util.py

"""
Helper function from 
https://github.com/hardmaru/pytorch_notebooks/blob/master/mixture_density_networks.ipynb


MIT License

Copyright (c) 2017

Permission is hereby granted, free of charge, to any person obtaining a copy
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in the Software without restriction, including without limitation the rights
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The above copyright notice and this permission notice shall be included in all
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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SOFTWARE.
"""

import numpy as np
import torch
from torch.autograd import Variable

"""
Generate data
"""


def generate_data(n_samples):
    epsilon = np.random.normal(size=(n_samples))
    x_data = np.random.uniform(-10.5, 10.5, n_samples)
    y_data = 7*np.sin(0.75*x_data) + 0.5*x_data + epsilon

    # change data type and shape, move from numpy to torch
    x_tensor = torch.from_numpy(np.float32(x_data).reshape(n_samples))
    y_tensor = torch.from_numpy(np.float32(y_data).reshape(n_samples))
    x_variable = Variable(x_tensor)
    y_variable = Variable(y_tensor, requires_grad=False)

    return x_data, x_variable, y_data, y_variable