for trace in trace_list:
#for i in range(nbatches):
#data = [event2id[record[0]]for record in trace_list[trace]]
data = [[event2id[record[0]] for record in trace_list[trace]]]
#data = torch.from_numpy(np.random.randint(1, V, size=(batch, 10))).cuda()
#data[:, 0] = 1
#print(data)
data = torch.Tensor(data).cuda()
src = Variable(data, requires_grad=False)
tgt = Variable(data, requires_grad=False)
#print(batch,nbatches,tgt.size())
yield Batch(src, tgt, 0)
for epoch in range(10):
model.train()
print()
run_epoch(data_gen(Data_test.trace_data, Data_test.event2id, 1), model,
SimpleLossCompute(model.generator, criterion, model_opt))
model.eval()
print(
run_epoch(data_gen(V, 30, 5), model,
SimpleLossCompute(model.generator, criterion, None)))
model.eval()
src = Variable(torch.LongTensor([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]]).cuda())
src_mask = Variable(torch.ones(1, 1, 10))
print(greedy_decode(model, src, src_mask, max_len=10, start_symbol=1))
tgt = torch.Tensor(tgt_batch_temp).cuda()
src = Variable(src, requires_grad=False)
tgt = Variable(tgt, requires_grad=False)
#print(src.size())
yield Batch(src, tgt, padding_dix)
src_batch_temp = list()
tgt_batch_temp = list()
print('xxxxxxxx')
for epoch in range(10):
print(epoch)
model.train()
run_epoch(
data_gen(Data_test.trace_data,
Data_test.event2id,
batch_size=1000,
padding_dix=0), model,
SimpleLossCompute(model.generator, criterion, model_opt))
model.eval()
print(
run_epoch(
data_gen(Data_test.trace_data,
Data_test.event2id,
batch_size=1,
padding_dix=0), model,
SimpleLossCompute(model.generator, criterion, None)))
model.eval()
src = Variable(torch.LongTensor([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]]).cuda())
tgt = torch.Tensor(tgt_batch_temp).cuda()
src = Variable(src, requires_grad=False)
tgt = Variable(tgt, requires_grad=False)
#print(src.size())
yield Batch(src, tgt, padding_dix)
src_batch_temp = list()
tgt_batch_temp = list()
for epoch in range(10):
print(epoch)
model.train()
# run_epoch(data_gen(train_list, Data_test.event2id, batch_size=200, padding_dix=0), model,
# SimpleLossCompute(model.generator, criterion, model_opt))
run_epoch(
data_gen(train_list, Data_test.event2id, batch_size=500,
padding_dix=0), model, TempLossCompute(criterion, model_opt))
model.eval()
print(
run_epoch(
data_gen(test_list,
Data_test.event2id,
batch_size=500,
padding_dix=0), model, TempLossCompute(criterion, None)))
model.eval()
print(
eval_model(
data_gen(test_list, Data_test.event2id, batch_size=500, padding_dix=0),