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Update titanlearn.py
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@ -30,9 +30,10 @@ from sklearn import metrics, datasets
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import numpy as np
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import matplotlib.pyplot as plt
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import math
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import time
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#enable CUDA if possible
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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device = torch.device("cpu")
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#linear_nn: creates a fully connected network given params
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def linear_nn(in_dim, hidden_dim, out_dim, num_hidden, act_fn="tanh", end="none"):
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@ -194,8 +195,12 @@ def retyuoipufdyu():
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data = torch.tensor(datasets.fetch_california_housing()['data']).to(torch.float)
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ground = datasets.fetch_california_housing()['target']
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ground=torch.tensor(ground).to(torch.float)
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ground = torch.tensor(ground).to(torch.float)
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model = linear_nn(8, 100, 1, 20, act_fn = "relu")
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print(model)
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return train_sgd_simple(model,"regression", data, ground, learnrate=1e-4, iters=1000)
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#retyuoipufdyu()
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start = time.time()
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retyuoipufdyu()
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end = time.time()
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print(end-start)
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