Created
February 26, 2018 00:35
-
-
Save jireh-father/6fdd33af90033ca5711934a835d0b4ed to your computer and use it in GitHub Desktop.
variance test
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| # import tensorflow as tf | |
| import numpy as np | |
| # x1 = np.random.random_integers(5, size=(3,2)) | |
| x1 = np.array([[1], [2], [3], [4], [5], [6], [7], [8], [9], [100]]) | |
| x2 = np.array([[1], [2], [3], [4], [5], [6], [7], [8], [9], [10]]) | |
| print(x1.var(), x2.var()) | |
| w1 = np.random.randn(10, 10) | |
| w2 = np.random.randn(10, 10) | |
| w2[0][0] = 100 | |
| print(w1.var()) | |
| # f = lambda x: 1.0/(1.0 + np.exp(-x)) # activation function (use sigmoid) | |
| # x = np.random.randn(10, 1) # random input vector of three numbers (3x1) | |
| # h1 = f(np.dot(W1, x) + b1) # calculate first hidden layer activations (4x1) | |
| # h2 = f(np.dot(W2, h1) + b2) # calculate second hidden layer activations (4x1) | |
| # out = np.dot(W3, h2) + b3 | |
| ret = np.dot(w1, x1) | |
| print(ret.var()) | |
| print(ret.mean()) | |
| ret = np.matmul(w1, x2) | |
| print(ret.var()) | |
| print(ret.mean()) | |
| ret = np.matmul(w1, np.matmul(w1, np.matmul(w1, x1))) | |
| print(ret.var()) | |
| print(ret.mean()) | |
| ret = np.matmul(w1, np.matmul(w1, np.matmul(w1, x2))) | |
| print(ret.var()) | |
| print(ret.mean()) | |
| ret = np.matmul(w2, np.matmul(w2, np.matmul(w2, x2))) | |
| print(ret.var()) | |
| print(ret.mean()) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment