Python源码示例：inception.slim.losses.l1_loss()
示例1
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例2
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例3
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例4
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例5
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例6
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例7
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例8
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例9
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例10
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例11
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例12
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例13
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例14
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例15
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例16
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例17
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例18
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例19
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
示例20
def testL1Loss(self):
with self.test_session():
shape = [5, 5, 5]
num_elem = 5 * 5 * 5
weights = tf.constant(1.0, shape=shape)
wd = 0.01
loss = losses.l1_loss(weights, wd)
self.assertEquals(loss.op.name, 'L1Loss/value')
self.assertAlmostEqual(loss.eval(), num_elem * wd, 5)
