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Automatically download GloVe embeddings #15

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Automatically download GloVe embeddings #15

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2ef9b24
dataHelper: automatically download GloVe embeddings
stefan-it Feb 13, 2018
b8d966b
main: prefer user-defined model via commandline option
stefan-it Feb 13, 2018
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5 changes: 3 additions & 2 deletions dataHelper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@
import pickle
from utils import log_time_delta
from tqdm import tqdm
from dataloader import Dataset
from dataloader import Dataset, Glove
import torch
from torch.autograd import Variable
from codecs import open
Expand Down Expand Up @@ -129,7 +129,7 @@ def load_text_vec(alphabet,filename="",embedding_size=-1):
def getEmbeddingFile(name):
#"glove" "w2v"

return os.path.join( ".vector_cache","glove.6B.300d.txt")
return os.path.join( ".vector_cache", "6b", "glove.6B.300d.txt")

def getDataSet(opt):

Expand Down Expand Up @@ -177,6 +177,7 @@ def loadData(opt):
# from functools import reduce
# word_set=set(reduce(lambda x,y :x+y,df["text"]))

Glove(corpus="6b", dim=300).process()
glove_file = getEmbeddingFile(opt.__dict__.get("embedding","glove_6b_300"))
loaded_vectors,embedding_size = load_text_vec(word_set,glove_file)
word_set = word_set & set(loaded_vectors.keys())
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2 changes: 1 addition & 1 deletion main.py
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Expand Up @@ -38,7 +38,7 @@
if "CUDA_VISIBLE_DEVICES" not in os.environ.keys():
os.environ["CUDA_VISIBLE_DEVICES"] =opt.gpu
#opt.model ='lstm'
opt.model ='capsule'
#opt.model ='capsule'

if from_torchtext:
train_iter, test_iter = utils.loadData(opt)
Expand Down