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train_fsns.py problem #71

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MS-MA opened this issue Apr 14, 2019 · 5 comments
Open

train_fsns.py problem #71

MS-MA opened this issue Apr 14, 2019 · 5 comments

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@MS-MA
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MS-MA commented Apr 14, 2019

In train_fsns.py, to trainer.run(), where does the program jump?

@Bartzi
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Bartzi commented Apr 15, 2019

it jumps into the train routine implemented by chainer

@MS-MA
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MS-MA commented Apr 15, 2019

Can you tell me the exact location of the program jump? thank you very much @Bartzi

@Bartzi
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Bartzi commented Apr 15, 2019

please have a look at the chainer documentation, and I think you will be able to find what you are looking for 😉

@MS-MA
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MS-MA commented Apr 20, 2019

hello Bartzi,I have a new problem about train_fsns.py
if i create a learning curriculum,like the follows:

[
{
"train":"/home/data/fsns/image/train/train_swap_max2words.csv",
"validation":"/home/data/fsns/image/validation/validation_swap_max2words.csv"
},
{
"train":"/home/data/fsns/image/train/train_swap_3words.csv",
"validation":"/home/data/fsns/image/validation/validation_swap_3words.csv"
},
{ "train":"/home/data/fsns/image/train/train_swap_4words.csv",
"validation":"/home/data/fsns/image/validation/validation_swap_4words.csv"
},
{ "train":"/home/data/fsns/image/train/train_swap_5words.csv",
"validation":"/home/data/fsns/image/validation/validation_swap_5words.csv"
},
{ "train":"/home/data/fsns/image/train/train_swap_6words.csv",
"validation":"/home/data/fsns/image/validation/validation_swap_6words.csv"
}

]

how should i adjust the attributes like the below in train_fsns.py ?

attributes_to_adjust = [
('num_timesteps', ['predictor', 'localization_net']),
('num_timesteps', ['predictor', 'recognition_net']),
('num_timesteps', ['lossfun', 'self']),
('num_labels', ['predictor', 'recognition_net']),
]

I am confused,could you give me a case? very thanks

@Bartzi
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Bartzi commented Apr 23, 2019

If you are not changing anything else than a train curriculum there is no need for chaning the code at this point. These lines of code are only necessary, because there are sveral pieces of code that need to be adjusted if the dataset is changed, this is just a list of locations where changes need to be made when updating the curriculum, so as long as you did not make any changes to code that deals with attributes that might be changed by a new dataset, you don't need to changes these lines of code.

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