Tensorflow print shape 出现 ? 问号

import  tensorflow as tf
from    tensorflow.keras import datasets, layers, optimizers, Sequential, metrics
from 	tensorflow import keras

def preprocess(x, y):
    x = tf.cast(x, dtype=tf.float32) / 255.
    y = tf.cast(y, dtype=tf.int32)
    return x,y


batchsz = 128
(x, y), (x_val, y_val) = datasets.cifar10.load_data()
y = tf.squeeze(y)
y_val = tf.squeeze(y_val)
y = tf.one_hot(y, depth=10) 
y_val = tf.one_hot(y_val, depth=10) 
print('datasets:', x.shape, y.shape, x_val.shape, y_val.shape, x.min(), x.max())


train_db = tf.data.Dataset.from_tensor_slices((x,y))
train_db = train_db.map(preprocess).shuffle(10000).batch(batchsz)
test_db = tf.data.Dataset.from_tensor_slices((x_val, y_val))
test_db = test_db.map(preprocess).batch(batchsz)


sample = next(iter(train_db))
print('batch:', sample[0].shape, sample[1].shape)

直接输出为

datasets: (50000, 32, 32, 3) (50000, 10) (10000, 32, 32, 3) (10000, 10) 0 255
batch: (?, 32, 32, 3) (?, 10)

这里出现了 '?' 

原因是没有创建graph 与Session

这里我们可以在程序开头加入

tf.enable_eager_execution()

eager_excution 可以直接运行op，而不需要事前建立graph,并且不需要创建session。

输出结果变为

datasets: (50000, 32, 32, 3) (50000, 10) (10000, 32, 32, 3) (10000, 10) 0 255
batch: (128, 32, 32, 3) (128, 10)