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zhoufeng3
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新增17，测试是否成功
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‎12_plot_activations.py

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Lines changed: 143 additions & 143 deletions
Original file line numberDiff line numberDiff line change
@@ -1,144 +1,144 @@
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import numpy as np
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import matplotlib.pyplot as plt
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##### Sigmoid
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sigmoid = lambda x: 1 / (1 + np.exp(-x))
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,100)
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fig = plt.figure()
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plt.plot(y,sigmoid(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('Sigmoid Function')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-2, -1, 0, 1, 2])
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plt.ylim(-2, 2)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('sigmoid.png')
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fig = plt.figure()
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##### TanH
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tanh = lambda x: 2*sigmoid(2*x)-1
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,100)
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plt.plot(y,tanh(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('TanH Function')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.ylim(-4, 4)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('tanh.png')
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fig = plt.figure()
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##### ReLU
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relu = lambda x: np.where(x>=0, x, 0)
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,1000)
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plt.plot(y,relu(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('ReLU')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.ylim(-4, 4)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('relu.png')
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fig = plt.figure()
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##### Leaky ReLU
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leakyrelu = lambda x: np.where(x>=0, x, 0.1*x)
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,1000)
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plt.plot(y,leakyrelu(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('Leaky ReLU')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.ylim(-4, 4)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('lrelu.png')
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fig = plt.figure()
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##### Binary Step
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bstep = lambda x: np.where(x>=0, 1, 0)
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,1000)
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plt.plot(y,bstep(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('Step Function')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-2, -1, 0, 1, 2])
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plt.ylim(-2, 2)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('step.png')
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1+
import numpy as np
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import matplotlib.pyplot as plt
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##### Sigmoid
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sigmoid = lambda x: 1 / (1 + np.exp(-x))
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,100)
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fig = plt.figure()
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plt.plot(y,sigmoid(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('Sigmoid Function')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-2, -1, 0, 1, 2])
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plt.ylim(-2, 2)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('sigmoid.png')
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fig = plt.figure()
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##### TanH
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tanh = lambda x: 2*sigmoid(2*x)-1
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,100)
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plt.plot(y,tanh(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('TanH Function')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.ylim(-4, 4)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('tanh.png')
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fig = plt.figure()
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##### ReLU
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relu = lambda x: np.where(x>=0, x, 0)
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,1000)
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plt.plot(y,relu(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('ReLU')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.ylim(-4, 4)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('relu.png')
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fig = plt.figure()
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##### Leaky ReLU
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leakyrelu = lambda x: np.where(x>=0, x, 0.1*x)
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,1000)
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plt.plot(y,leakyrelu(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('Leaky ReLU')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.ylim(-4, 4)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('lrelu.png')
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fig = plt.figure()
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##### Binary Step
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bstep = lambda x: np.where(x>=0, 1, 0)
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x=np.linspace(-10,10,10)
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y=np.linspace(-10,10,1000)
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plt.plot(y,bstep(y),'b', label='linspace(-10,10,100)')
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plt.grid(linestyle='--')
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plt.xlabel('X Axis')
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plt.ylabel('Y Axis')
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plt.title('Step Function')
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plt.xticks([-4, -3, -2, -1, 0, 1, 2, 3, 4])
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plt.yticks([-2, -1, 0, 1, 2])
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plt.ylim(-2, 2)
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plt.xlim(-4, 4)
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plt.show()
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#plt.savefig('step.png')
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print('done')

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