Tensorflow-model API

参考：
1、https://github.com/tensorflow/tensorflow
2、http://tflearn.org/doc_index/
3、http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html
4、http://keras-cn.readthedocs.io/en/latest/
5、https://keras.io/
6、http://pytorch.org/tutorials/

1、线性模型

tensorflow

import tensorflow as tffrom tensorflow.contrib.layers.python.layers import fully_connectedfrom tensorflow.contrib import slimfrom tensorflow.contrib import kerastf.nn.softmax(tf.matmul(X, weights) + biases)tf.matmul(X, weights) + biasestf.nn.bias_add(tf.matmul(X, weights),biases)tf.layers.dense(X,512)fc1=fully_connected(        X,        num_outputs=512,        activation_fn=tf.nn.relu,        normalizer_fn=tf.layers.batch_normalization,        weights_initializer=tf.random_uniform_initializer,        biases_initializer=tf.random_normal_initializer,        weights_regularizer=tf.nn.l2_loss,        biases_regularizer=tf.nn.l2_loss,    )slim.fully_connected()slim.layers.fully_connected()keras.layers.Dense()

tflearn

import tflearntflearn.fully_connected()tflearn.layers.fully_connected()

tensorlayer

import tensorlayer as tltl.layers.DenseLayer()

keras

import keraskeras.layers.Dense()

pytorch

import torch.nn as nnfc1 = nn.Linear(16 * 5 * 5, 120)

2、卷积模型

tensorflow

import tensorflow as tffrom tensorflow.contrib.layers.python.layers import fully_connected,convolution2dfrom tensorflow.contrib import slimfrom tensorflow.contrib import kerastf.nn.conv2d()tf.nn.convolution()tf.layers.conv2d()convolution2d()slim.convolution2dslim.conv2dslim.layers.conv2dslim.layers.convolution2dkeras.layers.Conv2D()keras.layers.Convolution2D()

tflearn

import tflearntflearn.conv_2d()tflearn.layers.conv_2d()

tensorlayer

import tensorlayer as tltl.layers.Conv2dLayertl.layers.Conv2d()

keras

import keraskeras.layers.Convolution2Dkeras.layers.Conv2D

pytorch

import torch.nn as nnconv2 = nn.Conv2d(6, 16, 5)