tf.keras.activations.serialize（十一）

TF.Keras序列化激活函数

最新推荐文章于 2021-08-17 09:53:30 发布

TJMtaotao

最新推荐文章于 2021-08-17 09:53:30 发布

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本文介绍tf.keras.activations.serialize函数，该函数用于将Keras的激活函数序列化为字符串形式，便于保存和传递。这是TensorFlow中Keras模块的一部分，主要应用于神经网络模型的构建和训练过程中。

tf.keras.activations.serialize

tf.keras.activations.serialize(activation)

Defined in tensorflow/python/keras/activations.py.

@tf_export('keras.activations.serialize')
	def serialize(activation):
	return activation.__name__

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$(selector).serialize() 只会将”成功的控件“序列化为字符串。如果不使用按钮来提交表单，则不对提交按钮的值序列化。如果要表单元素的值包含到序列字符串中，元素必须使用 name 属性。如下图片，当checkbox未选中时，此序列化值不能拼成字符串，只有在选中的时候才能序列化为字符串 ...

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当我在jupyter notebook中运行#tokenization from keras.preprocessing.text import Tokenizer num_words = 10000 tokenizer = Tokenizer(num_words=num_words) tokenizer.fit_on_texts(x) xtokens= tokenizer.texts_to_sequences(x)出现--------------------------------------------------------------------------- ImportError Traceback (most recent call last) Cell In[79], line 3 1 #tokenization ----> 3 from keras.preprocessing.text import Tokenizer 4 num_words = 10000 5 tokenizer = Tokenizer(num_words=num_words) File D:\tool\anaconda3\envs\li\Lib\site-packages\keras\__init__.py:2 1 # DO NOT EDIT. Generated by api_gen.sh ----> 2 from keras.api import DTypePolicy 3 from keras.api import FloatDTypePolicy 4 from keras.api import Function File D:\tool\anaconda3\envs\li\Lib\site-packages\keras\api\__init__.py:8 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 8 from keras.api import activations 9 from keras.api import applications 10 from keras.api import backend File D:\tool\anaconda3\envs\li\Lib\site-packages\keras\api\activations\__init__.py:7 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 7 from keras.src.activations import deserialize 8 from keras.src.activations import get 9 from keras.src.activations import serialize File D:\tool\anaconda3\envs\li\Lib\site-packages\keras\src\__init__.py:1 ----> 1 from keras.src import activations 2 from keras.src import applications 3 from keras.src import backend File D:\tool\anaconda3\envs\li\Lib\site-packages\keras\src\activations\__init__.py:3 1 import types ----> 3 from keras.src.activations.activations import celu 4 from keras.src.activations.activations import elu 5 from keras.src.activations.act

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tokenizer = tf.keras.preprocessing.text.Tokenizer(num_words=1000) sequences = tokenizer.texts_to_sequences(['hello world', 'this is a test']) print(sequences) ``` 以上样例利用了 TensorFlow 内嵌支持而...

