model-analysis | Model analysis tools for TensorFlow | Analytics library

by tensorflow Python Version: v0.44.0 License: Apache-2.0

X-Ray Key Features Code Snippets(4)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | model-analysis Summary

model-analysis is a Python library typically used in Analytics, Tensorflow applications. model-analysis has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install model-analysis' or download it from GitHub, PyPI.

TensorFlow Model Analysis (TFMA) is a library for evaluating TensorFlow models. It allows users to evaluate their models on large amounts of data in a distributed manner, using the same metrics defined in their trainer. These metrics can be computed over different slices of data and visualized in Jupyter notebooks. Caution: TFMA may introduce backwards incompatible changes before version 1.0.

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Quality

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Support

model-analysis has a medium active ecosystem.

It has 1203 star(s) with 266 fork(s). There are 74 watchers for this library.

It had no major release in the last 12 months.

There are 20 open issues and 51 have been closed. On average issues are closed in 219 days. There are 12 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of model-analysis is v0.44.0

Quality

model-analysis has 0 bugs and 0 code smells.

Security

model-analysis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

model-analysis code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

model-analysis 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

model-analysis releases are available to install and integrate.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Convert input to a label prediction example .
Calculate binary confusion matrix .
Flip the counterfactogram .
Generate a prediction .
Computes precision and recall at the given cutoff .
Validate and return a validation result .
Extracts evaluation and write results .
Return the default extractors .
Writes metrics and validations .
Converts a list of MetricMetations into a list of Tensors .

Get all kandi verified functions for this library.

model-analysis Key Features

No Key Features are available at this moment for model-analysis.

model-analysis Examples and Code Snippets

Output

Python

Lines of Code : 31

License : Strong Copyleft (GPL-3.0)

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output/
└── 'model'
    ├── 'phenotype'
    │   ├── QQ
    │   │   └── QQ plot figure (.png)
    │   ├── summary file (.txt)
    │   ├── GEMMA output file (.txt)
    │   ├── GEMMA log file (.txt)
    │   ├── best_p-values
    │   │   ├── top 1% varia

mLAMA: multilingual LAnguage Model Analysis,Reference:

Python

Lines of Code : 17

License : No License

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@inproceedings{kassner2021multilingual,
    title = "Multilingual {LAMA}: Investigating Knowledge in Multilingual Pretrained Language Models",
    author = {Kassner, Nora  and
      Dufter, Philipp  and
      Sch{\"u}tze, Hinrich},
    booktitle = "t

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis,Getting Started,Training and evaluation

Jupyter Notebook

Lines of Code : 16

License : Permissive (Apache-2.0)

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CUDA_VISIBLE_DEVICES=0 python3 train.py \
--train_data data_lmdb_release/training --valid_data data_lmdb_release/validation \
--select_data MJ-ST --batch_ratio 0.5-0.5 \
--Transformation None --FeatureExtraction VGG --SequenceModeling BiLSTM --Predic

how to fix "Command errored out with exit status 1"

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

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pip install pymodels

Community Discussions

Trending Discussions on model-analysis

'extras_require' must be a dictionary whose values are strings or lists of strings containing valid project/version requirement specifiers

QUESTION

'extras_require' must be a dictionary whose values are strings or lists of strings containing valid project/version requirement specifiers

Asked 2020-Dec-17 at 18:42

I have a setup.py which contains the following:

...

ANSWER

Answered 2020-Sep-01 at 13:41

You can only use PEP 508 - Dependency specification for Python Software Packages requirements. git://github.com/BioGeek/tta_wrapper.git@master#egg=tta_wrapper is not valid syntax according to that standard.

setuptools does accept the name@ url direct reference syntax:

Source https://stackoverflow.com/questions/63687990

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

Vulnerabilities

No vulnerabilities reported

Install model-analysis

The recommended way to install TFMA is using the PyPI package:. pip install from https://pypi-nightly.tensorflow.org.
To build from source follow the following steps:. Install the protoc as per the link mentioned: protoc. Create a virtual environment by running the commands. This will build the TFMA wheel in the dist directory. To install the wheel from dist directory run the commands.
For instructions on using TFMA, see the get started guide.