsim.out fails to allocate memory in MSMC. Please look into perfsim log. This model can only be used on PC emulation, it will get fault on target. **************************************************** ** 3 WARNINGS 0 ERRORS ** **************************************************** 0.0s: VX_ZONE_INIT:Enabled 0.9s: VX_ZONE_ERROR:Enabled 0.10s: VX_ZONE_WARNING:Enabled 0.356s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! ********** Frame Index 1 : Running float inference ********** ********** Frame Index 2 : Running fixed point mode for calibration ********** ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-ort-deeplabv3lite_mobilenetv2/tempDir/566TIDL_cast_out_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ********** Frame Index 2 : Running fixed point mode for calibration ********** ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-caffe_squeezenet_v1_1/tempDir/prob_Y_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 305.59 .... ..... ... .... ..... # 1 . .. T 301.56 .... ..... ... .... ..... ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-caffe_squeezenet_v1_1/tempDir/prob_Y_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 238.00 .... ..... ... .... ..... # 1 . .. T 229.80 .... ..... ... .... ..... ***************** Calibration iteration number 0 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-caffe_squeezenet_v1_1/tempDir/prob_Y_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 226.05 .... ..... ... .... ..... # 1 . .. ********** Frame Index 1 : Running float inference ********** T 219.20 .... ..... ... .... ..... ***************** Calibration iteration number 1 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-caffe_squeezenet_v1_1/tempDir/prob_Y_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 238.23 .... ..... ... .... ..... # 1 . .. T 238.13 .... ..... ... .... ..... ***************** Calibration iteration number 2 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-caffe_squeezenet_v1_1/tempDir/prob_Y_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 234.60 .... ..... ... .... ..... # 1 . .. T 229.31 .... ..... ... .... ..... ***************** Calibration iteration number 3 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-caffe_squeezenet_v1_1/tempDir/prob_Y_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 239.89 .... ..... ... .... ..... # 1 . .. T 229.35 .... ..... ... .... ..... ***************** Calibration iteration number 4 completed ************************ ------------------ Network Compiler Traces ----------------------------- successful Memory allocation substitute string tidl_net_ not found **************************************************** ** ALL MODEL CHECK PASSED ** **************************************************** Completed_Model : 2, Name : cl-ort-caffe_squeezenet_v1_1 , Total time : 2335.22, Offload Time : 294.18 , DDR RW MBs : 0, Output File : py_out_cl-ort-caffe_squeezenet_v1_1_ADE_val_00001801.jpg T 3567.88 .... ..... ... .... ..... # 1 . .. ********** Frame Index 2 : Running fixed point mode for calibration ********** ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-ort-ssd-lite_mobilenetv2_fpn/tempDir/boxeslabels_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 2123.56 .... ..... ... .... ..... # 1 . .. T 3377.50 .... ..... ... .... ..... ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-ort-deeplabv3lite_mobilenetv2/tempDir/566TIDL_cast_out_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 2027.05 .... ..... ... .... ..... ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-ort-ssd-lite_mobilenetv2_fpn/tempDir/boxeslabels_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 2380.03 .... ..... ... .... ..... # 1 . .. T 3738.21 .... ..... ... .... ..... # 1 . .. T 2354.68 .... ..... ... .... ..... ***************** Calibration iteration number 0 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-ort-ssd-lite_mobilenetv2_fpn/tempDir/boxeslabels_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . ..Converted model is valid! 2022-04-21 11:43:00.620251230 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622074544 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622080860 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.0.downsample.1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622086837 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.0.downsample.1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622091961 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622097094 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622102482 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.0.downsample.1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622107747 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622112605 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622117714 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622123029 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622128619 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622133902 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622138755 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622143400 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622148206 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622153084 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622158765 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622163559 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:00.622169038 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. Preliminary