def test_tanh(self):
""" tanh函数显示.
"""
print('{} test_tanh {}'.format('-'*15, '-'*15))
data_x = torch.arange(-8.0, 8.0, 0.1, requires_grad=True)
data_y = data_x.tanh()
show_x_y_axis(data_x.detach().numpy(), data_y.detach().numpy(), title='tanh') # 直接弹出图片
def test_show_x_y_axis(self):
""" 显示x、y坐标系.
"""
print('{} test_show_x_y_axis {}'.format('-' * 15, '-' * 15))
data_x = np.arange(0, 10)
data_y = 2 * data_x + 5
show_x_y_axis(data_x, data_y) # 直接弹出图片
def test_sigmoid(self):
""" sigmoid函数显示.
"""
print('{} test_sigmoid {}'.format('-'*15, '-'*15))
data_x = torch.arange(-8.0, 8.0, 0.1, requires_grad=True)
data_y = data_x.sigmoid()
show_x_y_axis(data_x.detach().numpy(), data_y.detach().numpy(), title='sigmoid') # 直接弹出图片
def test_ReLU(self):
""" ReLU函数显示.
"""
print('{} test_ReLU {}'.format('-'*15, '-'*15))
data_x = torch.arange(-8.0, 8.0, 0.1, requires_grad=True)
data_y = data_x.relu()
show_x_y_axis(data_x.detach().numpy(), data_y.detach().numpy(), title='ReLU') # 直接弹出图片
def test_tanh_grad(self):
""" tanh函数梯度显示.
"""
print('{} test_tanh_grad {}'.format('-'*15, '-'*15))
data_x = torch.arange(-8.0, 8.0, 0.1, requires_grad=True)
data_x.tanh().sum().backward()
data_y = data_x.grad
show_x_y_axis(data_x.detach().numpy(), data_y.detach().numpy(), title='tanh grad') # 直接弹出图片
def test_saddle_point(self):
""" 鞍点.
"""
print('{} test_saddle_point {}'.format('-' * 15, '-' * 15))
data_x = np.arange(-2.0, 2.0, 0.1)
data_y = data_x**3
annotates = [{
'text': 'saddle point',
'xy': (0, -0.2),
'xytext': (-0.52, -5.0),
'arrowstyle': '->'
}]
show_x_y_axis(data_x,
data_y,
title='saddle point',
annotates=annotates) # 直接弹出图片
def test_local_minimum(self):
""" 局部最小值显示.
"""
print('{} test_local_minimum {}'.format('-' * 15, '-' * 15))
data_x = np.arange(-1.0, 2.0, 0.1)
data_y = data_x * np.cos(np.pi * data_x)
annotates = [{
'text': 'local minimum',
'xy': (-0.3, -0.25),
'xytext': (-0.7, -1.0),
'arrowstyle': '->'
}, {
'text': 'global minimum',
'xy': (1.1, -0.95),
'xytext': (0.6, 0.8),
'arrowstyle': '->'
}]
show_x_y_axis(data_x,
data_y,
title='local minimum',
annotates=annotates) # 直接弹出图片
