process_batch.py

import numpy as np
import tensorflow as tf

TRAIN_DATA = './simple-examples/data/train_data_index.txt'
TRAIN_BATCH_SIZE = 20
TRAIN_NUM_STEP = 35


def read_data(file_path):
    with open(file_path, 'r') as fin:
        id_string = ' '.join([line.strip() for line in fin.readlines()])
    id_list = [int(w) for w in id_string.split()]
    return id_list


def make_batches(id_list, batch_size, num_step):
    num_batches = (len(id_list) - 1) // (batch_size * num_step)
    data = np.array(id_list[: num_batches * batch_size * num_step])
    data = np.reshape(data, [batch_size, num_batches * num_step])
    data_batches = np.split(data, num_batches, axis=1)

    label = np.array(id_list[1: num_batches * batch_size * num_step + 1])
    label = np.reshape(label, [batch_size, num_batches * num_step])
    label_batches = np.split(label, num_batches, axis=1)

    return list(zip(data_batches, label_batches))


def main():
    train_batches = make_batches(read_data(TRAIN_DATA), TRAIN_BATCH_SIZE, TRAIN_NUM_STEP)
    pass


if __name__ == '__main__':
    main()