from hare import Hare, Conversation
from hare.brain import BiGruBrain
brain: BiGruBrain = BiGruBrain()
brain.embedding_location = '/vol/bigdata/word_embeddings/glove/glove.6B.50d.txt'
brain.verbose = True
hare = Hare()
hare.brain = brain
convo = Conversation()
convo.add_utterance(speaker='a', content='hate you')
convo.add_utterance(speaker='b', content='i love you')
convo.label_speaker('a', 1)
hare.add_conversation(convo)
hare.train()
hare.save('/vol/tensusers2/wstoop/HaRe/hare/pretrained/simple')
hare.update_status_history_for_conversation()
hare.visualize_history_for_conversation()
from hare import Hare, Conversation
from hare.tensorflowbrain import BiGruBrain
mockhare = Hare()
mockhare.brain = BiGruBrain()
for i in range(10000):
convo = Conversation()
convo.add_utterance(speaker='a', content='c c c c c')
convo.add_utterance(speaker='b', content='c c c c c')
convo.add_utterance(speaker='b', content='c c c c b')
convo.add_utterance(speaker='a', content='c c c c a')
convo.label_speaker('b', 1)
mockhare.add_conversation(convo)
mockhare.train()
mockhare.visualize_history_for_conversation()
for n, line in enumerate(open(conv_hist_file)):
status_per_conversation.append(loads(line)[:CONVERSATION_LENGTH])
if n % 100 == 0:
print(conv_hist_file, n)
for threshold in THRESHOLDS:
h = Hare(name=threshold)
h.status_per_conversation = status_per_conversation
h.cut_off_value = threshold
hares.append(h)
#Load the conversations
conversations = []
current_conversation = Conversation()
for line in open(CONVERSATIONS_FILE):
line = line.strip()
if len(line) == 0:
continue
elif line[0] == '#':
try:
current_conversation.label_speaker(line.split()[1], 1)
except IndexError:
continue
current_conversation.utterances = current_conversation.utterances[:
CONVERSATION_LENGTH]
from hare import load_pretrained, Conversation, load_example_conversations
from hare.tensorflowbrain import BiGruBrain
simple_hare = load_pretrained('hare/pretrained/moba')
print(simple_hare.brain.determine_impact_of_words('well played noob'))
convo = Conversation()
convo.add_utterance(speaker='a', content='i am nice')
convo.add_utterance(speaker='b', content='FCK U YOU SUCK')
convo.add_utterance(speaker='b', content='YOU ARE LOSERS')
convo.add_utterance(speaker='a', content='well done')
convo.add_utterance(speaker='b', content='noobs fuckheads')
convo.add_utterance(speaker='a', content='no problem')
convo.label_speaker('b', 1)
simple_hare.add_conversation(convo)
simple_hare.update_status_history_for_conversation()
simple_hare.visualize_history_for_conversation()
for n, conversation in enumerate(load_example_conversations()):
simple_hare.add_conversation(conversation)
simple_hare.visualize_history_for_conversation(n + 1)
from hare import Hare, Conversation
from hare.bigrubrain import BiGruBrain
#Load the conversations
CONVERSATIONS_FILE = 'datasets/LoL/conversations_anon.txt'
NR_OF_CONVERSATIONS = 5000
conversations = []
current_conversation = Conversation()
for line in open(CONVERSATIONS_FILE):
line = line.strip()
if len(line) == 0:
continue
elif line[0] == '#':
try:
current_conversation.label_speaker(line.split()[1], 1)
except IndexError:
continue
conversations.append(current_conversation)
current_conversation = Conversation()
if len(conversations) % 100 == 0:
print(len(conversations))
if len(conversations) == NR_OF_CONVERSATIONS:
break
continue
from hare import load_pretrained, Conversation
CONVERSATIONS_FILE = 'datasets/LoL/single_conversation.txt'
current_conversation = Conversation()
print('loading conversation')
for line in open(CONVERSATIONS_FILE):
line = line.strip()
if len(line) == 0:
continue
elif line[0] == '#':
break
speaker, content = line.split('\t')
current_conversation.add_utterance(speaker, content)
print('loading pretrained moba')
moba_hare = load_pretrained('hare/pretrained/moba')
print('adding conversation')
moba_hare.add_conversation(current_conversation)
print('visualizing convo')
from hare import Hare, Conversation
from hare.brain import RandomBrain
random_hare = Hare()
random_hare.brain = RandomBrain()
convo = Conversation()
random_hare.add_conversation(convo)
convo.add_utterance(speaker='a', content='hello')
convo.add_utterance(speaker='b', content='hello')
convo.add_utterance(speaker='a', content='how is everyone doing?')
random_hare.update_status_history_for_conversation(0)
print(random_hare.status_per_conversation[0])
convo.label_speaker('b', 0.9)
acc = random_hare.calculate_retrospective_accuracy()
print(acc)