本文整理匯總了Python中optimization.AdamWeightDecayOptimizer方法的典型用法代碼示例。如果您正苦於以下問題：Python optimization.AdamWeightDecayOptimizer方法的具體用法？Python optimization.AdamWeightDecayOptimizer怎麽用？Python optimization.AdamWeightDecayOptimizer使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類optimization的用法示例。
在下文中一共展示了optimization.AdamWeightDecayOptimizer方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_adam
# 需要導入模塊: import optimization [as 別名]
# 或者: from optimization import AdamWeightDecayOptimizer [as 別名]
def test_adam(self):
with self.test_session() as sess:
w = tf.get_variable(
"w",
shape=[3],
initializer=tf.constant_initializer([0.1, -0.2, -0.1]))
x = tf.constant([0.4, 0.2, -0.5])
loss = tf.reduce_mean(tf.square(x - w))
tvars = tf.trainable_variables()
grads = tf.gradients(loss, tvars)
global_step = tf.train.get_or_create_global_step()
optimizer = optimization.AdamWeightDecayOptimizer(learning_rate=0.2)
train_op = optimizer.apply_gradients(zip(grads, tvars), global_step)
init_op = tf.group(tf.global_variables_initializer(),
tf.local_variables_initializer())
sess.run(init_op)
for _ in range(100):
sess.run(train_op)
w_np = sess.run(w)
self.assertAllClose(w_np.flat, [0.4, 0.2, -0.5], rtol=1e-2, atol=1e-2) 示例2: test_adam
# 需要導入模塊: import optimization [as 別名]
# 或者: from optimization import AdamWeightDecayOptimizer [as 別名]
def test_adam(self):
with self.test_session() as sess:
w = tf.get_variable(
"w",
shape=[3],
initializer=tf.constant_initializer([0.1, -0.2, -0.1]))
x = tf.constant([0.4, 0.2, -0.5])
loss = tf.reduce_mean(tf.square(x - w))
tvars = tf.trainable_variables()
grads = tf.gradients(loss, tvars)
global_step = tf.train.get_or_create_global_step()
optimizer = optimization.AdamWeightDecayOptimizer(learning_rate=0.2)
train_op = optimizer.apply_gradients(zip(grads, tvars), global_step)
init_op = tf.group(tf.global_variables_initializer(),
tf.local_variables_initializer())
sess.run(init_op)
for _ in range(100):
sess.run(train_op)
w_np = sess.run(w)
self.assertAllClose(w_np.flat, [0.4, 0.2, -0.5], rtol=1e-2, atol=1e-2) 開發者ID:Nagakiran1，項目名稱:Extending-Google-BERT-as-Question-and-Answering-model-and-Chatbot，代碼行數:22，代碼來源:optimization_test.py
示例3: test_adam
# 需要導入模塊: import optimization [as 別名]
# 或者: from optimization import AdamWeightDecayOptimizer [as 別名]
def test_adam(self):
with self.test_session() as sess:
w = tf.compat.v1.get_variable(
"w",
shape=[3],
initializer=tf.compat.v1.constant_initializer([0.1, -0.2, -0.1]))
x = tf.constant([0.4, 0.2, -0.5])
loss = tf.reduce_mean(input_tensor=tf.square(x - w))
tvars = tf.compat.v1.trainable_variables()
grads = tf.gradients(ys=loss, xs=tvars)
global_step = tf.compat.v1.train.get_or_create_global_step()
optimizer = optimization.AdamWeightDecayOptimizer(learning_rate=0.2)
train_op = optimizer.apply_gradients(zip(grads, tvars), global_step)
init_op = tf.group(tf.compat.v1.global_variables_initializer(),
tf.compat.v1.local_variables_initializer())
sess.run(init_op)
for _ in range(100):
sess.run(train_op)
w_np = sess.run(w)
self.assertAllClose(w_np.flat, [0.4, 0.2, -0.5], rtol=1e-2, atol=1e-2)