本文整理汇总了Python中optimization.AdamWeightDecayOptimizer方法的典型用法代码示例。如果您正苦于以下问题：Python optimization.AdamWeightDecayOptimizer方法的具体用法？Python optimization.AdamWeightDecayOptimizer怎么用？Python optimization.AdamWeightDecayOptimizer使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类optimization的用法示例。
在下文中一共展示了optimization.AdamWeightDecayOptimizer方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_adam
# 需要导入模块: import optimization [as 别名]
# 或者: from optimization import AdamWeightDecayOptimizer [as 别名]
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
# 需要导入模块: import optimization [as 别名]
# 或者: from optimization import AdamWeightDecayOptimizer [as 别名]
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) 开发者ID:Nagakiran1，项目名称:Extending-Google-BERT-as-Question-and-Answering-model-and-Chatbot，代码行数:22，代码来源:optimization_test.py
示例3: test_adam
# 需要导入模块: import optimization [as 别名]
# 或者: from optimization import AdamWeightDecayOptimizer [as 别名]
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)