--------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 1 ----> 1 from keras.datasets import imdb 3 # 加载IMDB数据集（保留最常见的20,000词） 4 max_features = 20000 File A:\anaconda\Lib\site-packages\keras\__init__.py:7 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 7 from keras import _tf_keras as _tf_keras 8 from keras import activations as activations 9 from keras import applications as applications File A:\anaconda\Lib\site-packages\keras\_tf_keras\__init__.py:1 ----> 1 from keras._tf_keras import keras File A:\anaconda\Lib\site-packages\keras\_tf_keras\keras\__init__.py:7 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 7 from keras import activations as activations 8 from keras import applications as applications 9 from keras import callbacks as callbacks File A:\anaconda\Lib\site-packages\keras\activations\__init__.py:7 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 7 from keras.src.activations import deserialize as deserialize 8 from keras.src.activations import get as get 9 from keras.src.activations import serialize as serialize File A:\anaconda\Lib\site-packages\keras\src\__init__.py:1 ----> 1 from keras.src import activations 2 from keras.src import applications 3 from keras.src import backend File A:\anaconda\Lib\site-packages\keras\src\activations\__init__.py:3 1 import types ----> 3 from keras.src.activations.activations import celu 4 from keras.src.activations.activations import elu 5 from keras.src.activations.activations import exponential File A:\anaconda\Lib\site-packages\keras\src\activations\activations.py:1 ----> 1 from keras.src import backend 2 from keras.src import ops 3 from keras.src.api_export import keras_export File A:\anaconda\Lib\site-packages\keras\src\backend\__init__.py:10 7 import torch 9 from keras.src.api_export import keras_export ---> 10 from keras.src.backend.common.dtypes import result_type 11 from keras.src.backend.common.keras_tensor import KerasTensor 12 from keras.src.backend.common.keras_tensor import any_symbolic_tensors File A:\anaconda\Lib\site-packages\keras\src\backend\common\__init__.py:2 1 from keras.src.backend.common import backend_utils ----> 2 from keras.src.backend.common.dtypes import result_type 3 from keras.src.backend.common.variables import AutocastScope 4 from keras.src.backend.common.variables import Variable as KerasVariable File A:\anaconda\Lib\site-packages\keras\src\backend\common\dtypes.py:5 3 from keras.src.api_export import keras_export 4 from keras.src.backend import config ----> 5 from keras.src.backend.common.variables import standardize_dtype 7 BOOL_TYPES = ("bool",) 8 INT_TYPES = ( 9 "uint8", 10 "uint16", (...) 16 "int64", 17 ) File A:\anaconda\Lib\site-packages\keras\src\backend\common\variables.py:11 9 from keras.src.backend.common.stateless_scope import get_stateless_scope 10 from keras.src.backend.common.stateless_scope import in_stateless_scope ---> 11 from keras.src.utils.module_utils import tensorflow as tf 12 from keras.src.utils.naming import auto_name 15 class Variable: File A:\anaconda\Lib\site-packages\keras\src\utils\__init__.py:1 ----> 1 from keras.src.utils.audio_dataset_utils import audio_dataset_from_directory 2 from keras.src.utils.dataset_utils import split_dataset 3 from keras.src.utils.file_utils import get_file File A:\anaconda\Lib\site-packages\keras\src\utils\audio_dataset_utils.py:4 1 import numpy as np 3 from keras.src.api_export import keras_export ----> 4 from keras.src.utils import dataset_utils 5 from keras.src.utils.module_utils import tensorflow as tf 6 from keras.src.utils.module_utils import tensorflow_io as tfio File A:\anaconda\Lib\site-packages\keras\src\utils\dataset_utils.py:9 5 from multiprocessing.pool import ThreadPool 7 import numpy as np ----> 9 from keras.src import tree 10 from keras.src.api_export import keras_export 11 from keras.src.utils import io_utils File A:\anaconda\Lib\site-packages\keras\src\tree\__init__.py:1 ----> 1 from keras.src.tree.tree_api import assert_same_paths 2 from keras.src.tree.tree_api import assert_same_structure 3 from keras.src.tree.tree_api import flatten File A:\anaconda\Lib\site-packages\keras\src\tree\tree_api.py:8 5 from keras.src.utils.module_utils import optree 7 if optree.available: ----> 8 from keras.src.tree import optree_impl as tree_impl 9 elif dmtree.available: 10 from keras.src.tree import dmtree_impl as tree_impl File A:\anaconda\Lib\site-packages\keras\src\tree\optree_impl.py:13 11 # Register backend-specific node classes 12 if backend() == "tensorflow": ---> 13 from tensorflow.python.trackable.data_structures import ListWrapper 14 from tensorflow.python.trackable.data_structures import _DictWrapper 16 try: File A:\anaconda\Lib\site-packages\tensorflow\__init__.py:55 53 from tensorflow._api.v2 import autograph 54 from tensorflow._api.v2 import bitwise ---> 55 from tensorflow._api.v2 import compat 56 from tensorflow._api.v2 import config 57 from tensorflow._api.v2 import data File A:\anaconda\Lib\site-packages\tensorflow\_api\v2\compat\__init__.py:8 3 """Public API for tf._api.v2.compat namespace 4 """ 6 import sys as _sys ----> 8 from tensorflow._api.v2.compat import v1 9 from tensorflow._api.v2.compat import v2 10 from tensorflow.python.compat.compat import forward_compatibility_horizon # line: 125 File A:\anaconda\Lib\site-packages\tensorflow\_api\v2\compat\v1\__init__.py:30 28 from tensorflow._api.v2.compat.v1 import autograph 29 from tensorflow._api.v2.compat.v1 import bitwise ---> 30 from tensorflow._api.v2.compat.v1 import compat 31 from tensorflow._api.v2.compat.v1 import config 32 from tensorflow._api.v2.compat.v1 import data File A:\anaconda\Lib\site-packages\tensorflow\_api\v2\compat\v1\compat\__init__.py:8 3 """Public API for tf._api.v2.compat namespace 4 """ 6 import sys as _sys ----> 8 from tensorflow._api.v2.compat.v1.compat import v1 9 from tensorflow._api.v2.compat.v1.compat import v2 10 from tensorflow.python.compat.compat import forward_compatibility_horizon # line: 125 File A:\anaconda\Lib\site-packages\tensorflow\_api\v2\compat\v1\compat\v1\__init__.py:32 30 from tensorflow._api.v2.compat.v1 import compat 31 from tensorflow._api.v2.compat.v1 import config ---> 32 from tensorflow._api.v2.compat.v1 import data 33 from tensorflow._api.v2.compat.v1 import debugging 34 from tensorflow._api.v2.compat.v1 import distribute File A:\anaconda\Lib\site-packages\tensorflow\_api\v2\compat\v1\data\__init__.py:8 3 """Public API for tf._api.v2.data namespace 4 """ 6 import sys as _sys ----> 8 from tensorflow._api.v2.compat.v1.data import experimental 9 from tensorflow.python.data.ops.dataset_ops import AUTOTUNE # line: 103 10 from tensorflow.python.data.ops.dataset_ops import DatasetV1 as Dataset # line: 3710 File A:\anaconda\Lib\site-packages\tensorflow\_api\v2\compat\v1\data\experimental\__init__.py:32 30 from tensorflow.python.data.experimental.ops.interleave_ops import parallel_interleave # line: 29 31 from tensorflow.python.data.experimental.ops.interleave_ops import sample_from_datasets_v1 as sample_from_datasets # 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