eucl_dist | Euclidean Distance Computation in Python | GPU library

by droyed Python Version: Current License: LGPL-3.0

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | eucl_dist Summary

eucl_dist is a Python library typically used in Hardware, GPU, Deep Learning, Pytorch applications. eucl_dist has no bugs, it has no vulnerabilities, it has a Weak Copyleft License and it has low support. However eucl_dist build file is not available. You can download it from GitHub.

There are two parts to the codebase - CPU and GPU based codes that as the names suggest, broadly speaking process the data on CPU and GPU respectively. The proposed method uses matrix-multiplication for better performance. With CPU implementations, we have two options - OpenBLAS or MKL to perform those matrix-multiplications. With GPU implementations, mainly we are leveraging CUBLAS to perform those matrix-multiplications. With most of the GPU implemenations presented in the codebase, we have the option to keep the final output on GPU to handle further compute heavy operations. This give us two options with GPU as well - keeping data on GPU or bringing it back to CPU host. Thus, considering both CPU and GPU implementations, there are four possibilities by which euclidean distances could be computed. There are few factors at play depending on the input data and output requirements that lets us propose different configurations for each of those four ways.

Support

Quality

Security

License

Reuse

Support

eucl_dist has a low active ecosystem.

It has 48 star(s) with 4 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 2 have been closed. On average issues are closed in 13 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of eucl_dist is current.

Quality

eucl_dist has 0 bugs and 33 code smells.

Security

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

eucl_dist code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

eucl_dist is licensed under the LGPL-3.0 License. This license is Weak Copyleft.

Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.

Reuse

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

eucl_dist has no build file. You will be need to create the build yourself to build the component from source.

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

eucl_dist saves you 162 person hours of effort in developing the same functionality from scratch.

It has 403 lines of code, 19 functions and 11 files.

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

Top functions reviewed by kandi - BETA

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

Compute the Euclidean distance between two arrays
Compute the squared squared sum between two arrays
Add two NumPy arrays
Extract a 2d array of two arrays
R Compute the distance between two matrices
Compute the sum of two arrays
Compute the dot product of two arrays
Compute squared sum of two arrays
Return the output dtype for a and b
Compute the squared sum of two arrays
Add vectors from GPU to GPU
Compute the dtype between two arrays
Return a GEMM function
Distance between two arrays
Convert to float32
Load data from a npy file

Get all kandi verified functions for this library.

eucl_dist Key Features

No Key Features are available at this moment for eucl_dist.

eucl_dist Examples and Code Snippets

No Code Snippets are available at this moment for eucl_dist.

Community Discussions

Trending Discussions on eucl_dist

Processing data in text files

Colab Failed (How) to import files from git

Finetuning DNN with continuous outputs in the last layer

Using purrr (tidyverse) to map distance function across all columns of dataframe

QUESTION

Processing data in text files

Asked 2020-Nov-14 at 15:34

I have multiple text file in a directory. Each of these files contains 7 columns and 20 rows. The last column has 0 values in all rows at the beginning. What i want to do is: I want to use the first three column of each txt file (line by line) to make some calćulation and store the result in the 7th column respectively line by line. To clarify the structure of one txt file:

...

ANSWER

Answered 2020-Nov-14 at 15:34

Put your code in a function and make the function accept the path as argument, then call the function in a for loop iterating over the list of files.

E.g.:

Source https://stackoverflow.com/questions/64829605

QUESTION

Colab Failed (How) to import files from git

Asked 2020-Aug-29 at 16:15

I am new to using Colab and cannot find anything to make it work. Could anybody help me fix it or share a solution?

...

ANSWER

Answered 2020-Aug-29 at 08:14

There is subfolder named 'eucl_dist' under 'eucl_dist' again.

So, you have to access './eucl_dist/eucl_dist/gpu_dist'

Try this one.

Source https://stackoverflow.com/questions/63642350

QUESTION

Finetuning DNN with continuous outputs in the last layer

Asked 2017-Dec-27 at 16:06

Greatly appreciate it if someone could help me out here:

I'm trying to do some finetuning on a regression task --- my inputs are 200X200 RGB images and my prediction output/label is a set of real values (let's say, within [0,10], though scaling is not a big deal here...?) --- on top of InceptionV3 architecture. Here are my functions that take a pretrained Inception model, remove the last layer and add a a new layer, set up for finetuning...

...

ANSWER

Answered 2017-Dec-27 at 12:26

Your output shape for the lambda layer is wrong. Define your functions like this:

Source https://stackoverflow.com/questions/47985005

QUESTION

Using purrr (tidyverse) to map distance function across all columns of dataframe

Asked 2017-Oct-10 at 23:28

I have a distance function which takes in 2 (numeric) vectors and calculates the distance between them.

For a given dataframe (mtcars_raw) in the example below and a fixed input vector (test_vec) I would like to calculate the pairwise distances (i.e. apply the distance function) to each column and test_vec and return the vector of distances. The length of the vector should be the number of columns.

Please see the reproducible example:

...

ANSWER

Answered 2017-Oct-10 at 23:28

Use map_dbl, which is a special case of map to loop through columns but explicitly return double type vector:

Source https://stackoverflow.com/questions/46677286

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

Vulnerabilities

No vulnerabilities reported

Install eucl_dist

You can download it from GitHub.
You can use eucl_dist 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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