Metadata-Version: 2.1
Name: vec2vec
Version: 0.0.3
Summary: vec2vec project
Home-page: https://github.com/pypa/sampleproject
Author: WangXiang
Author-email: xiangwangcn@163.com
License: UNKNOWN
Description: # vec2vec
        
        This repository provides a reference implementation of vec2vec, which can reduce the dimension to matrix.
        
        
        ### Requirements
        Before starting this project, you must install requirements below.
        
        ```
        faiss==1.7.0
        gensim==4.0.1
        networkx==2.6.2
        scikit-learn==0.24.2
        ```
        
        Note：It's recommended that using conda to install faiss, and conda version need to update.
        
        ```
        conda install faiss-cpu -c conda-forge
        ```
        
        ### Basic Usage
        
        1. To run *vec2vec*  by terminal, execute the following command from the project home directory:
           ```
           python ./vec2vec/main.py --input ./vec2vec/data/train.bow
           ```
           
           You can check out the other options available by using:
           ```
           python ./vec2vec/main.py  --help
           ```
        
        2. To run the vec2vec in your project, execute the following command:
        
           ```
           pip install vec2vec
           ```
        
        ### Input
        Refer to the ./vec2vec/data/train.bow in the project.
        
        ### Output
        The output are like below:
        
        	************* The number of num_walks is : 5 *******************
        	Matrix2vec p and q and topk: 1 1 10
        	The shape of the input matrix: (2000, 13155)
        	BuildNNGraphFromFAISS Finished in 0:00:03.305026 s.
        	The shape of the adjmatrix is: (2000, 2000)
        	Preprocess_transition_probs Finished in 0:00:00.902988 s.
        	Random Walk Finished in 0:00:00.590795 s.
        	Begin to train word2vec...
        	Model Matrix2vec Finished in 0:00:09.073013 s.
        	Accuracy：  [0.662 0.652 0.64  0.668]
        	Accuracy: 0.6555 (+/- 0.0212)
        
        ### Miscellaneous
        
        Please send any questions you might have about the code and/or the algorithm to xiangwangcn@163.com.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
