Hello,
I am trying to use a modified version of the Yolo V5 network on the Jetson Xavier NX with Jetpack 5.0.2. I am trying to export the model to TensorRT with the following command:
python3 export.py --weights m6_1500_SL1_001.pt --imgsz 1280 768 --include engine --device 0
OUTPUT:
export: data=data/coco128.yaml, weights=['m6_1500_SL1_001.pt'], imgsz=[1280, 768], batch_size=1, device=0, half=False, inplace=False, train=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=14, verbose=False, workspace=4, nms=False, agnostic_nms=False, topk_per_class=100, topk_all=100, iou_thres=0.45, conf_thres=0.25, include=['engine']
YOLOv5 🚀 c981b40 torch 1.12.0a0+2c916ef.nv22.3 CUDA:0 (Xavier, 7513MiB)
Fusing layers...
Model Summary: 378 layers, 35260464 parameters, 0 gradients, 48.9 GFLOPs
PyTorch: starting from m6_1500_SL1_001.pt (283.6 MB)
ONNX: starting export with onnx 1.13.0...
/home/pratum/yolo_v5_keypoint/models/yolo.py:63: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
if self.onnx_dynamic or self.grid[i].shape[2:4] != x[i].shape[2:4]:
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
WARNING: The shape inference of prim::Constant type is missing, so it may result in wrong shape inference for the exported graph. Please consider adding it in symbolic function.
ONNX: export failure: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument other in method wrapper__equal)
TensorRT: starting export with TensorRT 8.4.1.5...
[01/18/2023-10:06:21] [TRT] [I] [MemUsageChange] Init CUDA: CPU +181, GPU +0, now: CPU 1363, GPU 4084 (MiB)
[01/18/2023-10:06:24] [TRT] [I] [MemUsageChange] Init builder kernel library: CPU +131, GPU +171, now: CPU 1513, GPU 4250 (MiB)
export.py:286: DeprecationWarning: Use set_memory_pool_limit instead.
config.max_workspace_size = workspace * 1 << 30
[01/18/2023-10:06:25] [TRT] [I] ----------------------------------------------------------------
[01/18/2023-10:06:25] [TRT] [I] Input filename: m6_1500_SL1_001.onnx
[01/18/2023-10:06:25] [TRT] [I] ONNX IR version: 0.0.7
[01/18/2023-10:06:25] [TRT] [I] Opset version: 13
[01/18/2023-10:06:25] [TRT] [I] Producer name: pytorch
[01/18/2023-10:06:25] [TRT] [I] Producer version: 1.12.0
[01/18/2023-10:06:25] [TRT] [I] Domain:
[01/18/2023-10:06:25] [TRT] [I] Model version: 0
[01/18/2023-10:06:25] [TRT] [I] Doc string:
[01/18/2023-10:06:25] [TRT] [I] ----------------------------------------------------------------
[01/18/2023-10:06:26] [TRT] [W] onnx2trt_utils.cpp:367: Your ONNX model has been generated with INT64 weights, while TensorRT does not natively support INT64. Attempting to cast down to INT32.
[01/18/2023-10:06:26] [TRT] [W] onnx2trt_utils.cpp:395: One or more weights outside the range of INT32 was clamped
[01/18/2023-10:06:26] [TRT] [W] onnx2trt_utils.cpp:395: One or more weights outside the range of INT32 was clamped
[01/18/2023-10:06:26] [TRT] [W] onnx2trt_utils.cpp:395: One or more weights outside the range of INT32 was clamped
[01/18/2023-10:06:26] [TRT] [W] onnx2trt_utils.cpp:395: One or more weights outside the range of INT32 was clamped
TensorRT: Network Description:
TensorRT: input "images" with shape (1, 3, 64, 64) and dtype DataType.FLOAT
TensorRT: output "output" with shape (1, 255, 8) and dtype DataType.FLOAT
TensorRT: output "onnx::Sigmoid_601" with shape (1, 3, 8, 8, 8) and dtype DataType.FLOAT
TensorRT: output "onnx::Sigmoid_685" with shape (1, 3, 4, 4, 8) and dtype DataType.FLOAT
TensorRT: output "onnx::Sigmoid_769" with shape (1, 3, 2, 2, 8) and dtype DataType.FLOAT
TensorRT: output "onnx::Sigmoid_853" with shape (1, 3, 1, 1, 8) and dtype DataType.FLOAT
TensorRT: building FP32 engine in m6_1500_SL1_001.engine
export.py:306: DeprecationWarning: Use build_serialized_network instead.