subgraphs created = 1 Final number of subgraphs created are : 1, - Offloaded Nodes - 52, Total Nodes - 52 T 3791.61 .... ..... ... .... ..... ***************** Calibration iteration number 0 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-ort-deeplabv3lite_mobilenetv2/tempDir/566TIDL_cast_out_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ************** Frame index 1 : Running float import ************* WARNING: [TIDL_E_DATAFLOW_INFO_NULL] ti_cnnperfsim.out fails to allocate memory in MSMC. Please look into perfsim log. This model can only be used on PC emulation, it will get fault on target. **************************************************** ** 1 WARNINGS 0 ERRORS ** **************************************************** 0.0s: VX_ZONE_INIT:Enabled 0.6s: VX_ZONE_ERROR:Enabled 0.8s: VX_ZONE_WARNING:Enabled 0.311s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! T 2514.11 .... ..... ... .... ..... # 1 . .. ********** Frame Index 1 : Running float inference ********** T 2400.66 .... ..... ... .... ..... ***************** Calibration iteration number 1 completed ************************ ********** Frame Index 2 : Running fixed point mode for calibration ********** ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-resnet18-v1/tempDir/191_tidl_io_.qunat_stats_config.txt ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-ort-ssd-lite_mobilenetv2_fpn/tempDir/boxeslabels_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 4000.78 .... ..... ... .... ..... # 1 . .. T 1182.22 .... ..... ... .... ..... # 1 . .. T 1178.04 .... ..... ... .... ..... T 2375.80 .... ..... ... .... ..... # 1 . .. ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-resnet18-v1/tempDir/191_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 641.08 .... ..... ... .... ..... # 1 . .. T 637.81 .... ..... ... .... ..... ***************** Calibration iteration number 0 completed ************************ T 3956.45 .... ..... ... .... ..... ***************** Calibration iteration number 1 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-resnet18-v1/tempDir/191_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-ort-deeplabv3lite_mobilenetv2/tempDir/566TIDL_cast_out_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 2426.68 .... ..... ... .... ..... ***************** Calibration iteration number 2 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-ort-ssd-lite_mobilenetv2_fpn/tempDir/boxeslabels_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 648.55 .... ..... ... .... ..... # 1 . .. T 648.96 .... ..... ... .... ..... ***************** Calibration iteration number 1 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-resnet18-v1/tempDir/191_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 637.77 .... ..... ... .... ..... # 1 . .. T 628.32 .... ..... ... .... ..... ***************** Calibration iteration number 2 completed ************************ T 2513.77 .... ..... ... .... ..... # 1 . .. ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-resnet18-v1/tempDir/191_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 3863.65 .... ..... ... .... ..... # 1 . .. T 641.37 .... ..... ... .... ..... # 1 . .. T 637.52 .... ..... ... .... ..... ***************** Calibration iteration number 3 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/cl-ort-resnet18-v1/tempDir/191_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 2467.16 .... ..... ... .... ..... ***************** Calibration iteration number 3 completed ************************ T 635.57 .... ..... ... .... ..... # 1 . .. ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/od-ort-ssd-lite_mobilenetv2_fpn/tempDir/boxeslabels_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 637.23 .... ..... ... .... ..... ***************** Calibration iteration number 4 completed ************************ ------------------ Network Compiler Traces ----------------------------- successful Memory allocation substitute string tidl_net_ not found **************************************************** ** ALL MODEL CHECK PASSED ** **************************************************** Completed_Model : 1, Name : cl-ort-resnet18-v1 , Total time : 7018.86, Offload Time : 1188.73 , DDR RW MBs : 0, Output File : py_out_cl-ort-resnet18-v1_ADE_val_00001801.jpg T 3806.35 .... ..... ... .... ..... ***************** Calibration iteration number 2 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-ort-deeplabv3lite_mobilenetv2/tempDir/566TIDL_cast_out_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 2505.98 .... ..... ... .... ..... # 1 . .. T 2403.59 .... ..... ... .... ..... ***************** Calibration iteration number 4 completed ************************ ------------------ Network Compiler Traces ----------------------------- successful Memory allocation substitute string tidl_net_ not found INFORMATION: [TIDL_ResizeLayer] Resize_153 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] Resize_156 Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize. **************************************************** ** 2 WARNINGS 0 ERRORS ** **************************************************** Completed_Model : 4, Name : od-ort-ssd-lite_mobilenetv2_fpn , Total time : 17277.04, Offload Time : 2129.65 , DDR RW MBs : 0, Output File : py_out_od-ort-ssd-lite_mobilenetv2_fpn_ADE_val_00001801.jpg T 3948.75 .... ..... ... .... ..... # 1 . .. T 3901.57 .... ..... ... .... ..... ***************** Calibration iteration