def test_sigmoid(self):
# TODO: why not simulate math.sigmoid like with rsqrt?
inputValues = [-1000,-1,0,0.5,1,2,1000]
expectedOutput = [0.0000, 0.2689, 0.5, 0.6225, 0.7311, 0.8808, 1.000]
precision_4dps = 0.0002
def checkType(tensor):
self.assertEqual(tensor(inputValues).sigmoid(), tensor(expectedOutput), precision_4dps)
checkType(torch.FloatTensor)
checkType(torch.DoubleTensor)
python类sigmoid()的实例源码
def test_sigmoid(self):
# TODO: why not simulate math.sigmoid like with rsqrt?
inputValues = [-1000, -1, 0, 0.5, 1, 2, 1000]
expectedOutput = [0.0000, 0.2689, 0.5, 0.6225, 0.7311, 0.8808, 1.000]
precision_4dps = 0.0002
def checkType(tensor):
self.assertEqual(tensor(inputValues).sigmoid(), tensor(expectedOutput), precision_4dps)
checkType(torch.FloatTensor)
checkType(torch.DoubleTensor)
def test_sigmoid(self):
# TODO: why not simulate math.sigmoid like with rsqrt?
inputValues = [-1000, -1, 0, 0.5, 1, 2, 1000]
expectedOutput = [0.0000, 0.2689, 0.5, 0.6225, 0.7311, 0.8808, 1.000]
precision_4dps = 0.0002
def checkType(tensor):
self.assertEqual(tensor(inputValues).sigmoid(), tensor(expectedOutput), precision_4dps)
checkType(torch.FloatTensor)
checkType(torch.DoubleTensor)
def test_sigmoid(self):
# TODO: why not simulate math.sigmoid like with rsqrt?
inputValues = [-1000, -1, 0, 0.5, 1, 2, 1000]
expectedOutput = [0.0000, 0.2689, 0.5, 0.6225, 0.7311, 0.8808, 1.000]
precision_4dps = 0.0002
def checkType(tensor):
self.assertEqual(tensor(inputValues).sigmoid(), tensor(expectedOutput), precision_4dps)
checkType(torch.FloatTensor)
checkType(torch.DoubleTensor)
def test_sigmoid(self):
# TODO: why not simulate math.sigmoid like with rsqrt?
inputValues = [-1000, -1, 0, 0.5, 1, 2, 1000]
expectedOutput = [0.0000, 0.2689, 0.5, 0.6225, 0.7311, 0.8808, 1.000]
precision_4dps = 0.0002
def checkType(tensor):
self.assertEqual(tensor(inputValues).sigmoid(), tensor(expectedOutput), precision_4dps)
checkType(torch.FloatTensor)
checkType(torch.DoubleTensor)