module 'tensorflow._api.v2.train' has no attribute 'GradientDescentOptimizer'

Question

I used Python 3.7.3 and installed tensorflow 2.0.0-alpha0,But there are some problems。such as module 'tensorflow._api.v2.train' has no attribute 'GradientDescentOptimizer' Here's all my code

import  tensorflow as tf
import  numpy as np

x_data=np.random.rand(1,10).astype(np.float32)
y_data=x_data*0.1+0.3


Weights = tf.Variable(tf.random.uniform([1], -1.0, 1.0))
biases = tf.Variable(tf.zeros([1]))
y=Weights*x_data+biases

loss=tf.reduce_mean(tf.square(y-y_data))

optimizer=tf.train.GradientDescentOptimizer(0.5)
train=optimizer.minimize(loss)

init = tf.global_variables_initializer()  

sess = tf.Session()
sess.run(init)          

for step in range(201):
    sess.run(train)
    if step % 20 == 0:
        print(step, sess.run(Weights), sess.run(biases))

Answer 1

You are using Tensorflow 2.0. The following code will be helpful:

import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()

Answer 2

In TensorFlow 2.0, Keras became the default high-level API, and optimizer functions migrated from tf.keras.optimizers into separate API called tf.optimizers . They inherit from Keras class Optimizer. Relevant functions from tf.train aren't included into TF 2.0. So to access GradientDescentOptimizer , call tf.optimizers.SGD

Answer 3

This is because you are using TensorFlow version 2.

`tf.train.GradientDescentOptimizer(0.5)`

The above call is for TensorFlow version 1(ex: 1.15.0).

You can try pip install tensorflow==1.15.0 to downgrade the TensorFlow and use the code as it is.

Else use the TensorFlow version 2(what you already has) with following call.

tf.optimizers.SGD (learning_rate=0.001, lr_decay=0.0, decay_step=100, staircase=False, use_locking=False, name='SGD')

Answer 4

For the answer @HoyeolKim gave, it may be needed to add:

tf.disable_v2_behavior()

As it is suggested in this answer.