oot@30229850e11c:/home/root/examples/osrt_python/ort# python3 onnxrt_ep_dock927_condlanet_fp32.py -c | tee log_condlanet_slicev2_c.txt ***** WARNING : tensor_bits = 32 -- Compiling for floating point - target execution is not supported for 32 bit compilation !! ***** tidl_tools_path = /home/root/tidl_tools artifacts_folder = ../../../model-artifacts//condlanet_org/ tidl_tensor_bits = 32 debug_level = 6 num_tidl_subgraphs = 16 tidl_denylist = tidl_denylist_layer_name = tidl_denylist_layer_type = tidl_allowlist_layer_name = model_type = tidl_calibration_accuracy_level = 64 tidl_calibration_options:num_frames_calibration = 3 tidl_calibration_options:bias_calibration_iterations = 3 mixed_precision_factor = -1.000000 model_group_id = 0 power_of_2_quantization = 2 ONNX QDQ Enabled = 0 enable_high_resolution_optimization = 0 pre_batchnorm_fold = 1 add_data_convert_ops = 0 output_feature_16bit_names_list = m_params_16bit_names_list = m_single_core_layers_names_list = reserved_compile_constraints_flag = 1601 ti_internal_reserved_1 = WARNING : 'meta_layers_names_list' is not provided - running OD post processing in ARM mode Number of OD backbone nodes = 0 Size of odBackboneNodeIds = 0 Layer 0 -- layer name -- Conv_0 Input dims size = 4 dims --- 1 3 320 800 Supported TIDL layer type --- Conv -- Conv_0 Layer 1 -- layer name -- Relu_1 Input dims size = 4 dims --- 1 64 160 400 Supported TIDL layer type --- Relu -- Relu_1 Layer 2 -- layer name -- MaxPool_2 Input dims size = 4 dims --- 1 64 160 400 Supported TIDL layer type --- MaxPool -- MaxPool_2 Layer 3 -- layer name -- Conv_3 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Conv -- Conv_3 Layer 4 -- layer name -- Relu_4 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Relu -- Relu_4 Layer 5 -- layer name -- Conv_5 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Conv -- Conv_5 Layer 6 -- layer name -- Add_6 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Add -- Add_6 Layer 7 -- layer name -- Relu_7 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Relu -- Relu_7 Layer 8 -- layer name -- Conv_8 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Conv -- Conv_8 Layer 9 -- layer name -- Relu_9 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Relu -- Relu_9 Layer 10 -- layer name -- Conv_10 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Conv -- Conv_10 Layer 11 -- layer name -- Add_11 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Add -- Add_11 Layer 12 -- layer name -- Relu_12 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Relu -- Relu_12 Layer 13 -- layer name -- Conv_13 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Conv -- Conv_13 Layer 14 -- layer name -- Relu_14 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Relu -- Relu_14 Layer 15 -- layer name -- Conv_15 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Conv -- Conv_15 Layer 16 -- layer name -- Conv_16 Input dims size = 4 dims --- 1 64 80 200 Supported TIDL layer type --- Conv -- Conv_16 Layer 17 -- layer name -- Add_17 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Add -- Add_17 Layer 18 -- layer name -- Relu_18 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Relu -- Relu_18 Layer 19 -- layer name -- Conv_19 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Conv -- Conv_19 Layer 20 -- layer name -- Relu_20 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Relu -- Relu_20 Layer 21 -- layer name -- Conv_21 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Conv -- Conv_21 Layer 22 -- layer name -- Add_22 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Add -- Add_22 Layer 23 -- layer name -- Relu_23 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Relu -- Relu_23 Layer 24 -- layer name -- Conv_24 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Conv -- Conv_24 Layer 25 -- layer name -- Relu_25 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Relu -- Relu_25 Layer 26 -- layer name -- Conv_26 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Conv -- Conv_26 Layer 27 -- layer name -- Conv_27 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Conv -- Conv_27 Layer 28 -- layer name -- Add_28 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Add -- Add_28 Layer 29 -- layer name -- Relu_29 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Relu -- Relu_29 Layer 30 -- layer name -- Conv_30 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Conv -- Conv_30 Layer 31 -- layer name -- Relu_31 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Relu -- Relu_31 Layer 32 -- layer name -- Conv_32 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Conv -- Conv_32 Layer 33 -- layer name -- Add_33 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Add -- Add_33 Layer 34 -- layer name -- Relu_34 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Relu -- Relu_34 