回答編集履歴

  #n_hidden = [1,2,3,4,5,6,7,8,9,10]

  n_out = 1

  epochs=10

  x = tf.placeholder(dtype= tf.float32, shape=[None,n_in], name='x')

  t = tf.placeholder(dtype= tf.float32, shape=[None,n_out], name='t')

 

  for learn in LEARNING_RATE:

  train_step = tf.train.GradientDescentOptimizer(learn).minimize(loss)

  with tf.Session() as sess:

  sess.run(tf.global_variables_initializer())

  loss_cal=[]

  print(learn)

  print(sess.run(w32))

  })

  loss_cal.append(y_out)

  plt.plot(loss_cal)

  0.01

  [[-0.01278295]

  [ 0.00424424]