TensorFlow读取CSV数据（批量）

# -*- coding:utf-8 -*-
import tensorflow as tfdef read_data(file_queue):
reader = tf.TextLineReader(skip_header_lines=1)
key, value = reader.read(file_queue)
defaults = [[0], [0.], [0.], [0.], [0.], ['']]
Id,SepalLengthCm,SepalWidthCm,PetalLengthCm,PetalWidthCm,Species = tf.decode_csv(value, defaults) #因为使用的是鸢尾花数据集，这里需要对y值做转换
preprocess_op = tf.case({
tf.equal(Species, tf.constant('Iris-setosa')): lambda: tf.constant(0),
tf.equal(Species, tf.constant('Iris-versicolor')): lambda: tf.constant(1),
tf.equal(Species, tf.constant('Iris-virginica')): lambda: tf.constant(2),
}, lambda: tf.constant(-1), exclusive=True) return tf.stack([SepalLengthCm,SepalWidthCm,PetalLengthCm,PetalWidthCm]), preprocess_opdef create_pipeline(filename, batch_size, num_epochs=None):
file_queue = tf.train.string_input_producer([filename], num_epochs=num_epochs)
example, label = read_data(file_queue) min_after_dequeue = 1000
capacity = min_after_dequeue + batch_size
example_batch, label_batch = tf.train.shuffle_batch(
[example, label], batch_size=batch_size, capacity=capacity,
min_after_dequeue=min_after_dequeue
) return example_batch, label_batchx_train_batch, y_train_batch = create_pipeline('Iris-train.csv', 50, num_epochs=1000)
x_test, y_test = create_pipeline('Iris-test.csv', 60)init_op = tf.global_variables_initializer()
local_init_op = tf.local_variables_initializer() # local variables like epoch_num, batch_size
with tf.Session() as sess:
sess.run(init_op)
sess.run(local_init_op) # Start populating the filename queue.
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord) # Retrieve a single instance:
try:
#while not coord.should_stop():
while True:
example, label = sess.run([x_train_batch, y_train_batch])
print (example)
print (label)
except tf.errors.OutOfRangeError:
print ('Done reading')
finally:
coord.request_stop() coord.join(threads)
sess.close()

Id,SepalLengthCm,SepalWidthCm,PetalLengthCm,PetalWidthCm,Species
21,5.4,3.4,1.7,0.2,Iris-setosa
22,5.1,3.7,1.5,0.4,Iris-setosa
23,4.6,3.6,1.0,0.2,Iris-setosa
24,5.1,3.3,1.7,0.5,Iris-setosa
25,4.8,3.4,1.9,0.2,Iris-setosa
26,5.0,3.0,1.6,0.2,Iris-setosa
27,5.0,3.4,1.6,0.4,Iris-setosa
28,5.2,3.5,1.5,0.2,Iris-setosa
29,5.2,3.4,1.4,0.2,Iris-setosa
30,4.7,3.2,1.6,0.2,Iris-setosa
31,4.8,3.1,1.6,0.2,Iris-setosa
32,5.4,3.4,1.5,0.4,Iris-setosa
33,5.2,4.1,1.5,0.1,Iris-setosa
34,5.5,4.2,1.4,0.2,Iris-setosa
35,4.9,3.1,1.5,0.1,Iris-setosa
36,5.0,3.2,1.2,0.2,Iris-setosa
37,5.5,3.5,1.3,0.2,Iris-setosa