Layer 35 -- layer name -- Conv_35 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Conv -- Conv_35 Layer 36 -- layer name -- Relu_36 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Relu -- Relu_36 Layer 37 -- layer name -- Conv_37 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Conv -- Conv_37 Layer 38 -- layer name -- Conv_38 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Conv -- Conv_38 Layer 39 -- layer name -- Add_39 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Add -- Add_39 Layer 40 -- layer name -- Relu_40 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Relu -- Relu_40 Layer 41 -- layer name -- Conv_41 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Conv -- Conv_41 Layer 42 -- layer name -- Relu_42 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Relu -- Relu_42 Layer 43 -- layer name -- Conv_43 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Conv -- Conv_43 Layer 44 -- layer name -- Add_44 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Add -- Add_44 Layer 45 -- layer name -- Relu_45 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Relu -- Relu_45 Layer 46 -- layer name -- Conv_46 Input dims size = 4 dims --- 1 512 10 25 Supported TIDL layer type --- Conv -- Conv_46 Layer 47 -- layer name -- Relu_47 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Relu -- Relu_47 Layer 48 -- layer name -- Add_58 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Add -- Add_58 Layer 49 -- layer name -- Conv_59 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_59 Layer 50 -- layer name -- Reshape_64 Input dims size = 4 dims --- 1 16 10 25 Supported TIDL layer type --- Reshape -- Reshape_64 Layer 51 -- layer name -- Transpose_65 Input dims size = 3 dims --- 1 16 250 Supported TIDL layer type --- Transpose -- Transpose_65 Layer 52 -- layer name -- Conv_66 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_66 Layer 53 -- layer name -- Reshape_71 Input dims size = 4 dims --- 1 16 10 25 Supported TIDL layer type --- Reshape -- Reshape_71 Layer 54 -- layer name -- MatMul_72 Input dims size = 3 dims --- 1 250 16 Supported TIDL layer type --- MatMul -- MatMul_72 Layer 55 -- layer name -- Softmax_73 Input dims size = 3 dims --- 1 250 250 Supported TIDL layer type --- Softmax -- Softmax_73 Layer 56 -- layer name -- Transpose_74 Input dims size = 3 dims --- 1 250 250 Supported TIDL layer type --- Transpose -- Transpose_74 Layer 57 -- layer name -- Conv_75 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_75 Layer 58 -- layer name -- Reshape_80 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Reshape -- Reshape_80 Layer 59 -- layer name -- MatMul_81 Input dims size = 3 dims --- 1 64 250 Supported TIDL layer type --- MatMul -- MatMul_81 Layer 60 -- layer name -- Reshape_86 Input dims size = 3 dims --- 1 64 250 Supported TIDL layer type --- Reshape -- Reshape_86 Layer 61 -- layer name -- custom_added_Mul0 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Mul -- custom_added_Mul0 Layer 62 -- layer name -- Add_88 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Add -- Add_88 Layer 63 -- layer name -- Conv_89 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_89 Layer 64 -- layer name -- Relu_90 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Relu -- Relu_90 Layer 65 -- layer name -- Conv_91 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_91 Layer 66 -- layer name -- Relu_92 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Relu -- Relu_92 Layer 67 -- layer name -- Add_103 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Add -- Add_103 Layer 68 -- layer name -- Conv_104 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_104 Layer 69 -- layer name -- Reshape_109 Input dims size = 4 dims --- 1 16 10 25 Supported TIDL layer type --- Reshape -- Reshape_109 Layer 70 -- layer name -- Transpose_110 Input dims size = 3 dims --- 1 16 250 Supported TIDL layer type --- Transpose -- Transpose_110 Layer 71 -- layer name -- Conv_111 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_111 Layer 72 -- layer name -- Reshape_116 Input dims size = 4 dims --- 1 16 10 25 Supported TIDL layer type --- Reshape -- Reshape_116 Layer 73 -- layer name -- MatMul_117 Input dims size = 3 dims --- 1 250 16 Supported TIDL layer type --- MatMul -- MatMul_117 Layer 74 -- layer name -- Softmax_118 Input dims size = 3 dims --- 1 250 250 Supported TIDL layer type --- Softmax -- Softmax_118 Layer 75 -- layer name -- Transpose_119 Input dims size = 3 dims --- 1 250 250 Supported TIDL layer type --- Transpose -- Transpose_119 Layer 76 -- layer name -- Conv_120 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_120 Layer 77 -- layer name -- Reshape_125 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Reshape -- Reshape_125 Layer 78 -- layer name -- MatMul_126 Input dims size = 3 dims --- 1 64 