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57 × Eureka!OK I guess you ment the installed packages on the execution tab and i looked at the log.. so there i see the following:
Python 3.7.5 (default, Nov 7 2019, 10:50:52) [GCC 8.3.0]
argparse_utils == 1.3.0
trains == 0.14.3
Detailed import analysis
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IMPORT PACKAGE argparse_utils
simple_pipe2.py: 10
IMPORT PACKAGE trains
simple_pipe2.py: 9
if i stopped the running of the Original one before it ended, can it be the problem?
yes, I can see the model for his training in the web
so I didn't have much time to upgrade all the packs because I have some issues with that but it is on my todo list
*I see there is 0.16.1
Interesting... the code looks similar... i really don't know why it didn't showed the models in my trainings... I will try to add it manually for now
I read https://allegro.ai/docs/ but it is only for the open source of trains...
but I belive it should have work with 0.14.1 as well
@ https://app.slack.com/team/UT8T0V3NE ok so I see the packages that are listed are the ones that are imported on the python script that runs but it doesn't include the ones it needs from imports from other inner classes... I guess it is the way it works, so i need to specify all the packages that are not on the py script i run? (all the packages that the inner classes are using)
TF 1.15 (yes I know... i work on an old model of maskrcnn)
in the clone I see "Environment setup completed successfully" and nothing about timeout
@ https://app.slack.com/team/UT8T0V3NE any idea for what is the reason they are not listed there?
and it continues... but nothing about time out
(with the right branch, commit and all...)
ok, thank you 🙂 i will check it
i use Keras, "model.keras_model.save_weights(os.path.join(output_directory, 'model.h5'))" i want to see the results in trains... how do I do it? (I can see it saves the model in my dir but I can't see it on trains)
i can send requirements.txt if needed