René's URL Explorer Experiment

{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"I am very eager to your reply","articleBody":"from tensorflow.examples.tutorials.mnist import input_data\r\n\r\nimport tensorflow as tf\r\n\r\n\r\ndef weight_varible(shape):\r\n\tinitial =tf.truncated_normal(shape,stddev=0.1)\r\n\treturn tf.Variable(initial)\r\n\r\n\r\ndef bias_variable(shape):\r\n\tinitial=tf.constant(0.1,shape=shape)\r\n\treturn tf.Variable(initial)\r\n\r\ndef conv2d(x,W):\r\n\treturn tf.nn.conv2d(x,W,strides=[1,1,1,1],padding='SAME')\r\n\r\ndef max_pool_2x2(x):\r\n\treturn tf.nn.max_pool(x,ksize=[1,2,2,1],strides=[1,2,2,1],padding='SAME')\r\n\r\nmnist=input_data.read_data_sets('MNIST_data',one_hot=True)\r\nsess=tf.InteractiveSession()\r\n\r\n################ input,for 2 models i use the same input   ################3\r\nx=tf.placeholder(tf.float32,[None,784])\r\nx_image=tf.reshape(x,[-1,28,28,1])\r\n\r\n######################### the first model ########################################\r\nW_conv1=weight_varible([5,5,1,32])\r\nb_conv1=weight_varible([32])\r\n\r\nh_conv1=tf.nn.relu(conv2d(x_image,W_conv1)+b_conv1)\r\nh_pool1=max_pool_2x2(h_conv1)\r\n\r\nW_conv2=weight_varible([5,5,32,64])\r\nb_conv2=weight_varible([64])\r\n\r\nh_conv2=tf.nn.relu(conv2d(h_pool1,W_conv2)+b_conv2)\r\nh_pool2=max_pool_2x2(h_conv2)\r\n\r\nW_fc1=weight_varible([7*7*64,1024])\r\nb_fc1=weight_varible([1024])\r\n\r\nh_pool2_flat=tf.reshape(h_pool2,[-1,7*7*64])\r\nh_fc1=tf.nn.relu(tf.matmul(h_pool2_flat,W_fc1)+b_fc1)\r\n\r\nkeep_prob=tf.placeholder(tf.float32)\r\nh_fc1_drop=tf.nn.dropout(h_fc1,keep_prob)\r\n\r\nW_fc2=weight_varible([1024,10])\r\nb_fc2=weight_varible([10])\r\n\r\ny_conv=tf.nn.softmax(tf.matmul(h_fc1_drop,W_fc2)+b_fc2)\r\ny_=tf.placeholder(tf.float32,[None,10])\r\n\r\ncross_entropy=tf.reduce_sum(y_*tf.log(y_conv))\r\ntrain_step=tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)\r\ncorrect_prediction=tf.equal(tf.argmax(y_conv,1),tf.argmax(y_,1))\r\naccuracy=tf.reduce_mean(tf.cast(correct_prediction,tf.float32))\r\nsess.run(tf.initialize_all_variables())\r\n\r\n##################   the second parallel model,i use the same input as the first  ###############################\r\n\r\nW2_conv1=weight_varible([5,5,1,32])\r\nb2_conv1=weight_varible([32])\r\n\r\n# x=tf.placeholder(tf.float32,[None,784])\r\n# x_image=tf.reshape(x,[-1,28,28,1])\r\n\r\nh2_conv1=tf.nn.relu(conv2d(x_image,W2_conv1)+b2_conv1)\r\nh2_pool1=max_pool_2x2(h2_conv1)\r\n\r\nW2_conv2=weight_varible([5,5,32,64])\r\nb2_conv2=weight_varible([64])\r\n\r\nh2_conv2=tf.nn.relu(conv2d(h2_pool1,W2_conv2)+b2_conv2)\r\nh2_pool2=max_pool_2x2(h2_conv2)\r\n\r\nW2_fc1=weight_varible([7*7*64,1024])\r\nb2_fc1=weight_varible([1024])\r\n\r\nh2_pool2_flat=tf.reshape(h2_pool2,[-1,7*7*64])\r\nh2_fc1=tf.nn.relu(tf.matmul(h2_pool2_flat,W2_fc1)+b2_fc1)\r\n\r\nkeep_prob=tf.placeholder(tf.float32)\r\nh2_fc1_drop=tf.nn.dropout(h2_fc1,keep_prob)\r\n\r\nW2_fc2=weight_varible([1024,10])\r\nb2_fc2=weight_varible([10])\r\n\r\ny2_=tf.placeholder(tf.float32,[None,10])\r\ny2_conv=tf.nn.softmax(tf.matmul(h2_fc1_drop,W2_fc2)+b2_fc2)\r\n\r\n\r\ncross_entropy=tf.reduce_sum(y2_*tf.log(y2_conv))\r\ntrain_step=tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)\r\ncorrect_prediction=tf.equal(tf.argmax(y2_conv,1),tf.argmax(y2_,1))\r\naccuracy=tf.reduce_mean(tf.cast(correct_prediction,tf.float32))\r\nsess.run(tf.initialize_all_variables())\r\n\r\n##########################################################\r\n\r\nfor i in range(20000):\r\n\tbatch=mnist.train.next_batch(50)\r\n\tif i%100==0:\r\n\t\ttrain_accuracy=accuracy.eval(feed_dict={x:batch[0],y_:batch[1],keep_prob:1})\r\n\t\tprint('step %d,train accuracy %g'%(i,train_accuracy))\r\n\ttrain_step.run([y_conv,y2_conv],feed_dict={x:batch[0],y_:batch[1],keep_prob:0.5})\r\nprint('test accuracy %g'%accuracy.eval(feed_dict={x:mnist.test.images,y_:mnist.test.labels,keep_prob:1.0}))","author":{"url":"https://github.com/FranNetty","@type":"Person","name":"FranNetty"},"datePublished":"2017-06-01T02:27:32.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":0},"url":"https://github.com/2/tensorflow_basic_tutorial/issues/2"}