h5cat | Quick preview of HDF5 files on the command line

by jni Python Version: 0.1 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | h5cat Summary

h5cat is a Python library. h5cat has no bugs, it has no vulnerabilities, it has build file available and it has low support. However h5cat has a Non-SPDX License. You can install using 'pip install h5cat' or download it from GitHub, PyPI.

h5cat is a Python script to quickly preview the contents of an HDF5 file. It is designed to be used in situations where hdfview is overkill. It is distributed under the open-source MIT license.

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Support

h5cat has a low active ecosystem.

It has 10 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 2 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of h5cat is 0.1

Quality

h5cat has 0 bugs and 0 code smells.

Security

h5cat has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

h5cat code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

h5cat has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

h5cat releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

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

Top functions reviewed by kandi - BETA

kandi has reviewed h5cat and discovered the below as its top functions. This is intended to give you an instant insight into h5cat implemented functionality, and help decide if they suit your requirements.

Preview the contents of an HDF5 file .

Get all kandi verified functions for this library.

h5cat Key Features

No Key Features are available at this moment for h5cat.

h5cat Examples and Code Snippets

No Code Snippets are available at this moment for h5cat.

Community Discussions

Trending Discussions on h5cat

Using Keras, How can I load weights generated from CuDNNLSTM into LSTM Model?

QUESTION

Using Keras, How can I load weights generated from CuDNNLSTM into LSTM Model?

Asked 2020-Jan-04 at 20:54

I've developed a NN Model with Keras, based on the LSTM Layer. In order to increase speed on Paperspace (a GPU Cloud processing infrastructure), I've switched the LSTM Layer with the new CuDNNLSTM Layer. However this is usable only on machines with GPU cuDNN support. PS: CuDNNLSTM is available only on Keras master, not in the latest release.

So I've generated the weights and saved them to hdf5 format on the Cloud, and I'd like to use them locally on my MacBook. Since CuDNNLSTM layer is not available, only for my local installation I've switched back to LSTM.

Reading this tweet about CuDNN from @fchollet I thought it would work just fine, simply reading the weights back into the LSTM model.

However, when I try to import them Keras is throwing this error:

...

ANSWER

Answered 2017-Nov-01 at 19:48

The reason is that the CuDNNLSTM layer has a bias twice as large as that of LSTM. It's because of the underlying implementation of cuDNN API. You can compare the following equations (copied from cuDNN user's guide) to the usual LSTM equations:

CuDNN uses two bias terms, so the number of bias weights is doubled. To convert it back to what LSTM uses, the two bias terms need to be summed.

I've submitted a PR to do the conversion and it's merged. You can install the latest Keras from GitHub and the problem in weight loading should be solved.

Source https://stackoverflow.com/questions/47003418

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install h5cat

You can install using 'pip install h5cat' or download it from GitHub, PyPI.
You can use h5cat like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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