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- import numpy as np
- def read_input_file(file, matrix):
- i = 0
- for line in file:
- list_line = line.split(',')
- for j, c in enumerate(list_line):
- matrix[i, j] = int(c)
- i += 1
- return matrix
- def read_output_file(file, matrix):
- i = 0
- for line in file:
- matrix[i, 0] = int(line[:1])
- i += 1
- return matrix
- training_input = read_input_file(open('binMNIST_data/bindigit_trn.csv'), np.zeros(shape=(8000, 784)))
- testing_input = read_input_file(open('binMNIST_data/bindigit_tst.csv'), np.zeros(shape=(2000, 784)))
- training_out = read_output_file(open('binMNIST_data/targetdigit_trn.csv'), np.zeros(shape=(8000, 1)))
- testing_out = read_output_file(open('binMNIST_data/targetdigit_tst.csv'), np.zeros(shape=(2000, 1)))
- for i in range(28):
- for j in range(28):
- print(str(int(training_input[7999, 28*i+j])), end='')
- print()
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