def __iter__(self):
count = 0
for document in stream_reuters_documents():
sample = document["content"], "acq" in document["topics"] # todo: maybe try "usa" or "earn"
if count > num_train_samples:
if self.first_iteration:
test_samples.append(sample)
else:
yield sample
count += 1
self.first_iteration = False
def __iter__(self):
count = 0
for document in stream_reuters_documents():
sample = document["content"], "acq" in document[
"topics"] # todo: maybe try "usa" or "earn"
if count > num_train_samples:
if self.first_iteration:
test_samples.append(sample)
else:
yield sample
count += 1
self.first_iteration = False
def get_documents(self):
for document in stream_reuters_documents():
yield simple_preprocess(document["content"])
def get_topic_counts():
labels = defaultdict(int)
for document in stream_reuters_documents():
for topic in document["topics"]:
labels[topic] += 1
return labels
def get_documents(self):
for document in stream_reuters_documents():
yield simple_preprocess(document["content"])
def get_topic_counts():
labels = defaultdict(int)
for document in stream_reuters_documents():
for topic in document["topics"]:
labels[topic] += 1
return labels
