def get(self):
wv = VizSeqWebView(
args.data_root, self.get_task_arg(), models=self.get_models_arg(),
page_sz=self.get_page_sz_arg(), page_no=self.get_page_no_arg(),
query=self.get_query_arg(), sorting=self.get_sorting_arg()
)
page_data_json = wv.get_page_data_with_pagination()
self.write(page_data_json)
def view_scores(references: PathOrPathsOrDictOfStrList,
hypothesis: Optional[PathOrPathsOrDictOfStrList],
metrics: List[str],
tags: Optional[PathOrPathsOrDictOfStrList] = None):
_ref = VizSeqDataSources(references)
_hypo = VizSeqDataSources(hypothesis)
_tags, tag_set = None, []
if tags is not None:
_tags = VizSeqDataSources(tags, text_merged=True)
tag_set = sorted(_tags.unique())
_tags = _tags.text
models = _hypo.names
all_metrics = get_scorer_ids()
_metrics = []
for s in metrics:
if s in all_metrics:
_metrics.append(s)
else:
logger.warn(f'"{s}" is not a valid metric.')
scores = {
s: {
m: get_scorer(s)(corpus_level=True,
sent_level=False).score(_hypo.data[i].text,
_ref.text,
tags=_tags)
for i, m in enumerate(models)
}
for s in _metrics
}
corpus_scores = {
s: {m: scores[s][m].corpus_score
for m in models}
for s in _metrics
}
group_scores = {
s: {
t: {m: scores[s][m].group_scores[t]
for m in models}
for t in tag_set
}
for s in _metrics
}
metrics_and_names = [[s, get_scorer_name(s)] for s in _metrics]
html = env.get_template('ipynb_scores.html').render(
metrics_and_names=metrics_and_names,
models=models,
tag_set=tag_set,
corpus_scores=corpus_scores,
group_scores=group_scores,
corpus_and_group_score_latex=VizSeqWebView.latex_corpus_group_scores(
corpus_scores, group_scores),
corpus_and_group_score_csv=VizSeqWebView.csv_corpus_group_scores(
corpus_scores, group_scores),
)
return HTML(html)
def post(self):
task = self.get_task_arg()
cfg = VizSeqWebView(args.data_root, task).cfg
task_name = self.get_query_argument('n', task)
cfg.set_task_name(task_name)
description = self.get_query_argument('d', '')
cfg.set_description(description)
cfg_metrics = self.get_query_argument('m', '')
cfg_metrics = cfg_metrics.split(',') if len(cfg_metrics) > 0 else []
cfg.set_metrics(cfg_metrics)
tokenization = self.get_query_argument('tkn', '')
cfg.set_tokenization(tokenization)
self.finish(f'Task "{task}" Config updated.')
def get(self):
enum_tasks_and_names_and_enum_models = \
VizSeqWebView.get_enum_tasks_and_names_and_enum_models(args.data_root)
html = env.get_template('tasks.html').render(
enum_tasks_and_names_and_enum_models=enum_tasks_and_names_and_enum_models
)
self.write(html)
def get(self):
url_args = self.get_url_args()
models = self.get_models_arg()
task = self.get_task_arg()
page_sz, page_no = self.get_page_sz_arg(), self.get_page_no_arg()
query = self.get_query_arg()
sorting = self.get_sorting_arg()
s_metric = self.get_sorting_metric_arg()
wv = VizSeqWebView(
args.data_root, task, models=models, page_sz=page_sz,
page_no=page_no, query=query, sorting=sorting,
sorting_metric=s_metric
)
pd = wv.get_page_data()
html = env.get_template('view.html').render(
url_args=url_args, task=task, models=models, page_sz=page_sz,
page_no=page_no, sorting=sorting, query=query, metrics=wv.metrics,
src_has_text=wv.src_has_text, task_name=wv.task_name,
enum_src_names_and_types=wv.enum_src_names_and_types,
enum_ref_names=wv.enum_ref_names, trg_lang=pd.trg_lang,
span_highlight_js=SPAN_HIGHTLIGHT_JS, page_sizes=wv.page_sizes,
enum_metrics_and_names=wv.get_enum_metrics_and_names(),
tag_set=wv.get_tag_set(), tags=wv.get_tags(),
auto_tags=[[e] for e in pd.trg_lang],
all_metrics_and_names=wv.all_metrics_and_names, s_metric=s_metric,
pagination=wv.get_pagination(pd.total_examples, page_sz, page_no),
cur_idx=pd.cur_idx, viz_src=pd.viz_src, src=pd.cur_src,
ref=pd.viz_ref, hypo=pd.viz_hypo, n_samples=pd.n_samples,
cur_sent_scores=pd.viz_sent_scores, description=wv.description,
tokenization=wv.tokenization, all_tokenization=wv.all_tokenization,
total_examples=pd.total_examples, n_cur_samples=pd.n_cur_samples
)
self.write(html)
def get(self):
task = self.get_task_arg()
response = VizSeqWebView(args.data_root, task).get_n_grams()
self.write(response)
def get(self):
response = VizSeqWebView(
args.data_root, self.get_task_arg(), self.get_models_arg()
).get_scores()
self.write(response)