59487ef2b4
Warning message from old version:
/opt/conda/lib/python3.6/site-packages/torch/nn/functional.py:1047: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
49 lines
1.3 KiB
Python
49 lines
1.3 KiB
Python
"""
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View more, visit my tutorial page: https://morvanzhou.github.io/tutorials/
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My Youtube Channel: https://www.youtube.com/user/MorvanZhou
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Dependencies:
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torch: 0.4
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matplotlib
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"""
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import torch
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import torch.nn.functional as F
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from torch.autograd import Variable
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import matplotlib.pyplot as plt
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# fake data
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x = torch.linspace(-5, 5, 200) # x data (tensor), shape=(100, 1)
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x = Variable(x)
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x_np = x.data.numpy() # numpy array for plotting
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# following are popular activation functions
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y_relu = torch.relu(x).data.numpy()
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y_sigmoid = torch.sigmoid(x).data.numpy()
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y_tanh = torch.tanh(x).data.numpy()
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y_softplus = F.softplus(x).data.numpy() # there's no softplus in torch
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# y_softmax = torch.softmax(x, dim=0).data.numpy() softmax is a special kind of activation function, it is about probability
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# plt to visualize these activation function
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plt.figure(1, figsize=(8, 6))
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plt.subplot(221)
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plt.plot(x_np, y_relu, c='red', label='relu')
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plt.ylim((-1, 5))
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plt.legend(loc='best')
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plt.subplot(222)
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plt.plot(x_np, y_sigmoid, c='red', label='sigmoid')
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plt.ylim((-0.2, 1.2))
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plt.legend(loc='best')
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plt.subplot(223)
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plt.plot(x_np, y_tanh, c='red', label='tanh')
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plt.ylim((-1.2, 1.2))
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plt.legend(loc='best')
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plt.subplot(224)
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plt.plot(x_np, y_softplus, c='red', label='softplus')
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plt.ylim((-0.2, 6))
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plt.legend(loc='best')
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plt.show()
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