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Where is infersent.pickle? #72

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antoinecomp opened this issue Aug 6, 2018 · 4 comments
Closed

Where is infersent.pickle? #72

antoinecomp opened this issue Aug 6, 2018 · 4 comments

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@antoinecomp
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I'm trying to get your sentence embeddings method that provides semantic sentence representations in
InterSent/encoder folder but I don't see the infersent.pickle you are referencing.

A friend of mine rather used:

infersent = torch.load('InferSent/encoder/infersent.allnli.pickle', map_location=lambda storage, loc: storage)

But here nothing appears to be named infersent.allnli.pickle neither. Maybe she was referencing an old version ?

@aconneau
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aconneau commented Aug 7, 2018

Hi,

we made recent changes to InferSent, and so what you're referring to is indeed the old version. Please pull the new version and follow the README for the new versions of InferSent (which should be simpler to load).

Thanks,
Alexis

@antoinecomp
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True !

@antoinecomp
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antoinecomp commented Aug 7, 2018

@aconneau Hi Alexis ! I think this is related: has set_glove_path() function been changed for:

infersent.set_glove_path("InferSent/dataset/GloVe/glove.840B.300d.txt")

Because I have the following error when running it:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-18-1a6368709557> in <module>()
      1 infersent = torch.load('InferSent/encoder/infersent1.pkl', map_location=lambda storage, loc: storage)
----> 2 infersent.set_glove_path("InferSent/dataset/GloVe/glove.840B.300d.txt")
      3 

AttributeError: 'collections.OrderedDict' object has no attribute 'set_glove_path'

@Surendra03061975
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I am also facing the same issue as mentioned below .
Environment details :
Anaconda
Python 3.6
Windows 10

Please help me with answers which will work on the above environment

I'm trying to get your sentence embeddings method that provides semantic sentence representations in
InterSent/encoder folder but I don't see the infersent.pickle you are referencing.
A friend of mine rather used:
infersent = torch.load('InferSent/encoder/infersent.allnli.pickle', map_location=lambda storage, loc: storage)

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3 participants