basic_framework.py

# -*- coding:utf-8 -*-
#! /usr/bin/env python
#################################################################################
#     File Name           :     csv_reader.py
#     Created By          :     Hao Li
#     Creation Date       :     [2017-02-24 20:41]
#     Last Modified       :     [2017-02-25 10:09]
#     Description         :      
#################################################################################

import tensorflow as tf

# filename_queue = tf.train.string_input_producer(["data1.csv", "data2.csv"], shuffle=True)
filename_queue = tf.train.string_input_producer(["data0.csv"], shuffle=True, num_epochs=1)

reader = tf.TextLineReader()
key, value = reader.read(filename_queue)

# Default values, in case of empty columns. Also specifies the type of the
# decoded result.
record_defaults = [[1], [1], [1], [1], [1]]
col1, col2, col3, col4, col5 = tf.decode_csv(
            value, record_defaults=record_defaults
        )
features = tf.stack([col1, col2, col3, col4])

batch_size = 8
min_after_dequeue = 10
capacity = min_after_dequeue + 2 * batch_size
feature_batch, label_batch = tf.train.shuffle_batch(
        [features, col5], batch_size=batch_size, capacity=capacity,
        min_after_dequeue=min_after_dequeue, allow_smaller_final_batch=True
        )
# tf.initialize_all_variables()
with tf.Session() as sess:
    # Start populating the filename queue.
    # sess.run(tf.initialize_all_variables())
    sess.run(tf.local_variables_initializer())
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(coord=coord)

    try:
        while not coord.should_stop():
        # for _ in range(60):
            # Retrieve a single instance:
            # example, label = sess.run([features, col5])
            examples, labels = sess.run([feature_batch, label_batch])
            # print(example, label)
            print(examples, labels)
    except Exception as e:
        coord.request_stop(e)
        print("Exception ")
    finally:
        coord.request_stop()
        coord.join(threads)