def _create_tfclassifier():
        """
        To create a simple TensorFlowClassifier for testing.
        :return:
        """
        import tensorflow as tf

        # Define input and output placeholders
        input_ph = tf.placeholder(tf.float32, shape=[None, 28, 28, 1])
        labels_ph = tf.placeholder(tf.int32, shape=[None, 10])

        # Define the TensorFlow graph
        conv = tf.layers.conv2d(input_ph, 4, 5, activation=tf.nn.relu)
        conv = tf.layers.max_pooling2d(conv, 2, 2)
        fc = tf.layers.flatten(conv)

        # Logits layer
        logits = tf.layers.dense(fc, 10)

        # Train operator
        loss = tf.reduce_mean(tf.losses.softmax_cross_entropy(logits=logits, onehot_labels=labels_ph))
        optimizer = tf.train.AdamOptimizer(learning_rate=0.01)
        train = optimizer.minimize(loss)

        # TensorFlow session and initialization
        sess = tf.Session()
        sess.run(tf.global_variables_initializer())

        # Create the classifier
        tfc = TensorFlowClassifier(
            input_ph=input_ph,
            output=logits,
            labels_ph=labels_ph,
            train=train,
            loss=loss,
            learning=None,
            sess=sess,
            clip_values=(0, 1),
        )

        return tfc

        To create a simple TensorFlowClassifier for testing.
        :return:
        
tests/metrics/test_metrics.py