ustbbsy的博客

来源：The Functional APIShared layersAnother good use for the functional API are models that use shared layers. Shared layers are layer instances that are reused multiple times in the same model -- they learn features that correspond to multiple paths in

tf.strings.splitlines = tf.strings.split(line, '\n')输入是list格式输出是一个SparseTensorValue对象SparseTensorValue(indices,values=array( ,dtype),dense_shape)拿结果lines.values

eager模式import tensorflow as tfimport tensorflow.contrib.eager as tfetfe.enable_eager_execution()# 读hdfs# file_base_path="hdfs:///****"# files = tf.io.gfile.glob(file_base_path)# 读本地文件files = [os.path.join(path, f) for f in os.listdir(path)]d

tensorflow读取hdfs数据设置classpath变量直接执行如下脚本test.pyimport tensorflow as tf file_path = "hdfs:///a/b/.csv"files = tf.io.gfile.glob(file_path)print(files)1、shell中这样运行CLASSPATH=$($HADOOP_HDFS_HOME/bin/hadoop classpath --glob) python test.py2、.bashr

tf.keras.layers.BatchNormalization批归一化 批标准化tf.keras.layers.BatchNormalization( axis=-1, momentum=0.99, epsilon=0.001, center=True, scale=True, beta_initializer='zeros', gamma_initializer='ones', moving_mean_initializer='zeros', moving_

自定义Layertf.keras.layers.Layer 是所有 Keras 层的基类，它继承自 tf.Module。定义call 您只需换出父项，然后将 __call__ 更改为 call 即可将模块转换为 Keras 层定义build 定义输入的shape.build 仅被调用一次，而且是使用输入形状时调用的。它通常用于创建变量（权重）import tensorflow as tfclass MyLayer(tf.keras.layers.Layer): ...

tensorflow变量初始化