test2
This commit is contained in:
ksanu
parent
8b4b2a5232
commit
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22052
dev-0/out_float.tsv
22052
dev-0/out_float.tsv
File diff suppressed because it is too large
Load Diff
2
results.txt
Normal file
2
results.txt
Normal file
@ -0,0 +1,2 @@
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loss = 0.0010254832450300455
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f1: 0.963087248322
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51
s.py
51
s.py
@ -16,7 +16,7 @@ model = nn.Sequential(
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nn.Linear(16,1),
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nn.Sigmoid())
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criterion = nn.MSELoss()
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optimizer = optim.SGD(model.parameters(), lr=0.000001, momentum=0.8)
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optimizer = optim.SGD(model.parameters(), lr=0.001, momentum=0.9)
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#optimizer = optim.Adam(model.parameters())
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@ -132,27 +132,27 @@ testA_x = torch.cat([testA_x_temp.transpose(1,0), testA_x3], 1)
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dataset_train = TrainDataset(x, y)
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trainloader=DataLoader(dataset=dataset_train,batch_size=5)
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def train_loop(i = 4200): #~7h
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for i in range(i):
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for xb, yb_expected in trainloader: # for each iteration a bach of samples is taken from loader(currently batch_size=5)
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yp = model(xb)
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for i in range(2):
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for xb, yb_expected in trainloader: # for each iteration a bach of samples is taken from loader(currently batch_size=5)
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yp = model(xb)
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# debug
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"""
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debug_xb = pandas.DataFrame(xb.numpy())
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debug_yb_expected = pandas.DataFrame(yb_expected.numpy())
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debug_yp = pandas.DataFrame(yp.detach().numpy())
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"""
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loss = criterion(yp, yb_expected)
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optimizer.zero_grad()
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loss.backward()
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optimizer.step()
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print(loss)
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# debug
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"""
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debug_xb = pandas.DataFrame(xb.numpy())
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debug_yb_expected = pandas.DataFrame(yb_expected.numpy())
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debug_yp = pandas.DataFrame(yp.detach().numpy())
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"""
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#print(torch.squeeze(yp))
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#print(yb_expected)
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loss = criterion(torch.squeeze(yp), yb_expected)
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optimizer.zero_grad()
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loss.backward()
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optimizer.step()
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#print(loss)
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#4 200
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elapsed_time = timeit.timeit(train_loop, number=1)
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print("Training time: ", elapsed_time, "seconds")
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#elapsed_time = timeit.timeit(train_loop, number=1)
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#print("Training time: ", elapsed_time, "seconds")
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#saving results:
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#dev0:
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@ -179,14 +179,21 @@ print("f1_score_dev0 after training: ", score,"\nAcc: ", accuracy_score(dev_y_te
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#@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
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#testA:
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testA_y = model(testA_x)
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file=open("test-A/out.tsv","w")
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file=open("test-A/out.tsv","w+")
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file2=open("test-A/out_float.tsv","w")
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for i in range(0,11061):
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file2.write(str(testA_y[i].data.item()) + "\n")
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if testA_y[i].data.item() < 0.5:
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file.write("0" + "\n")
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file.write("0\n")
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else:
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file.write("1" + "\n")
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file.write("1\n")
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file.close()
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file2.close()
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file=open("results.txt","w")
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file.write("loss = " + str(loss.item())+ "\n")
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file.write("f1: " + str(score) + "\n" )
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file.close()
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11026
test-A/expected.tsv
Normal file
11026
test-A/expected.tsv
Normal file
File diff suppressed because it is too large
Load Diff
22122
test-A/out.tsv
22122
test-A/out.tsv
File diff suppressed because it is too large
Load Diff
11061
test-A/out_float.tsv
11061
test-A/out_float.tsv
File diff suppressed because it is too large
Load Diff
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