25_Tensorflow_상수와변수

import warnings 
warnings.filterwarnings('ignore')
!pip install tensorflow

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# tensorflow 라이브러리를 설치하고 tf라는 별명을 지정한다.
# !pip install tensorflow
#!pip install tensorflow
#import tensorflow as tf # 2.x 버전 import
# tensorflow 2.x버전이 설치된 경우 tensorflow 1.x버전 문법을 사용하기 위해
# 아래와 같이 import한다
import tensorflow.compat.v1 as tf

# tensorflow 2.x버전의 문법을 사용하지 않켔다고 선언한다.
tf.disable_v2_behavior()
print(tf.__version__)

WARNING:tensorflow:From c:\python\lib\site-packages\tensorflow\python\compat\v2_compat.py:101: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
Instructions for updating:
non-resource variables are not supported in the long term
2.6.2

상수,수식을 만든다 => 세션을 만든다.=> 실행한다. tensorflow상수

# constant()함수로 tensorflow에서 사용할 상수를 정의한다.
a = tf.constant(300) #상수를 정의한다.
print(a)

b = tf.constant(500) #상수를 정의한다.
print(b)

c=a+b #수식을 정의한다.
print(c)

d = tf.add(a,b)
print(d)

#tensorflow는 반드시 Session이라는 작업 영역을
#만든 후 상수, 변수,수식을 대입한 다음 실행해야 한다.
sess = tf.Session() # Session을 만든다.

#run() 함수로 tensorflow에서 Session의 내용을 실행한다.
print('a : {}'.format(sess.run(a)))
print('b : {}'.format(sess.run(b)))
print('c : {}'.format(sess.run(c)))
print('d : {}'.format(sess.run(d)))

Tensor("Const_19:0", shape=(), dtype=int32)
Tensor("Const_20:0", shape=(), dtype=int32)
Tensor("add_10:0", shape=(), dtype=int32)
Tensor("Add_11:0", shape=(), dtype=int32)
a : 300
b : 500
c : 800
d : 800

변수를 만든다 => 세션을 만든다. => 변수를 초기화 시킨다. => 실행한다.

tensorflow변수

# Variable() 함수로 tensorflow에서 사용할 변수를 정의한다.
a = tf.Variable(5) #a는 5를 기억하는 변수를 정의한다.
print(a)
b = tf.Variable(3) #b는 5를 기억하는 변수를 정의한다.
print(b)
c=a*b
print(c)

session = tf.Session()

# Variable()함수를 사용해서 생성한 변수는 반드시
# 사용하기 전에 초기화시켜야 한다.
# 변수 초기화는 변수를 사용하기 전 에만 해주면 된다.

# tensorflow 변수 초기화 
# global_variables_initializer() 함수로 tensorflow에서 사용할
# 변수를 초기화시킨다.

#init = tf.global_variables_initializer()
#sess.run(init)

#위의 두줄로 사용한 변수 초기화를 아래와 같이
#한줄로 줄여서 사용할 수 있다.
sess.run(tf.global_variables_initializer())

print('a : {}'.format(sess.run(a)))
print('b : {}'.format(sess.run(b)))
print('c : {}'.format(sess.run(c)))

a = tf.Variable(15) #변수에 저장된 데이터를 변경했다.

#변수에 저장된 데이터가 변경되었으므로, 다시 초기화한다.
sess.run(tf.global_variables_initializer())
d = tf.multiply(a, b)
print('d : {}'.format(sess.run(d)))

<tf.Variable 'Variable_12:0' shape=() dtype=int32_ref>
<tf.Variable 'Variable_13:0' shape=() dtype=int32_ref>
Tensor("mul_6:0", shape=(), dtype=int32)
a : 5
b : 3
c : 15
d : 45