claclacla

#!/usr/bin/env python3

# Example: python predict.py ../aipnd-project/flowers/test/10/image_07090.jpg ../model/checkpoint.pth
# Example: python predict.py ../aipnd-project/flowers/test/10/image_07090.jpg ../model/checkpoint.pth --topk 5 --gpu
# Example: python predict.py ../aipnd-project/flowers/test/10/image_07090.jpg ../model/checkpoint.pth --topk 5 --category_names ../aipnd-project/cat_to_name.json --gpu

# https://github.com/pytorch/examples/blob/master/imagenet/main.py#L139

import argparse

claclacla

# Standard deviation formula:
# SD = sqrt(sum(x - m)**2) / n

# x: the value in the dataset
# m: the mean of the dataset
# n: the number of values in the dataset

import math

N = [32, 30, 29, 33]

claclacla

# Softmax function
# SF(M) = e(A[i]) / sum(e(A))

# M: The given matrix

M = np.array([1, 2, 3])
    
# Calculate the exponential of all elements in the input array
    
M = np.exp(M)