Import Error due to a circular import

[Demirrr]

# retrieve and install project in development mode
git clone https://github.com/uma-pi1/kge.git
cd kge
pip install -e .
# download and preprocess datasets
cd data
sh download_all.sh
cd ..
kge start examples/toy-complex-train.yaml --job.device cpu
cd ..
python -c "import kge" 
python -c "from kge.util.io import load_checkpoint"

The above code works as expectedly. However, unfortunately, python -c "from kge.model import KgeModel" does not work due to ImportError: cannot import name 'KgeModel' from partially initialized module 'kge.model' (most likely due to a circular import) (/home/demir/Desktop/KGE_models/kge/kge/model/init.py)

[rgemulla]

Hmm, python -c "from kge.model import KgeModel" works for me. @Demirrr Can you post the full stack trace? @AdrianKs Can you reproduce this error?

[samuelbroscheit]

I also cannot reproduce it. @Demirrr what is your python version?

[Demirrr]

Thank you for prompt answers. The ImportError appears to stem from the old python version (3.6.4). By following below commands, everything went smoothly.

conda create -n tempkg python=3.7
conda activate tempkg
git clone https://github.com/uma-pi1/kge.git
cd kge
pip install -e .
# download and preprocess datasets
cd data
sh download_all.sh
cd ..
kge start examples/toy-complex-train.yaml --job.device cpu
cd ..
python -c "import kge" 
python -c "from kge.util.io import load_checkpoint"
python -c "from kge.util.io import load_checkpoint"
python -c "from kge.model import KgeModel"

[Demirrr]

I am interested in reusing pre-trained models to analyse scores that are assigned by pre-trained models, for any given, (e_i,r_j,e_j) where e_i,_e_j \in Entities and r_j \in Relations. Consequently, I would like to know whether it is possible to provide string representations of entities and relations into models and generate scores. If not, I reckon the easiest solution would be parsing ids.del files locating in data folder.

While playing with the interface, I stumble upon following outputs

import torch
from kge.model import KgeModel
from kge.util.io import load_checkpoint
checkpoint = load_checkpoint('fb15k-237-rescal.pt')
model = KgeModel.create_from(checkpoint)
s = torch.Tensor([0, 2,]).long()             # subject indexes
p = torch.Tensor([0, 1,]).long()             # relation indexes
scores = model.score_sp(s, p)                # scores of all objects for (s,p,?)
o = torch.argmax(scores, dim=-1)             # index of highest-scoring objects

model.dataset.entity_ids(0) => '/m/027rn'
model.dataset.entity_strings(0) => ''Dominican Republic''

Thank you for the great work and fostering reproducible research.

[rufex2001]

'/m/027rn' looks like an ID from the Freebase dumps used to make FB15K and FB15K-237.

On Sat, 3 Oct 2020, 09:27 Caglar Demir, notifications@github.com wrote:

I am interested in reusing pre-trained models to analyse scores that are assigned by pre-trained models, for any given, (e_i,r_j,e_j) where e_i,_e_j \in Entities and r_j \in Relations. Consequently, I would like to know whether it is possible to provide string representations of entities and relations into models and generate scores. If not, I reckon the easiest solution would be parsing ids.del files locating in data folder.

While playing with the interface, I stumble upon following outputs

import torch from kge.model import KgeModel from kge.util.io import load_checkpoint checkpoint = load_checkpoint('fb15k-237-rescal.pt') model = KgeModel.create_from(checkpoint) s = torch.Tensor([0, 2,]).long() # subject indexes p = torch.Tensor([0, 1,]).long() # relation indexes scores = model.score_sp(s, p) # scores of all objects for (s,p,?) o = torch.argmax(scores, dim=-1) # index of highest-scoring objects

model.dataset.entity_ids(0) => '/m/027rn' model.dataset.entity_strings(0) => ''Dominican Republic''

If not mistaken, '/m/027rn' does not occur in fb15k-237 but wn18rr.

Thank you for the great work and fostering reproducible research.

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[rgemulla]

We currently do not support directly to go from strings to ids. See #130 for details.

[rgemulla]

Closing since setup.py does state that Python 3.7 is required.