2019年5月16日

摘要： import tensorflow as tf from tensorflow.examples.tutorials.mnist import input_data INPUT_NODE = 784 # 输入节点 OUTPUT_NODE = 10 # 输出节点 LAYER1_NODE = 500 # 隐藏层数 ... 阅读全文

摘要： import tensorflow as tf from tensorflow.examples.tutorials.mnist import input_data INPUT_NODE = 784 # 输入节点 OUTPUT_NODE = 10 # 输出节点 LAYER1_NODE = 500 # 隐藏层数 ... 阅读全文

摘要： import tensorflow as tf from tensorflow.python.framework import graph_util v1 = tf.Variable(tf.constant(1.0, shape=[1]), name = "v1") v2 = tf.Variable(tf.constant(2.0, shape=[1]), name = "v2") resul... 阅读全文

摘要： import tensorflow as tf v = tf.Variable(0, dtype=tf.float32, name="v") ema = tf.train.ExponentialMovingAverage(0.99) print(ema.variables_to_restore()) saver = tf.train.Saver({"v/ExponentialMovingAv... 阅读全文

摘要： import tensorflow as tf v = tf.Variable(0, dtype=tf.float32, name="v") for variables in tf.global_variables(): print(variables.name) ema = tf.train.ExponentialMovingAverage(0.99) maintain_... 阅读全文

摘要： import tensorflow as tf v1 = tf.Variable(tf.random_normal([1], stddev=1, seed=1)) v2 = tf.Variable(tf.random_normal([1], stddev=1, seed=1)) result = v1 + v2 init_op = tf.global_variables_initialize... 阅读全文

摘要： import tensorflow as tf with tf.variable_scope("foo"): v = tf.get_variable("v", [1], initializer=tf.constant_initializer(1.0)) #with tf.variable_scope("foo"): # v = t... 阅读全文

摘要： from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets("E:\\datasets\\MNIST_data\\", one_hot=True) print("Training data size: ", mnist.train.num_examples) pri... 阅读全文

摘要： import tensorflow as tf v1 = tf.Variable(0, dtype=tf.float32) step = tf.Variable(0, trainable=False) ema = tf.train.ExponentialMovingAverage(0.99, step) maintain_averages_op = ema.apply([v1]) with... 阅读全文

摘要： import tensorflow as tf import matplotlib.pyplot as plt import numpy as np data = [] label = [] np.random.seed(0) # 以原点为圆心，半径为1的圆把散点划分成红蓝两部分，并加入随机噪音。 for i in range(150): x1 = np.random.uniform... 阅读全文