250 Supported TIDL layer type --- MatMul -- MatMul_126 Layer 79 -- layer name -- Reshape_131 Input dims size = 3 dims --- 1 64 250 Supported TIDL layer type --- Reshape -- Reshape_131 Layer 80 -- layer name -- custom_added_Mul1 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Mul -- custom_added_Mul1 Layer 81 -- layer name -- Add_133 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Add -- Add_133 Layer 82 -- layer name -- Conv_134 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_134 Layer 83 -- layer name -- Relu_135 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Relu -- Relu_135 Layer 84 -- layer name -- Conv_138 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Conv -- Conv_138 Layer 85 -- layer name -- Upsample_139 Input dims size = 4 dims --- 1 64 10 25 Supported TIDL layer type --- Upsample -- Upsample_139 Layer 86 -- layer name -- Conv_137 Input dims size = 4 dims --- 1 256 20 50 Supported TIDL layer type --- Conv -- Conv_137 Layer 87 -- layer name -- Add_140 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Add -- Add_140 Layer 88 -- layer name -- Conv_144 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Conv -- Conv_144 Layer 89 -- layer name -- Conv_148 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Conv -- Conv_148 Layer 90 -- layer name -- Relu_149 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Relu -- Relu_149 Layer 91 -- layer name -- Conv_150 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Conv -- Conv_150 Layer 92 -- layer name -- Sigmoid_166 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Sigmoid -- Sigmoid_166 Layer 93 -- layer name -- Clip_167 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Clip -- Clip_167 Layer 94 -- layer name -- custom_added_Mul9 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Mul -- custom_added_Mul9 Layer 95 -- layer name -- MaxPool_182 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- MaxPool -- MaxPool_182 Layer 96 -- layer name -- custom_added_Add1 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Add -- custom_added_Add1 Layer 97 -- layer name -- custom_added_Add0 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Add -- custom_added_Add0 Layer 98 -- layer name -- Div_186 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Div -- Div_186 Layer 99 -- layer name -- custom_added_Mul8 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Mul -- custom_added_Mul8 Layer 100 -- layer name -- custom_added_Add3 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Add -- custom_added_Add3 Layer 101 -- layer name -- Mul_189 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Mul -- Mul_189 Layer 102 -- layer name -- Squeeze_190 Input dims size = 4 dims --- 1 8 20 50 Supported TIDL layer type --- Squeeze -- Squeeze_190 Layer 103 -- layer name -- Reshape_192 Input dims size = 3 dims --- 8 20 50 Supported TIDL layer type --- Reshape -- Reshape_192 Layer 104 -- layer name -- TopK_193 Input dims size = 1 dims --- 8000 Unsupported (imports) TIDL layer type for ONNX op type --- TopK Layer 105 -- layer name -- Reshape_195 Input dims size = 1 dims --- 6 Supported TIDL layer type --- Reshape -- Reshape_195 Layer 106 -- layer name -- custom_added_Mul2 Input dims size = 2 dims --- 6 1 Supported TIDL layer type --- Mul -- custom_added_Mul2 Layer 107 -- layer name -- Slice_203 Input dims size = 2 dims --- 6 134 Supported TIDL layer type --- Slice -- Slice_203 Layer 108 -- layer name -- Gather_207 Input dims size = 2 dims --- 6 67 Unsupported (TIDL check) TIDL layer type --- Gather Layer 109 -- layer name -- Conv_151 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Conv -- Conv_151 Layer 110 -- layer name -- Relu_152 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Relu -- Relu_152 Layer 111 -- layer name -- Conv_153 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Conv -- Conv_153 Layer 112 -- layer name -- Reshape_172 Input dims size = 4 dims --- 1 1072 20 50 Supported TIDL layer type --- Reshape -- Reshape_172 Layer 113 -- layer name -- Transpose_179 Input dims size = 5 dims --- 1 8 134 20 50 Supported TIDL layer type --- Transpose -- Transpose_179 Layer 114 -- layer name -- Reshape_181 Input dims size = 5 dims --- 1 8 20 50 134 Supported TIDL layer type --- Reshape -- Reshape_181 Layer 115 -- layer name -- Slice_205 Input dims size = 2 dims --- 8000 134 Supported TIDL layer type --- Slice -- Slice_205 Layer 116 -- layer name -- Gather_209 Input dims size = 2 dims --- 8000 67 Supported TIDL layer type --- Gather -- Gather_209 Layer 117 -- layer name -- Slice_228 Input dims size = 2 dims --- 6 67 Supported TIDL layer type --- Slice -- Slice_228 Layer 118 -- layer name -- Reshape_236 Input dims size = 2 dims --- 6 66 Supported TIDL layer type --- Reshape -- Reshape_236 Layer 119 -- layer name -- Reshape_243 Input dims size = 4 dims --- 6 66 