with tf.variable_scope(scope): with tf.variable_scope('res1'): x = slim.conv2d(x_init, c, kernel_size=[3,3], stride=1, activation_fn = None) x = batch_norm(x) x = relu(x) with tf.variable_scope('res2'): x = slim
AI代码解释 defmixgenerator(x_init,c,org_pose,trg_pose):reuse=len([tfortintf.global_variables()ift.name.startswith('generator')])>0withtf.variable_scope('generator',reuse=reuse):org_pose=tf.cast(tf.reshape(org_pose,shape=[-1,1,1,org_pose.shape[-1]]),tf.float32)print(org_pose.sha...
rpn_select = tf.reshape(tf.where(tf.not_equal(rpn_labels, -1)), [-1]) rpn_cls_score = tf.reshape(tf.gather(rpn_cls_score, rpn_select), [-1, 2]) 选出那些label所对应的 ground_truth 对应的标签 函数接收的时候为所有的anchor对应的,针对label的赋值,来小批量的处理 rpn_labels = tf.re...
进行参数设置iftestImg.values():#用于dropout参数层dropout = 1#用于判断哪些参数不需要进行加载skip =[]#分类的类别数numClass = 1000#使用tf.placeholder进行x的输入参数初始化x = tf.placeholder(tf.float32, [1, 227
with tf.variable_scope(layername,reuse=None): # 权重和偏置都提前给一个初始值 Weights = tf.get_variable("weights",[in_size,out_size],initializer=tf.random_normal_initializer(stddev=0.1)) biases = tf.get_variable("biases",[out_size],initializer=tf.random_normal_initializer(mean=0.1,stddev=...
v1 = tf.get_variable("v", [1])print(v1.name) with tf.variable_scope("foo",reuse=True): v2= tf.get_variable("v", [1])print(v2.name) with tf.variable_scope("foo"): with tf.variable_scope("bar"): v3= tf.get_variable("v", [1])print(v3.name) ...
with tf.variable_scope('eval_net'): e1 =
2019-12-04 21:04 − tf.name_scope() 在 Tensorflow 当中有两种途径生成变量 variable, 一种是 tf.get_variable(), 另一种是 tf.Variable(). 如果在 tf.name_scope() 的框架下使用这两种方... blueattack 0 508 java.sql.SQLException: Unknown system variable 'query_cache_size' 2019-12-24...
tf.Graph().as_default():sess = tf.Session()with sess.as_default():initializer = tf.contrib.layers.xavier_initializer()with tf.variable_scope("model", reuse=None, initializer=initializer):m = network.GRU(is_training=True, word_embeddings=wordembedding, settings=settings)global_step = tf....
tf.summary.FileWriter类用于在目录中创建事件文件,并且向文件中添加摘要和事件,用来在TensorBoard中展示。 变量作用域 在TensorFlow中有两个作用域(scope),一个是name_scope,另一个是variable_scope。它们究竟有什么区别呢?简而言之,variable_scope主要是给variable_name加前缀,也可以给op_name加前缀:name_scope是给...