def csv_reader_dataset(filenames, n_readers=5,
batch_size=32, n_parse_threads=5,
shuffle_buffer_size=10000):
dataset = tf.data.Dataset.list_files(filenames)
dataset = dataset.repeat()
dataset = dataset.interleave(
lambda filename: tf.data.TextLineDataset(filename).skip(1),
cycle_length = n_readers
)
dataset.shuffle(shuffle_buffer_size)
dataset = dataset.map(parse_csv_line,
num_parallel_calls=n_parse_threads)
dataset = dataset.batch(batch_size)
return dataset
train_set = csv_reader_dataset(train_filenames,
batch_size = batch_size)
valid_set = csv_reader_dataset(valid_filenames,
batch_size = batch_size)
test_set = csv_reader_dataset(test_filenames,
batch_size = batch_size)
老师，这段代码中 ***dataset = dataset.repeat()***将数据集重复了无限次，在后面对训练集，测试集，验证集都调用了此函数，所以对于训练集，测试集，验证集都需要指定在每一个epoch中需要执行的步数，对吗？所以：
history = model.fit(train_set,
validation_data = valid_set,
steps_per_epoch = 11160 // batch_size,
validation_steps = 3870 // batch_size,
epochs = 100,
callbacks = callbacks)
#%%
model.evaluate(test_set, steps = 5160 // batch_size)
所以在上述代码中，有所示的三条语句， steps_per_epoch = 11160 // batch_size,
validation_steps = 3870 // batch_size,
steps = 5160 // batch_size
老师，我理解的对吗？