import tensorflow as tf
import numpy as np
graph = tf.Graph()
with graph.as_default():
    A = tf.placeholder(dtype=tf.float32, shape=[1, 2, 3])
    B = A * 2
    C = A * 3
    a_numpy = np.random.rand(1, 2, 3)
    feed_dict = {A: a_numpy}
    sess = tf.Session()
    b_numpy, c_numpy = sess.run((B, C), feed_dict)
    print(a_numpy)
    print(b_numpy)
    print(c_numpy)

05f9551512bf629b787e53d389cd8cddcbae64e3
<mask token>

<mask token>
with graph.as_default():
    A = tf.placeholder(dtype=tf.float32, shape=[1, 2, 3])
    B = A * 2
    C = A * 3
    a_numpy = np.random.rand(1, 2, 3)
    feed_dict = {A: a_numpy}
    sess = tf.Session()
    b_numpy, c_numpy = sess.run((B, C), feed_dict)
    print(a_numpy)
    print(b_numpy)
    print(c_numpy)

<mask token>
graph = tf.Graph()
with graph.as_default():
    A = tf.placeholder(dtype=tf.float32, shape=[1, 2, 3])
    B = A * 2
    C = A * 3
    a_numpy = np.random.rand(1, 2, 3)
    feed_dict = {A: a_numpy}
    sess = tf.Session()
    b_numpy, c_numpy = sess.run((B, C), feed_dict)
    print(a_numpy)
    print(b_numpy)
    print(c_numpy)

import tensorflow as tf
import numpy as np
graph = tf.Graph()
with graph.as_default():
    A = tf.placeholder(dtype=tf.float32, shape=[1, 2, 3])
    B = A * 2
    C = A * 3
    a_numpy = np.random.rand(1, 2, 3)
    feed_dict = {A: a_numpy}
    sess = tf.Session()
    b_numpy, c_numpy = sess.run((B, C), feed_dict)
    print(a_numpy)
    print(b_numpy)
    print(c_numpy)
