问TensorFlow2.0-针对大数据集的tf.estimator.DNNClassifier培训

EN

    labels = ['BENIGN', 'Syn', 'UDPLag', 'UDP', 'LDAP', 'MSSQL', 'NetBIOS', 'WebDDoS']

    # Build a DNN
    classifier = tf.estimator.DNNClassifier(
    feature_columns=feature_columns,
    hidden_units=[30, 10],
    n_classes=len(labels),
    label_vocabulary=labels)

    def input_fn(features, labels, training=True, batch_size=32):
       '''
       An input function for training or evaluating
       '''
       # Convert the inputs to a Dataset.
       dataset = tf.data.Dataset.from_tensor_slices((dict(features), labels))
       # Shuffle and repeat if you are in training mode.
       if training:
          dataset = dataset.shuffle(1000).repeat()
       return dataset.batch(batch_size)

    # Train the model
    classifier.train(
    input_fn=lambda: input_fn(train_features, train_label, training=True),
    steps=5000)

train_features.shape
>>> (15891114, 20)
train_label.shape
>>> (15891114,)

WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python

/ops/resource_variable_ops.py:1666: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.
Instructions for updating:
If using Keras pass *_constraint arguments to layers.
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.
Instructions for updating:
Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.
INFO:tensorflow:Calling model_fn.
WARNING:tensorflow:Layer dnn is casting an input tensor from dtype float64 to the layer's dtype of float32, which is new behavior in TensorFlow 2.  The layer has dtype float32 because it's dtype defaults to floatx.

If you intended to run this layer in float32, you can safely ignore this warning. If in doubt, this warning is likely only an issue if you are porting a TensorFlow 1.X model to TensorFlow 2.

To change all layers to have dtype float64 by default, call `tf.keras.backend.set_floatx('float64')`. To change just this layer, pass dtype='float64' to the layer constructor. If you are the author of this layer, you can disable autocasting by passing autocast=False to the base Layer constructor.

WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/optimizer_v2/adagrad.py:106: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
INFO:tensorflow:Done calling model_fn.
INFO:tensorflow:Create CheckpointSaverHook.