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ERROR] Network has dynamic or shape inputs, but no optimization

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I want to use the tao-converter file (on the jetson nx) to convert the unet model .etlt to int8 engine but get the error: [INFO] Detected input dimensions from the model: (-1, 1, 320, 320) [INFO] Model has dynamic shape. Setting up optimization profiles. [INFO] Using optimization profile min shape: (1, 1, 320, 320) for input: input_1:0 [INFO] Using optimization profile opt shape: (4, 1, 320, 320) for input: input_1:0 [INFO] Using optimization profile max shape: (16, 1, 320, 320) for input
ERROR] Network has dynamic or shape inputs, but no optimization
ICERM - Discrete Optimization: Mathematics, Algorithms, and Computation
ERROR] Network has dynamic or shape inputs, but no optimization
Network has dynamic or shape inputs, but no optimization profile has been defined. TRT 7.1 · Issue #518 · onnx/onnx-tensorrt · GitHub
ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
tensorrt 7.0 In function importInstanceNormalization: [8] Assertion failed: !isDynamic(tensor_ptr->getDimensions()) && InstanceNormalization does not support dynamic inputs! · Issue #374 · onnx/onnx-tensorrt · GitHub
ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
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ERROR] Network has dynamic or shape inputs, but no optimization
Accelerating Model inference with TensorRT: Tips and Best Practices for PyTorch Users, by hengtao tantai
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