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1 Answer1. Active Oldest Votes. 2. This is a compatibility issue between tensorflow 1.x and tensorflow 2.x. In other words, the syntax that you wrote works fine with tensorflow 1.x. But as you mentioned, you're using tensorflow 2.2 which is incompatible. So, you have can solve this issue by either one of the following two options:

Jun 14, 2018 · as a side note upgrading to version 1.4 is not enough because then we get: AttributeError: 'Iterator' object has no attribute '_output_classes' as in #66 where it is stated that tensorflow version 1.7 is mandatory. actually using tensorflow 1.8. also seems to work just fine.

11.12.2019 · AttributeError: module 'tensorflow' has no attribute 'sparse_placeholder' 色々調べた結果，tensorflowのバージョンの違いが原因と考えられるのですが，そういう場合はどうすればこのエラーを解決することができますか？

distributions module: Core module for TensorFlow distribution objects and helpers. Try to replace TensorFlowDNNClassifier with just DNNClassifier.

Jul 28, 2019 · Ubuntu 18.04 LTS clean install and fully updated, after a pip3 install of tensorflow-gpu and install of blocksparse from source I am getting the following error: Python 3.6.8 (default, Jan 14 2019, 11:02:34) [GCC 8.0.1 20180414 (experime...

08.07.2020 · module ‘tensorflow’ has no attribute ‘sparse_to_dense’ tensorflow2.0中把 sparse_to_dense去掉了 可以使用下面两个函数替代 1、先构造SparseTensor tf.sparse.SparseTensor() 2、再将Sparse Tensor转Dense tf.sparse.to_dense() 合在一起 sp...

08.09.2020 · How to resolve: AttributeError: module ‘tensorflow’ has no attribute ‘placeholder’ less than 1 minute read On this page. Issue; Solution 1: to follow the update scheme of Tensorflow 2.0; Solution 2: to use compatibility mode; Issue

30.11.2021 · ConfigProto disappeared in tf 2.0, so an elegant solution is: import tensorflow as tf. Python. import tensorflow as tf. . and then replace: tf.ConfigProto by tf.compat.v1.ConfigProto. In fact, the compatibility built in 2.0 to get tf 1.XX: tf.compat.v1 is really helpful.

06.07.2021 · Hello Guys How Are You All ? Hope You all are fine. Today I Have Faced How to AttributeError: module ‘tensorflow_core.compat.v1’ has no attribute ‘contrib’ In Python.How to AttributeError: module ‘tensorflow_core.compat.v1’ has no attribute ‘contrib’ So Here I am Explain to you all the possible solutions Here.

Apr 19, 2019 · AttributeError: module 'scipy' has no attribute 'sparse' in sklearn/utils/fixes.py #13678 Closed TatianaParshina opened this issue Apr 19, 2019 · 9 comments

Dec 13, 2019 · 1. This answer is not useful. Show activity on this post. If you know the exact line where tf.log is, replace it with tf.math.log. if not, you can use this guide to Automatically upgrade code to TensorFlow 2. Share. Follow this answer to receive notifications. answered Aug 1 '20 at 6:55. hossein hayati.

Nov 30, 2021 · ConfigProto disappeared in tf 2.0, so an elegant solution is: import tensorflow as tf. Python. import tensorflow as tf. . and then replace: tf.ConfigProto by tf.compat.v1.ConfigProto. In fact, the compatibility built in 2.0 to get tf 1.XX: tf.compat.v1 is really helpful.

Hi guys, I had to upgrade my tensorflow to re-install diffxpy and this seems to have broken my scGen: I've got the AttributeError: module ...

Nov 05, 2021 · The only time ordering can be violated is during manual manipulation of the indices and values to add entries. Reordering does not affect the shape of the SparseTensor. For example, if sp_input has shape [4, 5] and indices / values: [0, 3]: b [0, 1]: a [3, 1]: d [2, 0]: c. then the output will be a SparseTensor of shape [4, 5] and indices / values:

module 'tensorflow' has no attribute 'sparse_to_dense'tensorflow2.0中把sparse_to_dense去掉了可以使用下面两个函数替代1、先 ...

AttributeError: module 'tensorflow._api.v2.sets' has no attribute 'set_intersection',@SalahRahimi, Thank you for the update.

I have used the following code and my problem has resolved . import tensorflow.compat.v1 as tf tf.disable_v2_behavior().

If you have separate indices , values , and dense_shape tensors, wrap them in a SparseTensor object before passing to the ops below.

22.12.2021 · AttributeError: module 'setuptools._distutils' has no attribute 'version'. These are the versions I’m using: python 3.9.9 tensorboard 2.6.0 pytorch 1.10.0 tensorflow-deps 2.7.0 tensorflow-estimator 2.7.0 tensorflow-macos 2.7.0 tensorflow-metal 0.3.0

01.07.2019 · That is： AttributeError: module 'tensorflow.python.keras.api._v2.keras.backend' has no attribute 'set_image_dim_ordering' And I don't know what to do now #Here are some codes which are related to the problem above.

07.11.2019 · Fix AttributeError: module ‘tensorflow’ has no attribute ‘AUTO_REUSE’ – TensorFlow Tutorial

So I managed to fix the issue. There are two solutions. Either you manually change all the bits of code that needs to be updated from v1 to v2 in the model.py file such as tf.log to tf.math.log but you will need to do it for every single issue that is raised after (which is a pain).. Or you can create a separate environment with TensorFlow version 1.13.1 and keras 2.1.0.

28.07.2019 · Ubuntu 18.04 LTS clean install and fully updated, after a pip3 install of tensorflow-gpu and install of blocksparse from source I am getting the following error: Python 3.6.8 (default, Jan 14 2019, 11:02:34) [GCC 8.0.1 20180414 (experime...