Python × TensorFlow ③ ～TensorFlow を扱う上で必要な知識「プレースホルダ」～

import tensorflow as tf
import numpy as np

a = tf.constant(3)
b = tf.placeholder(dtype=tf.int32, shape=None)
c = tf.add(a, b)

with tf.Session() as sess:
    print(sess.run(c, feed_dict={b: 1}))
    print(sess.run(c, feed_dict={b: [1, 2, 3, 4]}))
    print(sess.run(c, feed_dict={b: np.random.randint(0, 9, 10)}))
    
# 以下，実行結果
# 4
# [4 5 6 7]
# [ 4  7  8  4  7  3  4  9 10  4]

import tensorflow as tf

a = tf.constant(3)
b = tf.placeholder(dtype=tf.int32, shape=None)
c = tf.add(a, b)

with tf.Session() as sess:
    print(sess.run(c, feed_dict={b: tf.ones(shape=[2, 3])}))
  
# 以下，実行結果
# TypeError: The value of a feed cannot be a tf.Tensor object. 
# Acceptable feed values include Python scalars, strings, lists, numpy ndarrays, or TensorHandles.

import tensorflow as tf

a = tf.constant(3)
b = tf.placeholder(dtype=tf.int32, shape=None)
c = tf.add(a, b)

with tf.Session() as sess:
    ones_tsr = sess.run(tf.ones(shape=[2, 3]))
    print(sess.run(c, feed_dict={b: ones_tsr}))
    
    print(type(tf.ones(shape=[2, 3])))
    print(type(ones_tsr))
  
# 以下，実行結果
# [[4 4 4]
#  [4 4 4]]
# <class 'tensorflow.python.framework.ops.Tensor'>
# <class 'numpy.ndarray'>

import tensorflow as tf

a = tf.Variable(tf.constant(1))
b = tf.constant(1)
c = tf.placeholder(dtype=tf.float32, shape=None)

print(type(a))
print(type(b))
print(type(c))

# 以下，実行結果
# <class 'tensorflow.python.ops.variables.Variable'>
# <class 'tensorflow.python.framework.ops.Tensor'>
# <class 'tensorflow.python.framework.ops.Tensor'>

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
import matplotlib.pyplot as plt

a = tf.placeholder(dtype=tf.float32, shape=(None, 28, 28))
b = tf.constant(255.0)
c = a * b

with tf.Session() as sess:
    mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
    img = mnist.train.images
    img = img.reshape(-1, 28, 28)
    result = sess.run(c, feed_dict={a: img})

for i in range(6):
    plt.subplot(2, 3, i+1)
    plt.imshow(result[i])
plt.show()