number 3 completed ************************ ~~~~~Running TIDL in PC emulation mode to collect Activations range for each layer~~~~~ Processing config file #0 : /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/model-artifacts/ss-ort-deeplabv3lite_mobilenetv2/tempDir/566TIDL_cast_out_tidl_io_.qunat_stats_config.txt ----------------------- TIDL Process with REF_ONLY FLOW ------------------------ # 0 . .. T 3618.03 .... ..... ... .... ..... # 1 . .. T 3615.57 .... ..... ... .... ..... ***************** Calibration iteration number 4 completed ************************ ------------------ Network Compiler Traces ----------------------------- successful Memory allocation substitute string tidl_net_ not found INFORMATION: [TIDL_ResizeLayer] 571 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] 576 Any resize ratio which is power of 2 and greater than 4 will be placed by combination of 4x4 resize layer and 2x2 resize layer. For example a 8x8 resize will be replaced by 4x4 resize followed by 2x2 resize. **************************************************** ** 2 WARNINGS 0 ERRORS ** **************************************************** Completed_Model : 3, Name : ss-ort-deeplabv3lite_mobilenetv2 , Total time : 27679.58, Offload Time : 4512.37 , DDR RW MBs : 0, Output File : py_out_ss-ort-deeplabv3lite_mobilenetv2_ADE_val_00001801.jpg Available execution providers : ['TIDLExecutionProvider', 'TIDLCompilationProvider', 'CPUExecutionProvider'] Running 4 Models - ['cl-ort-resnet18-v1', 'cl-ort-caffe_squeezenet_v1_1', 'ss-ort-deeplabv3lite_mobilenetv2', 'od-ort-ssd-lite_mobilenetv2_fpn'] Running_Model : cl-ort-resnet18-v1 Running_Model : cl-ort-caffe_squeezenet_v1_1 Running_Model : ss-ort-deeplabv3lite_mobilenetv2 Running_Model : od-ort-ssd-lite_mobilenetv2_fpn libtidl_onnxrt_EP loaded 0x3a6ec80 libtidl_onnxrt_EP loaded 0x3502e30 2022-04-21 11:43:32.890967946 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891011938 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891018694 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.0.downsample.1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891024159 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.0.downsample.1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891029255 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891034446 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891040543 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.0.downsample.1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891045626 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891050336 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891055306 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891060594 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891068208 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891073448 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891078092 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer1.1.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891082656 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891087428 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer4.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891092262 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.0.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891097790 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer3.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891102463 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.0.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. 2022-04-21 11:43:32.891107657 [W:onnxruntime:, graph.cc:3106 CleanUnusedInitializers] Removing initializer 'layer2.1.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model. libtidl_onnxrt_EP loaded 0x35a3b00 libtidl_onnxrt_EP loaded 0x411adf0 Final number of subgraphs created are : 1, - Offloaded Nodes - 68, Total Nodes - 68 Final number of subgraphs created are : 1, - Offloaded Nodes - 124, Total Nodes - 124 0.0s: VX_ZONE_INIT:Enabled 0.16s: VX_ZONE_ERROR:Enabled 0.18s: VX_ZONE_WARNING:Enabled 0.426s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! 0.0s: VX_ZONE_INIT:Enabled 0.9s: VX_ZONE_ERROR:Enabled 0.11s: VX_ZONE_WARNING:Enabled 0.348s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! Final number of subgraphs created are : 1, - Offloaded Nodes - 494, Total Nodes - 494 Final number of subgraphs created are : 1, - Offloaded Nodes - 52, Total Nodes - 52 0.0s: VX_ZONE_INIT:Enabled 0.10s: VX_ZONE_ERROR:Enabled 0.11s: VX_ZONE_WARNING:Enabled 0.392s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! 0.0s: VX_ZONE_INIT:Enabled 0.9s: VX_ZONE_ERROR:Enabled 0.10s: VX_ZONE_WARNING:Enabled 0.325s: VX_ZONE_INIT:[tivxInit:178] Initialization Done !!! , 0 0.518756 warplane, military plane ,, 1 0.321064 aircraft carrier, carrier, flattop, attack aircraft carrier ,, 2 0.108971 airliner ,, 3 0.020307 missile ,, 4 0.015969 projectile, missile , Saving image to ../../../output_images/ Completed_Model : 2, Name : cl-ort-caffe_squeezenet_v1_1 , Total time : 102.56, Offload Time : 102.51 , DDR RW MBs : 0, Output File : py_out_cl-ort-caffe_squeezenet_v1_1_airshow.jpg , 0 23.311415 warplane, military plane ,, 1 22.239624 aircraft carrier, carrier, flattop, attack aircraft carrier ,, 2 18.488363 projectile, missile ,, 3 18.220415 missile ,, 4 15.540942 wing , Saving image to ../../../output_images/ Completed_Model : 1, Name : cl-ort-resnet18-v1 , Total time : 339.18, Offload Time : 339.15 , DDR RW MBs : 