def _serve_web(template,
notebook_mode=True,
ip='127.0.0.1',
port=5000,
n_retries=100,
width='100%',
height=500,
**kwargs):
if notebook_mode and not is_notebook():
logger.warning(
'`notebook_mode=True` but the code is not running in Jupyter Notebook, will disable `notebook_mode`'
)
notebook_mode = False
port = find_open_port(ip, port, n_retries)
if notebook_mode:
from IPython.display import IFrame, display, HTML
html = escape(template)
iframe = (
'<div style="width:{width};height:{height}px">'
'<div style="position:relative;width:100%;height:0;padding-bottom:{ratio};">' # noqa
'<iframe srcdoc="{html}" style="position:absolute;width:100%;height:{height}px;left:0;top:0;' # noqa
'border:none !important;" '
'allowfullscreen webkitallowfullscreen mozallowfullscreen>'
'</iframe>'
'</div></div>').format(html=html,
width=width,
height=height,
ratio=1)
display(HTML(iframe))
else:
logger.info(f'Serving to http://{ip}:{port}/')
serve(template, ip=ip, port=port, **kwargs)
def _render_binary(data, notebook_mode = False):
index_negative = data['barplot']['x'].index('negative')
index_positive = data['barplot']['x'].index('positive')
index_neutral = data['barplot']['x'].index('neutral')
sentiment_mark = []
for k, v in data['word'].items():
sentiment_mark.append(
_sentiment_mark(
k,
v[index_negative],
v[index_positive],
v[index_neutral],
data['alphas'][k],
data['barplot']['x'][np.argmax(v)],
)
)
sentiment_mark = ' '.join(sentiment_mark)
this_dir = os.path.dirname(__file__)
if notebook_mode:
js_location, css_location = _upload_jupyter()
else:
js_location = 'static/echarts.min.js'
css_location = 'static/admin-materialize.min.css'
with open(os.path.join(this_dir, 'web', 'index.html')) as _file:
template = string.Template(_file.read())
template = template.substitute(
label = escape(data['class_name']),
p = sentiment_mark,
barplot_positive = escape(
json.dumps(int(data['barplot']['y'][index_positive]))
),
barplot_neutral = escape(
json.dumps(int(data['barplot']['y'][index_neutral]))
),
barplot_negative = escape(
json.dumps(int(data['barplot']['y'][index_negative]))
),
histogram_x = escape(json.dumps(data['histogram']['x'].tolist())),
histogram_y = escape(json.dumps(data['histogram']['y'].tolist())),
attention_x = escape(json.dumps(data['attention']['x'].tolist())),
attention_y = escape(json.dumps(data['attention']['y'].tolist())),
css_location = css_location,
js_location = js_location,
)
if notebook_mode:
from IPython.display import display, HTML
display(HTML(template))
else:
serve(template)
def _render_emotion(data, notebook_mode=False):
index_anger = data['barplot']['x'].index('anger')
index_fear = data['barplot']['x'].index('fear')
index_joy = data['barplot']['x'].index('joy')
index_love = data['barplot']['x'].index('love')
index_sadness = data['barplot']['x'].index('sadness')
index_surprise = data['barplot']['x'].index('surprise')
emotion_mark = []
for k, v in data['word'].items():
where = np.where(np.array(v) >= 0.3)[0].shape[0]
if where:
where = data['barplot']['x'][np.argmax(v)]
else:
where = 'neutral'
emotion_mark.append(
_emotion_mark(
k,
v[index_anger],
v[index_fear],
v[index_joy],
v[index_love],
v[index_sadness],
v[index_surprise],
data['alphas'][k],
where,
))
emotion_mark = ' '.join(emotion_mark)
this_dir = os.path.dirname(__file__)
if notebook_mode:
js_location, css_location = _upload_jupyter()
else:
js_location = 'static/echarts.min.js'
css_location = 'static/admin-materialize.min.css'
with open(os.path.join(this_dir, 'web', 'index_emotion.html')) as _file:
template = string.Template(_file.read())
template = template.substitute(
label=escape(data['class_name']),
p=emotion_mark,
barplot_anger=escape(json.dumps(int(
data['barplot']['y'][index_anger]))),
barplot_fear=escape(json.dumps(int(data['barplot']['y'][index_fear]))),
barplot_joy=escape(json.dumps(int(data['barplot']['y'][index_joy]))),
barplot_love=escape(json.dumps(int(data['barplot']['y'][index_love]))),
barplot_sadness=escape(
json.dumps(int(data['barplot']['y'][index_sadness]))),
barplot_surprise=escape(
json.dumps(int(data['barplot']['y'][index_surprise]))),
histogram_x=escape(json.dumps(data['histogram']['x'].tolist())),
histogram_y=escape(json.dumps(data['histogram']['y'].tolist())),
attention_x=escape(json.dumps(data['attention']['x'].tolist())),
attention_y=escape(json.dumps(data['attention']['y'].tolist())),
css_location=css_location,
js_location=js_location,
)
if notebook_mode:
from IPython.display import display, HTML
display(HTML(template))
else:
serve(template)
def _render_toxic(data, notebook_mode=False):
index_toxic = data['barplot']['x'].index('toxic')
index_severe_toxic = data['barplot']['x'].index('severe_toxic')
index_obscene = data['barplot']['x'].index('obscene')
index_threat = data['barplot']['x'].index('threat')
index_insult = data['barplot']['x'].index('insult')
index_identity_hate = data['barplot']['x'].index('identity_hate')
toxic_mark = []
for k, v in data['word'].items():
where = np.where(np.array(v) >= 0.5)[0].shape[0]
if where:
where = data['barplot']['x'][np.argmax(v)]
else:
where = 'neutral'
toxic_mark.append(
_toxic_mark(
k,
v[index_toxic],
v[index_severe_toxic],
v[index_obscene],
v[index_threat],
v[index_insult],
v[index_identity_hate],
data['alphas'][k],
where,
))
toxic_mark = ' '.join(toxic_mark)
this_dir = os.path.dirname(__file__)
if notebook_mode:
js_location, css_location = _upload_jupyter()
else:
js_location = 'static/echarts.min.js'
css_location = 'static/admin-materialize.min.css'
with open(os.path.join(this_dir, 'web', 'index_toxic.html')) as _file:
template = string.Template(_file.read())
template = template.substitute(
label=escape(data['class_name']),
p=toxic_mark,
barplot_toxic=escape(json.dumps(int(
data['barplot']['y'][index_toxic]))),
barplot_severe_toxic=escape(
json.dumps(int(data['barplot']['y'][index_severe_toxic]))),
barplot_obscene=escape(
json.dumps(int(data['barplot']['y'][index_obscene]))),
barplot_threat=escape(
json.dumps(int(data['barplot']['y'][index_threat]))),
barplot_insult=escape(
json.dumps(int(data['barplot']['y'][index_insult]))),
barplot_identity_hate=escape(
json.dumps(int(data['barplot']['y'][index_identity_hate]))),
histogram_x=escape(json.dumps(data['histogram']['x'].tolist())),
histogram_y=escape(json.dumps(data['histogram']['y'].tolist())),
attention_x=escape(json.dumps(data['attention']['x'].tolist())),
attention_y=escape(json.dumps(data['attention']['y'].tolist())),
css_location=css_location,
js_location=js_location,
)
if notebook_mode:
from IPython.display import display, HTML
display(HTML(template))
else:
serve(template)