1 1 Supported TIDL layer type --- Reshape -- Reshape_243 Layer 120 -- layer name -- Upsample_141 Input dims size = 4 dims --- 1 64 20 50 Supported TIDL layer type --- Upsample -- Upsample_141 Layer 121 -- layer name -- Conv_136 Input dims size = 4 dims --- 1 128 40 100 Supported TIDL layer type --- Conv -- Conv_136 Layer 122 -- layer name -- Add_142 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Add -- Add_142 Layer 123 -- layer name -- Conv_143 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Conv -- Conv_143 Layer 124 -- layer name -- Conv_173 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Conv -- Conv_173 Layer 125 -- layer name -- Relu_174 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Relu -- Relu_174 Layer 126 -- layer name -- Conv_175 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Conv -- Conv_175 Layer 127 -- layer name -- Relu_176 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Relu -- Relu_176 Layer 128 -- layer name -- Conv_177 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Conv -- Conv_177 Layer 129 -- layer name -- Relu_178 Input dims size = 4 dims --- 1 64 40 100 Supported TIDL layer type --- Relu -- Relu_178 Layer 130 -- layer name -- Concat_217 Input dims size = 0 dims --- Supported TIDL layer type --- Concat -- Concat_217 Layer 131 -- layer name -- Concat_220 Input dims size = 4 dims --- 1 66 40 100 Supported TIDL layer type --- Concat -- Concat_220 Layer 132 -- layer name -- Reshape_224 Input dims size = 4 dims --- 1 396 40 100 Supported TIDL layer type --- Reshape -- Reshape_224 Layer 133 -- layer name -- Mul_244 Input dims size = 4 dims --- 1 396 40 100 Unsupported (TIDL check) TIDL layer type --- Mul Layer 134 -- layer name -- Reshape_246 Input dims size = 4 dims --- 1 396 40 100 Supported TIDL layer type --- Reshape -- Reshape_246 Layer 135 -- layer name -- ReduceSum_247 Input dims size = 5 dims --- 1 6 66 40 100 Unsupported (imports) TIDL layer type for ONNX op type --- ReduceSum Layer 136 -- layer name -- Slice_229 Input dims size = 2 dims --- 6 67 Supported TIDL layer type --- Slice -- Slice_229 Layer 137 -- layer name -- custom_added_Reshape1 Input dims size = 2 dims --- 6 1 Supported TIDL layer type --- Reshape -- custom_added_Reshape1 Layer 138 -- layer name -- custom_added_Add5 Input dims size = 4 dims --- 1 1 1 6 Supported TIDL layer type --- Add -- custom_added_Add5 Layer 139 -- layer name -- Reshape_249 Input dims size = 4 dims --- 1 1 1 6 Supported TIDL layer type --- Reshape -- Reshape_249 Layer 140 -- layer name -- Add_250 Input dims size = 4 dims --- 1 6 40 100 Unsupported (TIDL check) TIDL layer type --- Add Layer 141 -- layer name -- Reshape_254 Input dims size = 4 dims --- 1 6 40 100 Supported TIDL layer type --- Reshape -- Reshape_254 Layer 142 -- layer name -- Transpose_305 Input dims size = 4 dims --- 1 6 40 100 Supported TIDL layer type --- Transpose -- Transpose_305 Layer 143 -- layer name -- Reshape_312 Input dims size = 4 dims --- 1 6 100 40 Supported TIDL layer type --- Reshape -- Reshape_312 Layer 144 -- layer name -- Conv_313 Input dims size = 3 dims --- 6 100 40 Unsupported (TIDL check) TIDL layer type --- Conv Layer 145 -- layer name -- Relu_314 Input dims size = 3 dims --- 6 64 40 Supported TIDL layer type --- Relu -- Relu_314 Layer 146 -- layer name -- Conv_315 Input dims size = 3 dims --- 6 64 40 Unsupported (TIDL check) TIDL layer type --- Conv Layer 147 -- layer name -- Transpose_316 Input dims size = 3 dims --- 6 2 40 Supported TIDL layer type --- Transpose -- Transpose_316 Layer 148 -- layer name -- Slice_204 Input dims size = 2 dims --- 6 134 Supported TIDL layer type --- Slice -- Slice_204 Layer 149 -- layer name -- Gather_257 Input dims size = 2 dims --- 6 67 Unsupported (TIDL check) TIDL layer type --- Gather Layer 150 -- layer name -- Slice_255 Input dims size = 2 dims --- 8000 134 Supported TIDL layer type --- Slice -- Slice_255 Layer 151 -- layer name -- Gather_259 Input dims size = 2 dims --- 8000 67 Supported TIDL layer type --- Gather -- Gather_259 Layer 152 -- layer name -- Slice_278 Input dims size = 2 dims --- 6 67 Supported TIDL layer type --- Slice -- Slice_278 Layer 153 -- layer name -- Reshape_286 Input dims size = 2 dims --- 6 66 Supported TIDL layer type --- Reshape -- Reshape_286 Layer 154 -- layer name -- Reshape_293 Input dims size = 4 dims --- 6 66 1 1 Supported TIDL layer type --- Reshape -- Reshape_293 Layer 155 -- layer name -- Reshape_274 Input dims size = 4 dims --- 1 396 40 100 Supported TIDL layer type --- Reshape -- Reshape_274 Layer 156 -- layer name -- Mul_294 Input dims size = 4 dims --- 1 396 40 100 Unsupported (TIDL check) TIDL layer type --- Mul Layer 157 -- layer name -- Reshape_296 Input dims size = 4 dims --- 1 396 40 100 Supported TIDL layer type --- Reshape -- Reshape_296 Layer 158 -- layer name -- ReduceSum_297 