row_shuffle Dense Weights

shuffle_rows.py

magic_number_1 = size_of_last_conv_layer
magic_number_2 = number_of_rows_in_dense / magic_number_1

def shuffle_rows(original_w):
	converted_w = np.zeros(original_w.shape)
	count = 0
	for index, row in enumerate(original_w):
		if (index % magic_number_1) == 0 and index != 0:
			count += 1
		new_index = ((index % magic_number_1) * magic_number_2) + count
		print("index from " + str(index) + " -> " + str(new_index))
		converted_w[new_index] = row
		initial = 1
	return converted_w