Tensorflow是Google開發的開源機器學習庫。它的應用之一是開發深度神經網絡。
模塊tensorflow.math
為許多基本的數學運算提供支持。函數tf.cos()
[別名tf.math.cos
]為Tensorflow中的餘弦函數提供支持。它期望輸入為弧度形式,並且輸出範圍為[-1,1]。輸入類型為張量,如果輸入包含多個元素,則將計算按元素的餘弦值。
用法:tf.cos(x, name=None) or tf.math.cos(x, name=None)
參數:
x:以下任何類型的張量:float16,float32,float64,complex64或complex128。
name(可選):操作的名稱。
返回類型:與x具有相同類型的張量。
代碼1:
# Importing the Tensorflow library
import tensorflow as tf
# A constant vector of size 6
a = tf.constant([1.0, -0.5, 3.4, -2.1, 0.0, -6.5], dtype = tf.float32)
# Applying the sin function and
# storing the result in 'b'
b = tf.cos(a, name ='cos')
# Initiating a Tensorflow session
with tf.Session() as sess:
print('Input type:', a)
print('Input:', sess.run(a))
print('Return type:', b)
print('Output:', sess.run(b))
輸出:
Input type:Tensor("Const_2:0", shape=(6, ), dtype=float32) Input:[ 1. -0.5 3.4000001 -2.0999999 0. -6.5 ] Return type:Tensor("cos:0", shape=(6, ), dtype=float32) Output:[ 0.54030228 0.87758255 -0.96679819 -0.50484604 1. 0.97658765]
代碼2:可視化
# Importing the Tensorflow library
import tensorflow as tf
# Importing the NumPy library
import numpy as np
# Importing the matplotlib.pylot function
import matplotlib.pyplot as plt
# A vector of size 15 with values from -5 to 5
a = np.linspace(-5, 5, 15)
# Applying the sigmoid function and
# storing the result in 'b'
b = tf.cos(a, name ='cos')
# Initiating a Tensorflow session
with tf.Session() as sess:
print('Input:', a)
print('Output:', sess.run(b))
plt.plot(a, sess.run(b), color = 'red', marker = "o")
plt.title("tensorflow.cos")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
輸出:
Input:[-5. -4.28571429 -3.57142857 -2.85714286 -2.14285714 -1.42857143 -0.71428571 0. 0.71428571 1.42857143 2.14285714 2.85714286 3.57142857 4.28571429 5. ] Output:[ 0.28366219 -0.41384591 -0.90903414 -0.9598162 -0.5413659 0.1417459 0.75556135 1. 0.75556135 0.1417459 -0.5413659 -0.9598162 -0.90903414 -0.41384591 0.28366219]
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注:本文由純淨天空篩選整理自vaibhav29498大神的英文原創作品 Python | Tensorflow cos() method。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。