# coding=utf-8
# date: 2018-4-11,18:49:05
# name: smz


import tensorflow as tf
import tensorflow.contrib.slim as slim
import tensorflow.contrib.layers as tf_contrib_layers

def main(input):
    # layer_1 = slim.conv2d(input, 10, [5, 5], 2, scope='layer_1')  # 默认是nn.relu激活
    # layer_1_bn = slim.batch_norm()
    # tf.metrics.mean()
    # tf.identity()
    # with slim.arg_scope()
    tf.nn.conv2d()
    # tf.squeeze()
    # slim.utils.convert_collection_to_dict()
    # tf.add()
    # tf.multiply()
    # tf.subtract()
    # tf.squeeze()
    # tf.square()
    # tf.map_fn()
    # tf.expand_dims()
    # tf.placeholder()
    # tf.get_default_graph()
    # tf.device()
    # tf.split()

    tf.ones_like()
    tf.losses.add_loss()
    tf_contrib_layers.optimize_loss()
    tf.reduce_mean()
    tf.nn.sigmoid_cross_entropy_with_logits()


if __name__ == '__main__':
    a = 0
    main(a)