catamount | compute graph analysis tool to load construct | Machine Learning library

by baidu-research Python Version: ppopp-2019-artifact License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | catamount Summary

catamount is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. catamount has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Catamount is a compute graph analysis tool to load, construct, and modify deep learning models and to symbolically analyze their compute requirements.

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Quality

Security

License

Reuse

Support

catamount has a low active ecosystem.

It has 13 star(s) with 4 fork(s). There are 7 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 1 have been closed. On average issues are closed in 3 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of catamount is ppopp-2019-artifact

Quality

catamount has 0 bugs and 0 code smells.

Security

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

catamount code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

catamount 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

catamount releases are available to install and integrate.

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

Installation instructions, examples and code snippets are available.

catamount saves you 3237 person hours of effort in developing the same functionality from scratch.

It has 6956 lines of code, 616 functions and 53 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Propagate the shape of the wrapped slice
Returns a string representation of this operator
Return a list of dimensions
Set the value of the tensor
Reshape the shapes of the inputs
Tests if this dimension is a scalar
Return the number of elements
Calculate the minimal footprint subtree
Calculate footprint
Propagate the dimensions of the collective operation
Propagate shapes to the input tensors
Propagate shapes
Propagate the dimensions of the tensor
Propagate the shapes of the inputs
Propagate the shape of the ExpandDims operator
Propagate the shapes of the outputs
Calculate the algops op
Calculates the amount of alg bytes of the operation
Calculates the gradient op
Calculate the Alignop op
Propagate input shapes to output shape
Propagate the shape of the tensor
Propagate shapes to the input tensor
Create a split op
Propagate the shapes of the input tensor
Calculate the gradient of the gradients

Get all kandi verified functions for this library.

catamount Key Features

No Key Features are available at this moment for catamount.

catamount Examples and Code Snippets

No Code Snippets are available at this moment for catamount.

Community Discussions

Trending Discussions on catamount

Does machine learning framework caffe support different data type precisions?

Aggregate values by levels of another factor but keep all rows in R

AJAX form going to PHP script instead of submitting

QUESTION

Does machine learning framework caffe support different data type precisions?

Asked 2018-Aug-20 at 13:44

I am currently playing with the CaffeNet C++ image classification example. By default, this example using float. And here were the results I got:

...

ANSWER

Answered 2018-Aug-20 at 12:09

The mean file and the trained parameter you are using in the tutorial are stored in single precision values. Changing float to double in the program does not change the stored values, thus trying to read stored single-precision values as double-precision results with you reading "garbage". You'll have to manually convert the files to double precision values

Source https://stackoverflow.com/questions/51929852

QUESTION

Aggregate values by levels of another factor but keep all rows in R

Asked 2017-Aug-13 at 23:31

I have a dataframe in R with this structure:

...

ANSWER

Answered 2017-Aug-13 at 23:31

Usually, if you want to aggregate and keep the rows intact, ave can help. So, we use lapply to loop through the columns (except the first two) and use ave to calculate max value by SiteID

Source https://stackoverflow.com/questions/45665168

QUESTION

AJAX form going to PHP script instead of submitting

Asked 2017-Feb-17 at 23:11

I'm attempting to use AJAX to post a simple insert query to the database; however, I'm using a while loop to generate multiple PHP forms which seems to be causing problems. I use the same class for all the html forms, and I've been attempting to use the live function in AJAX but it doesn't seem to be working. I'm just wondering how to insert this data asynchronously.

Thanks for the help.

PHP

...

ANSWER

Answered 2017-Feb-17 at 23:11

This is all wrong:

Source https://stackoverflow.com/questions/42308891

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

Vulnerabilities

No vulnerabilities reported

Install catamount

Do you want to learn about the compute requirements of the deep learning models you're training or inferencing?.
WARNING: This may change currently installed packages (e.g., Tensorflow), which may cause backward compatibility issues. If you have previously-installed packages, we recommend installing these requirements manually (e.g., pip install <package> with no version requirements).
WARNING: This may change currently installed Tensorflow to a particular minimum version. If you have an older version installed already, you can try removing the version dependency in setup.py.

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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