def testInvalidKeepProb(self):
x_dim, y_dim = 40, 30
t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32)
with self.assertRaises(ValueError):
alpha_dropout(t, -1.0)
with self.assertRaises(ValueError):
alpha_dropout(t, 1.1)
with self.assertRaises(ValueError):
alpha_dropout(t, [0.0, 1.0])
with self.assertRaises(ValueError):
alpha_dropout(t, array_ops.placeholder(dtypes.float64))
with self.assertRaises(ValueError):
alpha_dropout(t, array_ops.placeholder(dtypes.float32, shape=[2]))
def testInvalidKeepProb(self):
x_dim, y_dim = 40, 30
t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32)
with self.assertRaises(ValueError):
alpha_dropout(t, -1.0)
with self.assertRaises(ValueError):
alpha_dropout(t, 1.1)
with self.assertRaises(ValueError):
alpha_dropout(t, [0.0, 1.0])
with self.assertRaises(ValueError):
alpha_dropout(t, array_ops.placeholder(dtypes.float64))
with self.assertRaises(ValueError):
alpha_dropout(t, array_ops.placeholder(dtypes.float32, shape=[2]))
def testAlphaDropout(self):
x_dim, y_dim = 40, 30
for keep_prob in [0.1, 0.5, 0.8]:
with self.test_session():
t = random_ops.random_normal([x_dim, y_dim])
output = alpha_dropout(t, keep_prob)
self.assertEqual([x_dim, y_dim], output.get_shape())
t_mean, t_std = nn_impl.moments(t, axes=[0, 1])
output_mean, output_std = nn_impl.moments(output, axes=[0, 1])
self.assertLess(abs(t_mean.eval() - output_mean.eval()), 0.1)
self.assertLess(abs(t_std.eval() - output_std.eval()), 0.1)
def testAlphaDropout(self):
x_dim, y_dim = 40, 30
for keep_prob in [0.1, 0.5, 0.8]:
with self.test_session():
t = random_ops.random_normal([x_dim, y_dim])
output = alpha_dropout(t, keep_prob)
self.assertEqual([x_dim, y_dim], output.get_shape())
t_mean, t_std = nn_impl.moments(t, axes=[0, 1])
output_mean, output_std = nn_impl.moments(output, axes=[0, 1])
self.assertLess(abs(t_mean.eval() - output_mean.eval()), 0.1)
self.assertLess(abs(t_std.eval() - output_std.eval()), 0.1)
def testShapedDropoutShapeError(self):
# Runs shaped dropout and verifies an error is thrown on misshapen noise.
x_dim = 40
y_dim = 30
keep_prob = 0.5
t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32)
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, y_dim + 10])
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, y_dim, 5])
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim + 3])
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim])
# test that broadcasting proceeds
_ = alpha_dropout(t, keep_prob, noise_shape=[y_dim])
_ = alpha_dropout(t, keep_prob, noise_shape=[1, y_dim])
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, 1])
_ = alpha_dropout(t, keep_prob, noise_shape=[1, 1])
def testShapedDropoutShapeError(self):
# Runs shaped dropout and verifies an error is thrown on misshapen noise.
x_dim = 40
y_dim = 30
keep_prob = 0.5
t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32)
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, y_dim + 10])
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, y_dim, 5])
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim + 3])
with self.assertRaises(ValueError):
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim])
# test that broadcasting proceeds
_ = alpha_dropout(t, keep_prob, noise_shape=[y_dim])
_ = alpha_dropout(t, keep_prob, noise_shape=[1, y_dim])
_ = alpha_dropout(t, keep_prob, noise_shape=[x_dim, 1])
_ = alpha_dropout(t, keep_prob, noise_shape=[1, 1])
def testNoDropoutFast(self):
x = array_ops.zeros((5, ))
for p in 1, constant_op.constant(1.0):
y = alpha_dropout(x, keep_prob=p)
self.assertTrue(x is y)
def testNoDropoutFast(self):
x = array_ops.zeros((5,))
for p in 1, constant_op.constant(1.0):
y = alpha_dropout(x, keep_prob=p)
self.assertTrue(x is y)
