我已经采用了提供的鲍鱼示例,并确保我已经理解了......好吧,我想我做到了.但是作为我正在研究的另一个估算项目是生产垃圾 - 我试图添加张量板,所以我可以理解发生了什么.
基本代码是https://www.tensorflow.org/extend/estimators
我添加了一个Session和一个writer
# Set model params
model_params = {"learning_rate": 0.01}
with tf.Session () as sess:
# Instantiate Estimator
nn = tf.contrib.learn.Estimator(model_fn=model_fn, params=model_params)
writer = tf.summary.FileWriter ( '/tmp/ab_tf' , sess.graph)
nn.fit(x=training_set.data, y=training_set.target, steps=5000)
# Score accuracy
ev = nn.evaluate(x=test_set.data, y=test_set.target, steps=1)
And added 1 line in the model_fn function so it looks like this...
def model_fn(features, targets, mode, params):
"""Model function for Estimator."""
# Connect the first hidden layer to input layer
# (features) with relu activation …我正在尝试更新一个简单的三层关系表集。
他们是
该模型的 SQLAlchemy 代码如下所示
class Parent(Base):
__tablename__ = 'parent'
id = Column(Integer, primary_key=True)
name = Column(String)
children = relationship("Child", back_populates="parents")
class Child(Base):
__tablename__ = 'child'
id = Column(Integer, primary_key=True)
name = Column(String)
parent_id = Column(Integer, ForeignKey('parent.id'))
parents = relationship("Parent", back_populates="children")
grandchildren = relationship("GrandChild",
back_populates="grandparent",
)
class GrandChild(Base):
__tablename__ = 'grandchild'
id = Column(Integer, primary_key=True)
name = Column(String)
parent_id = Column(Integer, ForeignKey('parent.id'))
child_id = Column(Integer, ForeignKey('child.id'))
grandparent = relationship("Child", back_populates="grandchildren")
插入代码看起来像这样......
p3 = Parent(name="P3")
c5 = Child(name="C5") …