with builder.build_engine(network, config) as engine, open(f, 'wb') as t:
[01/18/2023-10:06:27] [TRT] [I] ---------- Layers Running on DLA ----------
[01/18/2023-10:06:27] [TRT] [I] ---------- Layers Running on GPU ----------
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_612
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Mul_625
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_636
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_696
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Mul_709
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_720
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_780
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Mul_793
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_804
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_864
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Mul_877
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONSTANT: onnx::Add_888
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_15
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_16), Mul_17)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_18
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_19), Mul_20)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_21 || Conv_38
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_22), Mul_23)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_39), Mul_40)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_24
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_25), Mul_26)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_27
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_28), Mul_29), Add_30)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_31
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_32), Mul_33)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_34
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_35), Mul_36), Add_37)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_238 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_42
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_43), Mul_44)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_45
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_46), Mul_47)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_48 || Conv_79
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_49), Mul_50)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_80), Mul_81)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_51
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_52), Mul_53)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_54
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_55), Mul_56), Add_57)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_58
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_59), Mul_60)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_61
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_62), Mul_63), Add_64)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_65
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_66), Mul_67)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_68
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_69), Mul_70), Add_71)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_72
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_73), Mul_74)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_75
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_76), Mul_77), Add_78)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_83
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_84), Mul_85)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_86
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_87), Mul_88)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_89 || Conv_134
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_90), Mul_91)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_135), Mul_136)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_92
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_93), Mul_94)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_95
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_96), Mul_97), Add_98)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_99
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_100), Mul_101)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_102
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_103), Mul_104), Add_105)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_106
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_107), Mul_108)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_109
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_110), Mul_111), Add_112)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_113
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_114), Mul_115)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_116
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_117), Mul_118), Add_119)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_120
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_121), Mul_122)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_123
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_124), Mul_125), Add_126)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_127
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_128), Mul_129)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_130
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_131), Mul_132), Add_133)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_138
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_139), Mul_140)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_141
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_142), Mul_143)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_144 || Conv_161
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_145), Mul_146)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_162), Mul_163)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_147
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_148), Mul_149)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_150
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_151), Mul_152), Add_153)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_154
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_155), Mul_156)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_157
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_158), Mul_159), Add_160)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_165
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_166), Mul_167)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_168
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_169), Mul_170)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_171 || Conv_188
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_172), Mul_173)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_189), Mul_190)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_174
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_175), Mul_176)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_177
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_178), Mul_179), Add_180)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_181
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_182), Mul_183)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_184
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(Sigmoid_185), Mul_186), Add_187)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_192
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_193), Mul_194)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_195
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_196), Mul_197)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POOLING: MaxPool_198
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POOLING: MaxPool_199
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POOLING: MaxPool_200
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::MaxPool_398 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::MaxPool_399 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::MaxPool_400 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_202
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_203), Mul_204)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_205
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_206), Mul_207)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] RESIZE: Resize_208
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_413 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_210 || Conv_225
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_211), Mul_212)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_226), Mul_227)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_213
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_214), Mul_215)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_216
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_217), Mul_218)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_219
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_220), Mul_221)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_222
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_223), Mul_224)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_229
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_230), Mul_231)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_232
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_233), Mul_234)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] RESIZE: Resize_235
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_444 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_237 || Conv_252
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_238), Mul_239)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_253), Mul_254)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_240
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_241), Mul_242)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_243
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_244), Mul_245)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_246
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_247), Mul_248)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_249
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_250), Mul_251)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_256
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_257), Mul_258)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_259
