tensorflow import keras import matplotlib.pyplot as plt from tensorflow.keras import layers import tensorflow_addons...as tfa %matplotlib inline 这里使用了TensorFlow_addons模块,它实现了核心 TensorFlow 中未提供的新功能。...tensorflow_addons的安装要注意与tf的版本对应关系,请参考: https://github.com/tensorflow/addons。
pip install tensorflow-addons 要在Python代码中使用TensorFlow-addons,您只需导入包: import tensorflow as tf import tensorflow_addons
这里需要注意的一点是,keras的API中并没有像PyTorch的API中的这个参数group,这样的话,就无法衍生成GN和InstanceN层了,在之后的内容,会在Tensorflow_Addons库中介绍
重大更改 tf.contrib 目前已经完全被移除了,它里面的各种 API 要么移植到了 TensorFlow 的核心 API、要么移到了独立的第三方库 tensorflow_addons、或者完全移除了
other = LooseVersion(other) /opt/bdp/data01/anaconda3/envs/rasa/lib/python3.8/site-packages/tensorflow_addons...other = LooseVersion(other) /opt/bdp/data01/anaconda3/envs/rasa/lib/python3.8/site-packages/tensorflow_addons
代码地址: https://github.com/tensorflow/addons/blob/master/tensorflow_addons/optimizers/lamb.py 引言 随着大规模数据集的出现
38253797/article/details/116292496 TF implementation https://github.com/tensorflow/addons/blob/v0.7.1/tensorflow_addons...for gradient stability # TF implementation https://github.com/tensorflow/addons/blob/v0.7.1/tensorflow_addons
from tensorflow.keras import layers import tensorflow_hub as hub import tensorflow_text as text import tensorflow_addons
pandas as pdimport tensorflow as tffrom tensorflow import kerasfrom tensorflow.keras import layersimport tensorflow_addons
例如,下面的代码创建了一个基本的编码器-解码器模型,相似于图16-3: import tensorflow_addons as tfa encoder_inputs = keras.layers.Input
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