Input dims size = 5 dims --- 1 6 66 40 100 Unsupported (imports) TIDL layer type for ONNX op type --- ReduceSum Layer 159 -- layer name -- Slice_279 Input dims size = 2 dims --- 6 67 Supported TIDL layer type --- Slice -- Slice_279 Layer 160 -- layer name -- custom_added_Reshape2 Input dims size = 2 dims --- 6 1 Supported TIDL layer type --- Reshape -- custom_added_Reshape2 Layer 161 -- layer name -- custom_added_Add4 Input dims size = 4 dims --- 1 1 1 6 Supported TIDL layer type --- Add -- custom_added_Add4 Layer 162 -- layer name -- Reshape_299 Input dims size = 4 dims --- 1 1 1 6 Supported TIDL layer type --- Reshape -- Reshape_299 Layer 163 -- layer name -- Add_300 Input dims size = 4 dims --- 1 6 40 100 Unsupported (TIDL check) TIDL layer type --- Add Layer 164 -- layer name -- Reshape_304 Input dims size = 4 dims --- 1 6 40 100 Supported TIDL layer type --- Reshape -- Reshape_304 Layer 165 -- layer name -- custom_added_Reshape0 Input dims size = 2 dims --- 6 1 Supported TIDL layer type --- Reshape -- custom_added_Reshape0 Layer 166 -- layer name -- Reshape_197 Input dims size = 1 dims --- 6 Supported TIDL layer type --- Reshape -- Reshape_197 Preliminary subgraphs created = 12 Final number of subgraphs created are : 10, - Offloaded Nodes - 156, Total Nodes - 167 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. Layers type not supported by TIDL --- layer type - TopK, Node name -TopK_193 ALLOWLISTING : Unsupported axis configuration for gather layer!, only line gather is supported -- file info - tidl_import_common_model_check.cpp , TIDL_checkGatherTensorProperties , 825 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. ALLOWLISTING : ADD/MUL/SUB/DIV layer : The variable inputs must of be same dimensions --tidl_import_common_model_check.cpp , TIDL_checkAddMulSubDivTensorProperties , 403 Layers type not supported by TIDL --- layer type - ReduceSum, Node name -ReduceSum_247 ALLOWLISTING : ADD/MUL/SUB/DIV layer : The variable inputs must of be same dimensions --tidl_import_common_model_check.cpp , TIDL_checkAddMulSubDivTensorProperties , 403 WARNING -- [TIDL_ConvolutionLayer] Layer parameter combination has undergone limited validation and may have some issues. Following are the parameters: Kernel 1x0 Stride 1x1 dilation 1x1 Pad 0x0 Bias 1 WARNING -- [TIDL_ConvolutionLayer] Layer parameter combination has undergone limited validation and may have some issues. Following are the parameters: Kernel 1x0 Stride 1x1 dilation 1x1 Pad 0x0 Bias 1 ALLOWLISTING : Unsupported axis configuration for gather layer!, only line gather is supported -- file info - tidl_import_common_model_check.cpp , TIDL_checkGatherTensorProperties , 825 ALLOWLISTING : ADD/MUL/SUB/DIV layer : The variable inputs must of be same dimensions --tidl_import_common_model_check.cpp , TIDL_checkAddMulSubDivTensorProperties , 403 Layers type not supported by TIDL --- layer type - ReduceSum, Node name -ReduceSum_297 ALLOWLISTING : ADD/MUL/SUB/DIV layer : The variable inputs must of be same dimensions --tidl_import_common_model_check.cpp , TIDL_checkAddMulSubDivTensorProperties , 403 Running runtimes graphviz - /home/root/tidl_tools/tidl_graphVisualiser_runtimes.out ../../../model-artifacts//condlanet_org//allowedNode.txt ../../../model-artifacts//condlanet_org//tempDir/graphvizInfo.txt ../../../model-artifacts//condlanet_org//tempDir/runtimes_visualization.svg *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_0_0 0, Conv, 3, 1, image, 600 1, Relu, 1, 1, 600, 203 2, MaxPool, 1, 1, 203, 204 3, Conv, 3, 1, 204, 603 4, Relu, 1, 1, 603, 207 5, Conv, 3, 1, 207, 606 6, Add, 2, 1, 606, 210 7, Relu, 1, 1, 210, 211 8, Conv, 3, 1, 211, 609 9, Relu, 1, 1, 609, 214 10, Conv, 3, 1, 214, 612 11, Add, 2, 1, 612, 217 12, Relu, 1, 1, 217, 218 13, Conv, 3, 1, 218, 621 14, Conv, 3, 1, 218, 615 15, Relu, 1, 1, 615, 221 16, Conv, 3, 1, 221, 618 17, Add, 2, 1, 618, 226 18, Relu, 1, 1, 226, 227 19, Conv, 3, 1, 227, 624 20, Relu, 1, 1, 624, 230 21, Conv, 3, 1, 230, 627 22, Add, 2, 1, 627, 233 23, Relu, 1, 1, 233, 234 24, Conv, 3, 1, 234, 636 25, Conv, 3, 1, 234, 630 26, Relu, 1, 1, 630, 237 27, Conv, 3, 1, 237, 633 28, Add, 2, 1, 633, 242 29, Relu, 1, 1, 242, 243 30, Conv, 3, 1, 243, 639 31, Relu, 1, 1, 639, 246 32, Conv, 3, 1, 246, 642 33, Add, 2, 1, 642, 249 34, Relu, 1, 1, 249, 250 35, Conv, 3, 1, 250, 378 36, Conv, 3, 1, 250, 651 37, Conv, 3, 1, 250, 645 38, Relu, 1, 1, 645, 253 39, Conv, 3, 1, 253, 648 40, Add, 2, 1, 648, 258 41, Relu, 1, 1, 258, 259 42, Conv, 3, 1, 259, 654 43, Relu, 1, 1, 654, 262 44, Conv, 3, 1, 262, 657 45, Add, 2, 1, 657, 265 46, Relu, 1, 1, 265, 266 47, Conv, 3, 1, 266, 660 48, Relu, 1, 1, 660, 269 49, Add, 2, 1, 269, 280 50, Conv, 3, 1, 280, 301 51, Reshape, 2, 1, 301, 308 52, Conv, 3, 1, 280, 290 53, Reshape, 2, 1, 290, 297 54, Conv, 3, 1, 280, 281 55, Reshape, 