问TF:如何从用户输入数据创建数据集

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# Create a Dataset
dataset = tf.data.Dataset.zip((input_dataset, label_dataset)).batch(32).repeat(...)

# Create Iterator
input, label = dataset.make_one_shot_iterator()

# Create Placholders
x = tf.placeholder_with_default(input, shape=[...], name='input')
y = tf.placeholder_with_default(label, shape-[...], name='label')

def nn_model(features, labels):
    logits = ...    
    loss = tf.reduce_sum(tf.nn.softmax_cross_entropy_with_logits_v2(labels=labels, logits=logits))
    optimizer = tf.train.AdamOptimizer(learning_rate=0.01).minimize(loss)
    return optimizer, loss

# Create Model
train_op, loss_op = nn_model(x, y)

# Training
sess.run(train_op)

# Inference
sess.run(logits, feed_dict={x:..., y:...})