keras-io | Keras documentation, hosted live at kerasio | Machine Learning library

by keras-team Jupyter Notebook Version: Current License: Apache-2.0

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kandi X-RAY | keras-io Summary

keras-io is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning applications. keras-io has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Keras documentation, hosted live at keras.io

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keras-io has a medium active ecosystem.

It has 2322 star(s) with 1861 fork(s). There are 50 watchers for this library.

It had no major release in the last 6 months.

There are 347 open issues and 151 have been closed. On average issues are closed in 110 days. There are 60 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of keras-io is current.

Quality

keras-io has no bugs reported.

Security

keras-io has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

keras-io is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

keras-io releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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keras-io Key Features

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keras-io Examples and Code Snippets

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Community Discussions

Trending Discussions on keras-io

Gradients are None while implementing GradCam

AttributeError: module 'transformers' has no attribute 'TFBertModel'

How to display Softmax highest probability

QUESTION

Gradients are None while implementing GradCam

Asked 2022-Mar-09 at 14:22

I am trying to implement grad-cam for a tensorflow 2.0 model (created using the keras-api), but the gradients returned from the tape are always None.

I am following the example given on https://keras.io/examples/vision/grad_cam/.

My model is fairly simple, but I swapped it out for the builtin Xception model provided by tf.keras.applications in order to debug (no difference in behavior, so the problem must be with my code).

...

ANSWER

Answered 2022-Mar-09 at 14:22

Like @AloneTogether mentionned, the result of argmax is not differentiable, thus the None result after applying tape.gradients(...) is normal, since no gradient can be computed.

While the result of argmax cannot be differentiated, it can be used to select the correct activation in the following way:

Source https://stackoverflow.com/questions/71399091

QUESTION

AttributeError: module 'transformers' has no attribute 'TFBertModel'

Asked 2021-Sep-06 at 03:34

My env is created by pycharm, it has the followings packages: tensorflow==1.13.0rc1, CUDA = 11 andcorresponding cudn.but run https://github.com/keras-team/keras-io/blob/master/examples/nlp/semantic_similarity_with_bert.py from 1 to 269 line,print(f"Strategy: {strategy}") model.summary() After execution, the following error is reported:

...

ANSWER

Answered 2021-Sep-06 at 03:34

Tensorflow 2.6.0 works

Source https://stackoverflow.com/questions/68936716

QUESTION

How to display Softmax highest probability

Asked 2021-Jun-21 at 01:19

I am running the following code. I am trying to display the probability of the predicted label next to the prediction but I have a hard time trying in doing so.

...

ANSWER

Answered 2021-Jun-20 at 16:43

I did not run the code, but I beleive preds variable will be having all the probabilities.

For a particular input that you are trying to predict, if you want to see the maximum prediction value, you can do max(pred).

Source https://stackoverflow.com/questions/68057861

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