2, 1, 281, 288 56, Transpose, 1, 1, 288, 289 57, MatMul, 2, 1, 289, 298 58, Softmax, 1, 1, 298, 299 59, Transpose, 1, 1, 299, 300 60, MatMul, 2, 1, 308, 309 61, Reshape, 2, 1, 309, 316 62, Mul, 2, 1, 316, 317 63, Add, 2, 1, 317, 318 64, Conv, 3, 1, 318, 663 65, Relu, 1, 1, 663, 321 66, Conv, 3, 1, 321, 666 67, Relu, 1, 1, 666, 324 68, Add, 2, 1, 324, 335 69, Conv, 3, 1, 335, 356 70, Reshape, 2, 1, 356, 363 71, Conv, 3, 1, 335, 345 72, Reshape, 2, 1, 345, 352 73, Conv, 3, 1, 335, 336 74, Reshape, 2, 1, 336, 343 75, Transpose, 1, 1, 343, 344 76, MatMul, 2, 1, 344, 353 77, Softmax, 1, 1, 353, 354 78, Transpose, 1, 1, 354, 355 79, MatMul, 2, 1, 363, 364 80, Reshape, 2, 1, 364, 371 81, Mul, 2, 1, 371, 372 82, Add, 2, 1, 372, 373 83, Conv, 3, 1, 373, 669 84, Relu, 1, 1, 669, 376 85, Conv, 3, 1, 376, 379 86, Upsample, 2, 1, 379, 383 87, Add, 2, 1, 378, 384 88, Conv, 3, 1, 384, 391 89, Conv, 3, 1, 391, 395 90, Relu, 1, 1, 395, 396 91, Conv, 3, 1, 396, 397 92, Sigmoid, 1, 1, 397, 413 93, Clip, 1, 1, 413, 414 94, MaxPool, 1, 1, 414, 436 95, Mul, 2, 1, 414, mul_out_Sub_183 96, Add, 2, 1, mul_out_Sub_183, 437 97, Add, 2, 1, 437, 439 98, Div, 2, 1, 437, 440 99, Mul, 2, 1, 440, mul_out_Sub_188 100, Add, 2, 1, mul_out_Sub_188, 442 101, Mul, 2, 1, 414, 443 102, Squeeze, 1, 1, 443, 444 103, Reshape, 2, 1, 444, 446 Input tensor name - image Output tensor name - 234 Output tensor name - 384 Output tensor name - 391 Output tensor name - 446 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_1_1 0, Reshape, 2, 1, 448, seeds 1, Mul, 2, 1, seeds, 454 2, Slice, 1, 1, 454, 458 Input tensor name - 448 Output tensor name - seeds Output tensor name - 454 Output tensor name - 458 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_2_2 0, Conv, 3, 1, 391, 398 1, Relu, 1, 1, 398, 399 2, Conv, 3, 1, 399, 400 3, Reshape, 2, 1, 400, 423 4, Transpose, 1, 1, 423, 433 5, Reshape, 2, 1, 433, 435 6, Slice, 1, 1, 435, 460 7, Gather, 2, 1, 460, 464 8, Slice, 1, 1, 464, 488 9, Reshape, 2, 1, 488, reshape_out_Sub_231 10, Add, 2, 1, reshape_out_Sub_231, add_out_Sub_231 11, Reshape, 2, 1, add_out_Sub_231, 514 12, Conv, 3, 1, 234, 377 13, Upsample, 2, 1, 384, 388 14, Add, 2, 1, 377, 389 15, Conv, 3, 1, 389, 390 16, Conv, 3, 1, 390, 672 17, Relu, 1, 1, 672, 426 18, Conv, 3, 1, 426, 675 19, Relu, 1, 1, 675, 429 20, Conv, 3, 1, 429, 678 21, Relu, 1, 1, 678, 432 22, Concat, 2, 1, 471, 472 23, Concat, 6, 1, 472, 475 24, Reshape, 2, 1, 475, 483 25, Slice, 1, 1, 464, 487 26, Reshape, 2, 1, 487, 501 27, Reshape, 2, 1, 501, 508 Input tensor name - 391 Input tensor name - 462 Input tensor name - 384 Input tensor name - 234 Output tensor name - 435 Output tensor name - 508 Output tensor name - 475 Output tensor name - 483 Output tensor name - 514 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_3_3 0, Reshape, 2, 1, 509, 511 Input tensor name - 509 Output tensor name - 511 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_4_4 0, Reshape, 2, 1, 515, 523 1, Transpose, 1, 1, 523, 588 2, Reshape, 2, 1, 588, 595 Input tensor name - 515 Output tensor name - 523 Output tensor name - 595 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_5_5 0, Relu, 1, 1, 596, 597 Input tensor name - 596 Output tensor name - 597 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_6_6 0, Slice, 1, 1, 454, 459 1, Transpose, 1, 1, 598, 599 Input tensor name - 598 Input tensor name - 454 Output tensor name - 599 Output tensor name - 459 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_7_7 0, Slice, 1, 1, 435, 524 1, Gather, 2, 1, 524, 528 2, Slice, 1, 1, 528, 552 3, Reshape, 2, 1, 552, reshape_out_Sub_281 4, Add, 2, 1, reshape_out_Sub_281, add_out_Sub_281 5, Reshape, 2, 1, add_out_Sub_281, 578 6, Reshape, 2, 1, 475, 547 7, Slice, 1, 1, 528, 551 8, Reshape, 2, 1, 551, 565 9, Reshape, 2, 1, 565, 572 Input tensor name - 435 Input tensor name - 526 Input tensor name - 475 Output tensor name - 572 Output tensor name - 547 Warning: FFFFFF is not a known color. Output tensor name - 578 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_8_8 0, Reshape, 2, 1, 573, 575 Input tensor name - 573 Output tensor name - 575 *** In TIDL_createStateImportFunc *** Compute on node : TIDLExecutionProvider_TIDL_9_9 0, Reshape, 2, 1, 447, output_dict_list 1, Reshape, 2, 1, seeds, output_seeds 2, Reshape, 2, 1, 579, 587 Input tensor name - 579 Input tensor name - seeds Input tensor name - 447 Output tensor name - 587 Output tensor name - output_seeds Output tensor name - output_dict_list Graph Domain TO version : 9In TIDL_onnxRtImportInit subgraph_name=subgraph_0 Layer 0, subgraph id subgraph_0, name=234 Layer 1, subgraph id subgraph_0, name=384 Layer 2, subgraph id subgraph_0, name=391 Layer 3, subgraph id subgraph_0, name=446 Layer 4, subgraph id subgraph_0, name=image In TIDL_runtimesOptimizeNet: LayerIndex = 109, dataIndex = 105 WARNING: Batch Norm Layer custom_added_Mul0'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: Batch Norm Layer custom_added_Mul1's coeff cannot be found(or not match) in coef file, Random bias will be generated! Only for evaluation usage! Results are all random! ************** Frame index 1 : Running float import ************* In TIDL_runtimesPostProcessNet In TIDL_runtimesPostProcessNet 1 In TIDL_runtimesPostProcessNet 2 In TIDL_runtimesPostProcessNet 3 INFORMATION: [TIDL_ResizeLayer] Upsample_139 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. **************************************************** ** 1 WARNINGS 0 ERRORS ** **************************************************** In TIDL_runtimesPostProcessNet 4 ************ in TIDL_subgraphRtCreate ************ The soft limit is 2048 The hard limit is 2048 MEM: Init ... !!! MEM: Init ... Done !!! 0.0s: VX_ZONE_INIT:Enabled 0.4s: VX_ZONE_ERROR:Enabled 0.4s: VX_ZONE_WARNING:Enabled 0.1763s: VX_ZONE_INIT:[tivxInit:185] Initialization Done !!! TIDL_initDebugTraceParams Done -------------------------------------------- TIDL Memory size requiement (record wise): MemRecNum , Space , Attribute , Alignment , Size(KBytes), BasePtr 0 , DDR Cacheable , Persistent , 128, 19.25 , 0x00000000 1 , DDR Cacheable , Persistent , 128, 0.64 , 0x00000000 2 , L1D , Scratch , 128, 16.00 , 0x00000000 3 , L2 , Scratch , 128, 4.00 , 0x00000000 4 , L3/MSMC , Scratch , 128, 56.00 , 0x00000000 5 , DDR Cacheable , Persistent , 128, 586.88 , 0x00000000 6 , DDR Cacheable , Scratch , 128, 45090.69, 0x00000000 7 , L1D , Scratch , 0, 0.00 , 0x00000000 8 , DDR Cacheable , Scratch , 128, 24511.25, 0x00000000 9 , L1D , Scratch , 0, 0.00 , 0x00000000 10 , DDR Cacheable , Persistent , 128, 1457.12 , 0x00000000 11 , DDR Cacheable , Scratch , 128, 512.25 , 0x00000000 12 , L1D , Scratch , 0, 0.00 , 0x00000000 13 , L1D , Scratch , 0, 0.00 , 0x00000000 14 , DDR Cacheable , Persistent , 128, 0.00 , 0x00000000 -------------------------------------------- Total memory size requirement (space wise): Mem Space , Size(KBytes) L1D , 16.00 L2 , 4.00 L3/MSMC , 56.00 DDR Cacheable, 72178.08 -------------------------------------------- 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 -------------------------------------------- 0.35371s: VX_ZONE_ERROR:[tivxAlgiVisionCreate:363] Calling ialg.algAlloc failed with status = -1120 0.35395s: VX_ZONE_ERROR:[tivxKernelTIDLCreate:926] tivxAlgiVisionCreate returned NULL 0.35499s: VX_ZONE_ERROR:[ownContextSendCmd:822] Command ack message returned failure cmd_status: -1 0.35501s: VX_ZONE_ERROR:[ownContextSendCmd:862] tivxEventWait() failed. 0.35502s: VX_ZONE_ERROR:[ownNodeKernelInit:584] Target kernel, TIVX_CMD_NODE_CREATE failed for node TIDLNode 0.35503s: VX_ZONE_ERROR:[ownNodeKernelInit:585] Please be sure the target callbacks have been registered for this core 0.35504s: VX_ZONE_ERROR:[ownNodeKernelInit:586] If the target callbacks have been registered, please ensure no errors are occurring within the create callback of this kernel 0.35506s: VX_ZONE_ERROR:[ownGraphNodeKernelInit:583] kernel init for node 0, kernel com.ti.tidl:1:4 ... failed !!! 0.35509s: VX_ZONE_ERROR:[vxVerifyGraph:2059] Node kernel init failed 0.35510s: VX_ZONE_ERROR:[vxVerifyGraph:2113] Graph verify failed TIDL_RT_OVX: ERROR: Verifying TIDL graph ... Failed !!! TIDL_RT_OVX: ERROR: Verify OpenVX graph failed ************ TIDL_subgraphRtCreate done ************ ********** Frame Index 1 : Running float inference ********** Graph Domain TO version : 9In TIDL_onnxRtImportInit subgraph_name=subgraph_1 Layer 0, subgraph id subgraph_1, name=seeds Layer 1, subgraph id subgraph_1, name=454 Layer 2, subgraph id subgraph_1, name=458 Layer 3, subgraph id subgraph_1, name=448 In TIDL_runtimesOptimizeNet: LayerIndex = 7, dataIndex = 4 ************** Frame index 1 : Running float import ************* In TIDL_runtimesPostProcessNet In TIDL_runtimesPostProcessNet 1 In TIDL_runtimesPostProcessNet 2 In TIDL_runtimesPostProcessNet 3 **************************************************** ** ALL MODEL CHECK PASSED ** **************************************************** In TIDL_runtimesPostProcessNet 4 ************ in TIDL_subgraphRtCreate ************ TIDL_initDebugTraceParams Done -------------------------------------------- TIDL Memory size requiement (record wise): MemRecNum , Space , Attribute , Alignment , Size(KBytes), BasePtr 0 , DDR Cacheable , Persistent , 128, 19.25 , 0x00000000 1 , DDR Cacheable , Persistent , 128, 0.64 , 0x00000000 2 , DDR Cacheable , Scratch , 128, 16.00 , 0x00000000 3 , DDR Cacheable , Scratch , 128, 4.00 , 0x00000000 4 , DDR Cacheable , Scratch , 128, 56.00 , 0x00000000 5 , DDR Cacheable , Persistent , 128, 260.64 , 0x00000000 6 , DDR Cacheable , Scratch , 128, 1.67 , 0x00000000 7 , DDR Cacheable , Scratch , 128, 0.12 , 0x00000000 8 , DDR Cacheable , Scratch , 128, 4.88 , 0x00000000 9 , DDR Cacheable , Scratch , 128, 9.28 , 0x00000000 10 , DDR Cacheable , Persistent , 128, 302.89 , 0x00000000 11 , DDR Cacheable , Scratch , 128, 512.25 , 0x00000000 12 , DDR Cacheable , Persistent , 128, 0.12 , 0x00000000 13 , DDR Cacheable , Persistent , 128, 6233.32 , 0x00000000 14 , DDR Cacheable , Persistent , 128, 0.00 , 0x00000000 -------------------------------------------- Total memory size requirement (space wise): Mem Space , Size(KBytes) DDR Cacheable, 7421.07 -------------------------------------------- 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 -------------------------------------------- TIDL init call from ivision API -------------------------------------------- TIDL Memory size requiement (record wise): MemRecNum , Space , Attribute , Alignment , Size(KBytes), BasePtr 0 , DDR Cacheable , Persistent , 128, 19.25 , 0x0e6e9000 1 ,2024-05-20 15:17:45.709887924 [E:onnxruntime:, sequential_executor.cc:494 ExecuteKernel] Non-zero status code returned while running Gather node. Name:'Gather_207' Status Message: /onnxruntime/onnxruntime/core/framework/op_kernel.cc:83 virtual OrtValue* onnxruntime::OpKernelContext::OutputMLValue(int, const onnxruntime::TensorShape&) status.IsOK() was false. Shape mismatch attempting to re-use buffer. {1,1,1,1,1,6} != {1,1,1,6,67}. Validate usage of dim_value (values should be > 0) and dim_param (all values with the same string should equate to the same size) in shapes in the model. Available execution providers : ['TIDLExecutionProvider', 'TIDLCompilationProvider', 'CPUExecutionProvider'] Running 1 Models - ['condlanet_org'] Running_Model : condlanet_org Running shape inference on model /home/root/lucid/model_onnx/condlanettest.onnx ***************Running_Inference Section ********** This is Lucid Model for image /home/root/lucid/data_onnx/test_images/img0221.png Traceback (most recent call last): File "/home/root/examples/osrt_python/ort/onnxrt_ep_dock927_condlanet_fp32.py", line 431, in DDR Cacheable , Persistent , 128, 0.64 , 0x0e6e8000 2 , DDR Cacheable , Scratch , 128, 16.00 , 0x032ab000 3 , DDR Cacheable , Scratch , 128, 4.00 , 0x0e6e7000 4 , DDR Cacheable , Scratch , 128, 56.00 , 0xb4eb8000 5 , DDR Cacheable , Persistent , 128, 260.64 , 0x993be000 6 , DDR Cacheable , Scratch , 128, 1.67 , 0x0e6e6000 7 , DDR Cacheable , Scratch , 128, 0.12 , 0x0e6e5000 8 , DDR Cacheable , Scratch , 128, 4.88 , 0x032a9000 9 , DDR Cacheable , Scratch , 128, 9.28 , 0x02e0b000 10 , DDR Cacheable , Persistent , 128, 302.89 , 0x966b4000 11 , DDR Cacheable , Scratch , 128, 512.25 , 0x54c4d000 12 , DDR Cacheable , Persistent , 128, 0.12 , 0x03b34000 13 , DDR Cacheable , Persistent , 128, 6233.32 , 0x177b2000 14 , DDR Cacheable , Persistent , 128, 0.00 , 0x032a8000 -------------------------------------------- Total memory size requirement (space wise): Mem Space , Size(KBytes) DDR Cacheable, 7421.07 -------------------------------------------- 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 # - 1 Alg Init for Layer # - 2 Alg Init for Layer # - 3 Alg Init for Layer # - 4 Alg Init for Layer # - 6 Alg Init for Layer # - 7 PREEMPTION: Adding a new priority object for targetPriority = 2, handle = 0x7bcb0e6e9000 PREEMPTION: Now total number of priority objects = 1 at priorityId = 2, with new memRec of base = 0x7bcb03b34000 and size = 128 PREEMPTION: Requesting context memory addr for handle 0x7bcb0e6e9000, return Addr = 0x7bca34039db8 ************ TIDL_subgraphRtCreate done ************ Warning : Couldn't find corresponding ioBuf tensor for onnx tensor with matching name ********** Frame Index 1 : Running float inference ********** run_model(model, mIdx) File "/home/root/examples/osrt_python/ort/onnxrt_ep_dock927_condlanet_fp32.py", line 329, in run_model imgs, output, proc_time, sub_graph_time, height, width,org_imgs,img_name = infer_image(sess, input_images, config) File "/home/root/examples/osrt_python/ort/onnxrt_ep_dock927_condlanet_fp32.py", line 186, in infer_image output = list(sess.run(None, {input_name: input_data })) File "/usr/local/lib/python3.10/dist-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 200, in run return self._sess.run(output_names, input_feed, run_options) onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Non-zero status code returned while running Gather node. Name:'Gather_207' Status Message: /onnxruntime/onnxruntime/core/framework/op_kernel.cc:83 virtual OrtValue* onnxruntime::OpKernelContext::OutputMLValue(int, const onnxruntime::TensorShape&) status.IsOK() was false. Shape mismatch attempting to re-use buffer. {1,1,1,1,1,6} != {1,1,1,6,67}. Validate usage of dim_value (values should be > 0) and dim_param (all values with the same string should equate to the same size) in shapes in the model.