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Currently, visualize a computation graph needs to export pkl file and load in jittorvis, it is not straightforward, we can do it in a better way:
import jittorvis import jittor as jt from jittor.models import resnet18 model = resnet18() img = jt.rand((1,3,100,100)) jittorvis.visualize_model(model, img, ip=xxxx, port=xxxx, ...)
The text was updated successfully, but these errors were encountered:
in the updated version, we can use jittorvis in the following way:
import jittor as jt from jittor.models import resnet18 from jittorvis import server model = resnet18() with jt.flag_scope(trace_py_var=2, trace_var_data=1): output = model(input) output.sync() trace_data = jt.dump_trace_data() jt.clear_trace_data() server.run(trace_data, port=5005, host='0.0.0.0')
In this way you don't need to export pkl file and reload in jittorvis. Also, we will introduce the function "visualize_model" in jittorvis soon.
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Solved
Merge pull request #2 from ThuWangzw/reconstruct
daa4078
feat: add a simple network layout
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Currently, visualize a computation graph needs to export pkl file and load in jittorvis, it is not straightforward, we can do it in a better way:
The text was updated successfully, but these errors were encountered: