压缩文件

import tensorflow as tf 

#函数接口定义

try:tf.Variable(initial_value=None,
				trainable=True,
				collections=None,
				validate_shape=True,
				caching_device=None,
				name=None,
				variable_def=None,
				dtype=None,
				expected_shape=None,
				import_scope=None)
except:pass


#1. 变量创建后会被加入到 GraphKeys.GLOBAL_VARIABLES 中
#2. 默认可被训练，
#3. 实例名字a, b是唯一标志符，重复了会覆盖，但name可以重复
#3. 默认dtype是float32(<-小数)，int32(<-整数)
a 		= 	tf.Variable(10,name='var1')
b		=	tf.Variable([[11,12],[21.0,22.0]],name='var1')
c 		= 	tf.Variable('田偉業',name='var1')

sess 	=	tf.Session(); sess.run(tf.global_variables_initializer())

print(a.eval(session=sess))
#10
print(b.eval(session=sess))
#[[11 12]
# [21 22]]
print(a.shape, a.dtype, a.trainable)
#() <dtype: 'int32_ref'> True
print(b.shape, b.dtype, b.trainable)
#(2, 2) <dtype: 'float32_ref'> True
print(c.shape, c.dtype, c.trainable)
#() <dtype: 'string_ref'> True
print(a.name,b.name,c.name)
#var1:0 var1_1:0 var1_2:0

---

转载请注明来源 https://tianweiye.github.io