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_260), Mul_261)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] RESIZE: Resize_262
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_475 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_264 || Conv_279
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_265), Mul_266)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_280), Mul_281)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_267
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_268), Mul_269)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_270
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_271), Mul_272)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_273
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_274), Mul_275)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_276
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_277), Mul_278)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_283
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_284), Mul_285)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_286
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_364
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_287), Mul_288)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: input.264 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_290 || Conv_305
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_381 + Transpose_382
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_291), Mul_292)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_306), Mul_307)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_293
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(Sigmoid_383)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_388
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_401
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_412
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_425
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_430
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_294), Mul_295)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_296
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(onnx::Mul_621 + (Unnamed Layer* 409) [Shuffle] + Mul_403, PWN(onnx::Pow_623 + (Unnamed Layer* 412) [Shuffle], Pow_405)), Mul_407)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_297), Mul_298)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_608 + (Unnamed Layer* 397) [Shuffle] + Mul_390, PWN(onnx::Sub_610 + (Unnamed Layer* 400) [Shuffle], Sub_392)), Add_394), onnx::Mul_614 + (Unnamed Layer* 405) [Shuffle] + Mul_396)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_632 + (Unnamed Layer* 418) [Shuffle] + Mul_414, PWN(onnx::Sub_634 + (Unnamed Layer* 421) [Shuffle], Sub_416)), Add_418), onnx::Mul_638 + (Unnamed Layer* 426) [Shuffle] + Mul_420)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_299
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_615 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_626 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_639 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_435
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: Reshape_435_copy_output
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_300), Mul_301)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_302
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_303), Mul_304)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_309
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_310), Mul_311)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_312
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_436
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_313), Mul_314)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: input.232 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_316 || Conv_331
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_453 + Transpose_454
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_317), Mul_318)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_332), Mul_333)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_319
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(Sigmoid_455)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_460
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_473
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_484
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_497
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_502
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_320), Mul_321)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_322
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(onnx::Mul_705 + (Unnamed Layer* 465) [Shuffle] + Mul_475, PWN(onnx::Pow_707 + (Unnamed Layer* 468) [Shuffle], Pow_477)), Mul_479)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_323), Mul_324)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_692 + (Unnamed Layer* 453) [Shuffle] + Mul_462, PWN(onnx::Sub_694 + (Unnamed Layer* 456) [Shuffle], Sub_464)), Add_466), onnx::Mul_698 + (Unnamed Layer* 461) [Shuffle] + Mul_468)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_716 + (Unnamed Layer* 474) [Shuffle] + Mul_486, PWN(onnx::Sub_718 + (Unnamed Layer* 477) [Shuffle], Sub_488)), Add_490), onnx::Mul_722 + (Unnamed Layer* 482) [Shuffle] + Mul_492)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_325
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_699 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_710 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_723 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_507
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: Reshape_507_copy_output
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_326), Mul_327)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_328
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_329), Mul_330)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_335
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_336), Mul_337)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_338
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_508
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_339), Mul_340)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: input.200 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_342 || Conv_357
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_525 + Transpose_526
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_343), Mul_344)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_358), Mul_359)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_345
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(Sigmoid_527)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_532
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_545
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_556
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_569
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_574
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_346), Mul_347)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_348
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(onnx::Mul_789 + (Unnamed Layer* 521) [Shuffle] + Mul_547, PWN(onnx::Pow_791 + (Unnamed Layer* 524) [Shuffle], Pow_549)), Mul_551)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_349), Mul_350)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_776 + (Unnamed Layer* 509) [Shuffle] + Mul_534, PWN(onnx::Sub_778 + (Unnamed Layer* 512) [Shuffle], Sub_536)), Add_538), onnx::Mul_782 + (Unnamed Layer* 517) [Shuffle] + Mul_540)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_800 + (Unnamed Layer* 530) [Shuffle] + Mul_558, PWN(onnx::Sub_802 + (Unnamed Layer* 533) [Shuffle], Sub_560)), Add_562), onnx::Mul_806 + (Unnamed Layer* 538) [Shuffle] + Mul_564)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_351
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_783 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_794 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_807 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_579
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: Reshape_579_copy_output
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_352), Mul_353)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_354
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_355), Mul_356)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_361
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(Sigmoid_362), Mul_363)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] CONVOLUTION: Conv_580
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_597 + Transpose_598
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(Sigmoid_599)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_604
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_617
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_628
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_641
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SLICE: Slice_646
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(onnx::Mul_873 + (Unnamed Layer* 577) [Shuffle] + Mul_619, PWN(onnx::Pow_875 + (Unnamed Layer* 580) [Shuffle], Pow_621)), Mul_623)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_860 + (Unnamed Layer* 565) [Shuffle] + Mul_606, PWN(onnx::Sub_862 + (Unnamed Layer* 568) [Shuffle], Sub_608)), Add_610), onnx::Mul_866 + (Unnamed Layer* 573) [Shuffle] + Mul_612)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] POINTWISE: PWN(PWN(PWN(onnx::Mul_884 + (Unnamed Layer* 586) [Shuffle] + Mul_630, PWN(onnx::Sub_886 + (Unnamed Layer* 589) [Shuffle], Sub_632)), Add_634), onnx::Mul_890 + (Unnamed Layer* 594) [Shuffle] + Mul_636)
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_867 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_878 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: onnx::Concat_891 copy
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] SHUFFLE: Reshape_651
[01/18/2023-10:06:27] [TRT] [I] [GpuLayer] COPY: Reshape_651_copy_output
[01/18/2023-10:06:27] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +7, now: CPU 1665, GPU 4481 (MiB)
[01/18/2023-10:06:27] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +0, GPU +8, now: CPU 1665, GPU 4489 (MiB)
[01/18/2023-10:06:27] [TRT] [I] Local timing cache in use. Profiling results in this builder pass will not be stored.
[01/18/2023-10:08:42] [TRT] [W] Tactic Device request: 2599MB Available: 2242MB. Device memory is insufficient to use tactic.
