import tensorflow as tf
import numpy as np
x_ = [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] for i in range(10)]
x_ = np.asarray(x_)
print(x_)
x = tf.placeholder(tf.float32, [10, 10])
v = tf.reduce_sum(x, 0)
init = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init)
res = sess.run(v, feed_dict={x: x_})
print(res)

79a6c5b88a3ce546c71e35dde8cda560ded1a953
<mask token>

<mask token>
print(x_)
<mask token>
sess.run(init)
<mask token>
print(res)

<mask token>
x_ = [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] for i in range(10)]
x_ = np.asarray(x_)
print(x_)
x = tf.placeholder(tf.float32, [10, 10])
v = tf.reduce_sum(x, 0)
init = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init)
res = sess.run(v, feed_dict={x: x_})
print(res)

import tensorflow as tf
import numpy as np
x_ = [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9] for i in range(10)]
x_ = np.asarray(x_)
print(x_)
x = tf.placeholder(tf.float32, [10, 10])
v = tf.reduce_sum(x, 0)
init = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init)
res = sess.run(v, feed_dict={x: x_})
print(res)
