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View Code? Open in Web Editor NEWArtifacts for SOSP'19 paper Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions
Artifacts for SOSP'19 paper Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions
Hi,
Thanks for the great work. I meet a problem during using the code.
To export the optimized nasrnn model, I add the three lines at the end of examples/nasrnn.py
:
onnx_model = xf.export_onnx(new_graph)
onnx.checker.check_model(onnx_model)
onnx.save(onnx_model, "nasrnn_opt_xflow.onnx")
Then run the command $ python examples/nasrnn.py
.
The program gives the following error message on function xf.export_onnx(new_graph)
:
......
cost[Concat]: numInputs(2) cost(0.0001) total_cost(1.3592)
cost[Matmul]: input(1:1024 1024:1) weight(1024:512 512:1) cost(0.0116) total_cost(1.3708)
Cost metrics: exe_time(1.3708) flops(0.0196) memory_access(0.4395) kernel_launches(190)
op.guid=53520 mytype=Concat inedges=2
Traceback (most recent call last):
File "examples/nasrnn.py", line 36, in <module>
onnx_model = xf.export_onnx(new_graph)
File "/home/yaoyao/anaconda3/lib/python3.7/site-packages/xflow-0.0.0-py3.7-linux-x86_64.egg/xflow/__init__.py", line 277, in export_onnx
inputs.append(_input_tensor_name(graph, e, op))
File "/home/yaoyao/anaconda3/lib/python3.7/site-packages/xflow-0.0.0-py3.7-linux-x86_64.egg/xflow/__init__.py", line 240, in _input_tensor_name
return "{}{}_{}".format(mytype, op['guid'], input_weight_names[mytype][inedge['dstIdx']])
KeyError: 'Concat'
Thanks a lot if you can help!
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