[01/18/2023-10:08:42] [TRT] [W] Skipping tactic 3 due to insufficient memory on requested size of 2599 detected for tactic 0x0000000000000004.
[01/18/2023-10:08:42] [TRT] [W] Tactic Device request: 2599MB Available: 2242MB. Device memory is insufficient to use tactic.
[01/18/2023-10:08:42] [TRT] [W] Skipping tactic 8 due to insufficient memory on requested size of 2599 detected for tactic 0x000000000000003c.
[01/18/2023-10:12:17] [TRT] [I] Detected 1 inputs and 9 output network tensors.
[01/18/2023-10:12:18] [TRT] [I] Total Host Persistent Memory: 218496
[01/18/2023-10:12:18] [TRT] [I] Total Device Persistent Memory: 14336
[01/18/2023-10:12:18] [TRT] [I] Total Scratch Memory: 55296
[01/18/2023-10:12:18] [TRT] [I] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 29 MiB, GPU 1953 MiB
[01/18/2023-10:12:18] [TRT] [I] [BlockAssignment] Algorithm ShiftNTopDown took 193.957ms to assign 11 blocks to 260 nodes requiring 517124 bytes.
[01/18/2023-10:12:18] [TRT] [I] Total Activation Memory: 517124
[01/18/2023-10:12:18] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +1, GPU +0, now: CPU 1691, GPU 5323 (MiB)
[01/18/2023-10:12:18] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +13, GPU +256, now: CPU 13, GPU 256 (MiB)
[01/18/2023-10:12:18] [TRT] [W] The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
[01/18/2023-10:12:18] [TRT] [W] The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
TensorRT: export success, saved as m6_1500_SL1_001.engine (161.9 MB)
Export complete (387.20s)
Results saved to /home/pratum/yolo_v5_keypoint
Visualize with https://netron.app
It says that the process finished successfully. However, when I try to detect with the exported model it tells me that the input must be 64 x 64.
COMMAND:
python3 detect.py --img 1280 768 --source /home/pratum/diego_dataset_06_12_2022/images/test --weights m6_1500_SL1_001.engine --conf 0.1 --save-txt
OUTPUT:
detect: weights=['m6_1500_SL1_001.engine'], source=/home/pratum/diego_dataset_06_12_2022/images/test, imgsz=[1280, 768], conf_thres=0.1, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False
YOLOv5 🚀 c981b40 torch 1.12.0a0+2c916ef.nv22.3 CUDA:0 (Xavier, 7513MiB)
Loading m6_1500_SL1_001.engine for TensorRT inference...
[01/18/2023-10:16:20] [TRT] [I] [MemUsageChange] Init CUDA: CPU +186, GPU +0, now: CPU 277, GPU 2392 (MiB)
[01/18/2023-10:16:20] [TRT] [I] Loaded engine size: 154 MiB
[01/18/2023-10:16:22] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +346, GPU +330, now: CPU 813, GPU 2900 (MiB)
[01/18/2023-10:16:22] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in engine deserialization: CPU +0, GPU +151, now: CPU 0, GPU 151 (MiB)
[01/18/2023-10:16:24] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +0, GPU +0, now: CPU 1132, GPU 3199 (MiB)
[01/18/2023-10:16:24] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +0, GPU +1, now: CPU 0, GPU 152 (MiB)
Traceback (most recent call last):
File "detect.py", line 257, in <module>
main(opt)
File "detect.py", line 252, in main
run(**vars(opt))
File "/home/pratum/.local/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "detect.py", line 101, in run
model.warmup(imgsz=(1, 3, *imgsz), half=half) # warmup
File "/home/pratum/yolo_v5_keypoint/models/common.py", line 435, in warmup
self.forward(im) # warmup
File "/home/pratum/yolo_v5_keypoint/models/common.py", line 401, in forward
assert im.shape == self.bindings['images'].shape, (im.shape, self.bindings['images'].shape)
AssertionError: (torch.Size([1, 3, 1280, 768]), (1, 3, 64, 64))
Any ideas on how to solve this? Any way to cross compliling the model?
Thank you very much.
Package: nvidia-jetpack
Version: 5.0.2-b231
Priority: standard
Section: metapackages
Maintainer: NVIDIA Corporation
Installed-Size: 199 kB
Depends: nvidia-jetpack-runtime (= 5.0.2-b231), nvidia-jetpack-dev (= 5.0.2-b231)
Homepage: http://developer.nvidia.com/jetson
Download-Size: 29,3 kB
APT-Sources: https://repo.download.nvidia.com/jetson/common r35.1/main arm64 Packages
Description: NVIDIA Jetpack Meta Package