def binary(lang):
g.lang = lang
s = set()
s.add(lang)
other_lang = list(set(language_dicts.keys()) -
s)[0] # works only for two languages
g.strings = language_dicts[lang]
if request.method == "GET":
return render_template("binary.html",
other_lang=other_lang,
languages=languages,
model1=list(our_models.keys())[-2],
model2=list(our_models.keys())[-1],
models=our_models,
url=url)
else:
if request.form.getlist("word"): # First time click
word = request.form.getlist("word")[0]
word = process_query(word)
models = request.form.getlist("models")
if len(models) != 2:
error_value = 'Select 2 years!'
return render_template('binary.html',
error=error_value,
models=our_models,
url=url,
other_lang=other_lang,
model1=list(our_models.keys())[-3],
model2=list(our_models.keys())[-2],
languages=languages)
model1, model2 = models
if model1 == model2:
error_value = "Identical models"
return render_template('binary.html',
error=error_value,
model1=model1,
model2=model2,
other_lang=other_lang,
languages=languages,
models=our_models,
url=url)
if word == "Incorrect tag!":
error_value = "Incorrect tag!"
return render_template('binary.html',
error=error_value,
model1=model1,
model2=model2,
other_lang=other_lang,
languages=languages,
models=our_models,
url=url)
message = {
'operation': '7',
'word': word,
'model1': model1,
"model2": model2,
'with_examples': True
}
result = json.loads(serverquery(message).decode('utf-8'))
if word + " is unknown to the model" in result:
error_value = "Unknown word"
return render_template("binary.html",
error=error_value,
word=word,
models=our_models,
tags=tags,
url=url,
usermodels=[defaultmodel],
tags2show=exposed_tags)
else: # User presses the 'Confirm' button to wait longer for the results
word, model1, model2 = request.form.get("confirm").split()
message = {
'operation': '7',
'word': word,
'model1': model1,
"model2": model2,
'with_examples': "slow"
}
result = json.loads(serverquery(message).decode('utf-8'))
label = result["label"]
proba = float(result["proba"])
examples = result["examples"]
frequencies = result["frequencies"]
if type(examples) is dict:
examples_type = 1
else:
examples_type = 0
if label == "1":
ok_models = [model1, model2]
m = hashlib.md5()
hashword = ":".join(
[",".join([str(i) for i in j]) for j in ok_models] + [word])
hashword = hashword.encode('ascii', 'backslashreplace')
m.update(hashword)
if not os.path.isdir("data/images/heatmaps"):
os.mkdir("data/images/heatmaps")
fname = m.hexdigest()
trajectory_message = {
'operation': '6',
'query': word,
'pos': "ALL",
'model': ok_models
}
trajectory_result = json.loads(
serverquery(trajectory_message).decode('utf-8'))
if not os.path.exists(root + 'data/images/tsne_shift'):
os.makedirs(root + 'data/images/tsne_shift')
if trajectory_result['word_list']:
tsne_semantic_shifts(trajectory_result, fname)
return render_template("binary.html",
model1=model1,
model2=model2,
frequencies=frequencies,
other_lang=other_lang,
languages=languages,
models=our_models,
url=url,
label=label,
proba="{:.2f}".format(proba),
word=word,
examples=examples,
examples_type=examples_type,
fname=fname)
return render_template("binary.html",
model1=model1,
model2=model2,
frequencies=frequencies,
other_lang=other_lang,
languages=languages,
models=our_models,
url=url,
label=label,
proba="{:.2f}".format(proba),
word=word,
examples=examples,
examples_type=examples_type)
def associates_page(lang):
global our_models
g.lang = lang
s = set()
s.add(lang)
other_lang = list(set(language_dicts.keys()) -
s)[0] # works only for two languages
g.strings = language_dicts[lang]
if request.method == 'POST':
list_data = request.form['list_query']
# Nearest associates queries
if list_data != 'dummy' and list_data.replace('_', '').replace('-', '').\
replace('::', '').replace(' ', '').isalnum():
list_data = list_data.strip()
query = process_query(list_data)
model_value = request.form.getlist('model')
if len(model_value) < 1:
model_value = [defaultmodel]
if query == "Incorrect tag!":
error_value = "Incorrect tag!"
return render_template('associates.html',
error=error_value,
word=list_data,
models=our_models,
tags2show=exposed_tags,
other_lang=other_lang,
languages=languages,
url=url,
usermodels=model_value)
userpos = []
if tags:
pos_value = request.form.getlist('pos')
if len(pos_value) < 1:
pos = query.split('_')[-1]
else:
pos = pos_value[0]
if pos != 'ALL':
userpos.append(pos)
if pos == 'Q':
pos = query.split('_')[-1]
else:
pos = 'ALL'
images = {query.split('_')[0]: None}
models_row = {}
inferred = set()
frequencies = {}
labels, probas = list(), list()
results = map(
get_model_changes,
[(model1, model2, query)
for (model1, model2) in zip(model_value, model_value[1:])])
results = sorted(results)
for model1, model2, result in results:
if query + " is unknown to the model" in result:
label = "0"
proba = 0.0
else:
label = result["label"]
proba = float(result["proba"])
labels.append(label)
probas.append(proba)
for model in model_value:
if not model.strip() in our_models:
return render_template('associates.html',
other_lang=other_lang,
url=url,
languages=languages,
usermodels=model_value)
results = map(get_model_neighbors,
[(x, query, pos) for x in model_value])
results = sorted(results)
ok_models = list()
for model, result, model_query in results:
frequencies[model] = result['frequencies']
if model_query != query:
frequencies[model][query] = frequencies[model][model_query]
if model_query + " is unknown to the model" in result:
models_row[model] = "Unknown!"
continue
elif 'No results' in result:
models_row[model] = 'No results!'
continue
else:
for word in result['neighbors']:
images[word[0].split('_')[0]] = None
models_row[model] = result['neighbors']
ok_models.append(model)
if dbpedia:
try:
images = get_images(images)
except TimeoutError:
pass
if 'inferred' in result:
inferred.add(model)
m = hashlib.md5()
hashword = ":".join(
[",".join([str(i) for i in j])
for j in model_value] + [query, pos])
hashword = hashword.encode('ascii', 'backslashreplace')
m.update(hashword)
fname = m.hexdigest()
if len(ok_models) == 0:
error_value = "Unknown word"
return render_template("associates.html",
error=error_value,
models=our_models,
tags=tags,
url=url,
usermodels=model_value,
tags2show=exposed_tags)
trajectory_message = {
'operation': '6',
'query': query,
'pos': pos,
'model': ok_models
}
trajectory_result = json.loads(
serverquery(trajectory_message).decode('utf-8'))
if query + " is unknown to the model" in trajectory_result:
error_value = "Unknown word"
return render_template("associates.html",
error=error_value,
models=our_models,
tags=tags,
url=url,
usermodels=[defaultmodel],
tags2show=exposed_tags)
if not os.path.exists(root + 'data/images/tsne_shift'):
os.makedirs(root + 'data/images/tsne_shift')
if trajectory_result['word_list']:
tsne_semantic_shifts(trajectory_result, fname)
return render_template('associates.html',
list_value=models_row,
word=query,
pos=pos,
number=len(model_value),
wordimages=images,
models=our_models,
tags=tags,
other_lang=other_lang,
languages=languages,
tags2show=exposed_tags,
url=url,
usermodels=model_value,
userpos=userpos,
inferred=inferred,
frequencies=frequencies,
visible_neighbors=10,
fname=fname,
labels=labels,
probas=probas)
else:
error_value = "Incorrect query!"
return render_template("associates.html",
error=error_value,
models=our_models,
tags=tags,
url=url,
usermodels=[defaultmodel],
tags2show=exposed_tags)
return render_template('associates.html',
models=our_models,
tags=tags,
other_lang=other_lang,
languages=languages,
url=url,
usermodels=['2013', '2014', '2015'],
tags2show=exposed_tags)