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View Code? Open in Web Editor NEWInference of quantization aware trained networks using TensorRT
License: Apache License 2.0
Inference of quantization aware trained networks using TensorRT
License: Apache License 2.0
When I use postprocess_onnx to process the onnx model which is the output of step 4, encounter a erro:
Traceback (most recent call last):
File "postprocess_onnx_ori.py", line 54, in
graph = process_transpose_nodes(graph)
File "postprocess_onnx_ori.py", line 33, in process_transpose_nodes
conv_weights_tensor = node.i(1).i().i().inputs[0]
File "/root/.local/lib/python3.8/site-packages/onnx_graphsurgeon/ir/node.py", line 62, in i
return self.inputs[tensor_idx].inputs[producer_idx]
Then I view the onnx model by Netron, I find that every conv node's input[1] is just a tensor, not a node, so when run node.i(1) failed. Is this a bug or miss some instructions between step 4 and step5?
Hi,
This repo is only for tensorflow, so is there some guidance for the QAT in torch to trt?
Thx,
Lei
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