0, Output File : py_out_cl-ort-resnet18-v1_airshow.jpg Saving image to ../../../output_images/ Completed_Model : 4, Name : od-ort-ssd-lite_mobilenetv2_fpn , Total time : 771.48, Offload Time : 771.40 , DDR RW MBs : 0, Output File : py_out_od-ort-ssd-lite_mobilenetv2_fpn_ADE_val_00001801.jpg Saving image to ../../../output_images/ Completed_Model : 3, Name : ss-ort-deeplabv3lite_mobilenetv2 , Total time : 978.30, Offload Time : 978.25 , DDR RW MBs : 0, Output File : py_out_ss-ort-deeplabv3lite_mobilenetv2_ADE_val_00001801.jpg Downloading ../../../models/public/mobilenetv2-1.0.onnx Converted model is valid! Traceback (most recent call last): File "tvm_compilation_onnx_example.py", line 38, in from tvm import relay File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/__init__.py", line 26, in from ._ffi.base import TVMError, __version__ File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/__init__.py", line 28, in from .base import register_error File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 71, in _LIB, _LIB_NAME = _load_lib() File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 57, in _load_lib lib = ctypes.CDLL(lib_path[0], ctypes.RTLD_GLOBAL) File "/usr/lib/python3.6/ctypes/__init__.py", line 348, in __init__ self._handle = _dlopen(self._name, mode) OSError: libtinfo.so.5: cannot open shared object file: No such file or directory Downloading ../../../models/public/inception_v3.tflite /home/achavan8/Documents/Projects/AutoHitch/Model_Training/TI-DL-EVM_local/edgeai-tidl-tools/models/public/inception_v3.tflite Traceback (most recent call last): File "tvm_compilation_tflite_example.py", line 40, in from tvm import relay File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/__init__.py", line 26, in from ._ffi.base import TVMError, __version__ File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/__init__.py", line 28, in from .base import register_error File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 71, in _LIB, _LIB_NAME = _load_lib() File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 57, in _load_lib lib = ctypes.CDLL(lib_path[0], ctypes.RTLD_GLOBAL) File "/usr/lib/python3.6/ctypes/__init__.py", line 348, in __init__ self._handle = _dlopen(self._name, mode) OSError: libtinfo.so.5: cannot open shared object file: No such file or directory Traceback (most recent call last): File "tvm_compilation_onnx_example.py", line 38, in from tvm import relay File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/__init__.py", line 26, in from ._ffi.base import TVMError, __version__ File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/__init__.py", line 28, in from .base import register_error File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 71, in _LIB, _LIB_NAME = _load_lib() File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 57, in _load_lib lib = ctypes.CDLL(lib_path[0], ctypes.RTLD_GLOBAL) File "/usr/lib/python3.6/ctypes/__init__.py", line 348, in __init__ self._handle = _dlopen(self._name, mode) OSError: libtinfo.so.5: cannot open shared object file: No such file or directory Traceback (most recent call last): File "tvm_compilation_tflite_example.py", line 40, in from tvm import relay File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/__init__.py", line 26, in from ._ffi.base import TVMError, __version__ File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/__init__.py", line 28, in from .base import register_error File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 71, in _LIB, _LIB_NAME = _load_lib() File "/home/achavan8/.local/lib/python3.6/site-packages/tvm/_ffi/base.py", line 57, in _load_lib lib = ctypes.CDLL(lib_path[0], ctypes.RTLD_GLOBAL) File "/usr/lib/python3.6/ctypes/__init__.py", line 348, in __init__ self._handle = _dlopen(self._name, mode) OSError: libtinfo.so.5: cannot open shared object file: No such file or directory Traceback (most recent call last): File "tvm_compilation_mxnet_example.py", line 37, in from gluoncv import model_zoo ModuleNotFoundError: No module named 'gluoncv' Running Inference on Model - ../../../model-artifacts/cl-dlr-tflite_inceptionnetv3 2022-04-21 12:44:46,130 ERROR error in DLRModel instantiation model_path ../../../model-artifacts/cl-dlr-tflite_inceptionnetv3 doesn't exist Traceback (most recent call last): File "/home/achavan8/.local/lib/python3.6/site-packages/dlr/api.py", line 89, in __init__ self._impl = DLRModelImpl(model_path, dev_type, dev_id, error_log_file, use_default_dlr) File "/home/achavan8/.local/lib/python3.6/site-packages/dlr/dlr_model.py", line 65, in __init__ raise ValueError("model_path %s doesn't exist" % model_path) ValueError: model_path ../../../model-artifacts/cl-dlr-tflite_inceptionnetv3 doesn't exist Traceback (most recent call last): File "dlr_inference_example.py", line 194, in postprocess_for_tflite_inceptionnetv3, 0) File "dlr_inference_example.py", line 157, in model_create_and_run model = DLRModel(model_dir, 'cpu') File "/home/achavan8/.local/lib/python3.6/site-packages/dlr/api.py", line 92, in __init__ raise ex File "/home/achavan8/.local/lib/python3.6/site-packages/dlr/api.py", line 89, in __init__ self._impl = DLRModelImpl(model_path, dev_type, dev_id, error_log_file, use_default_dlr) File "/home/achavan8/.local/lib/python3.6/site-packages/dlr/dlr_model.py", line 65, in __init__ raise ValueError("model_path %s doesn't exist" % model_path) ValueError: model_path ../../../model-artifacts/cl-dlr-tflite_inceptionnetv3 doesn't exist