Package Health Score

66 / 100

security
No known security issues
popularity
Limited
maintenance
Healthy
community
Limited

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noir
48

Popularity

Limited

GitHub Stars: 9
Forks: 3
Contributors: 20

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package nnoir-onnx, we found that it has been starred 9 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 27, 2024
Direct Vulnerabilities: 0
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0
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0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
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0
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License Risk: 0
H
0
M
0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 0
Open PR: 7
Last Release: 22 days ago
Last Commit: 24 days ago

Further analysis of the maintenance status of nnoir-onnx based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that nnoir-onnx demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 20
Funding: No

With more than 10 contributors for the nnoir-onnx repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: <4.0,>=3.9

Age: 6 years
Latest Release: 22 days ago
Dependencies: 0 Direct
Versions: 23
Maintainers: 0
Wheels: OS Independent

Readme

nnoir-onnx

nnoir-onnx is a converter from ONNX model to NNOIR model.

Install

From PyPI:

pip install nnoir-onnx

From Dockerhub:

docker pull idein/nnoir-tools:20240208

Example

wget https://www.cntk.ai/OnnxModels/mnist/opset_7/mnist.tar.gz
tar xvzf mnist.tar.gz
onnx2nnoir -o model.nnoir mnist/model.onnx

With docker:

docker run --rm -it -u $UID:$GID -v $(pwd):/work idein/nnoir-tools:20240208 onnx2nnoir --graph_name "mobilenet" -o mobilenetv2-1.0.nnoir mobilenetv2-1.0.onnx

Supported ONNX Operators

Add
AveragePool
BatchNormalization
- scale, B, mean, and var must be "constant"
Clip
- must be opset version 6 or 11
- if opset version is 11
  - max must be "constant"
- min must be 0
Concat
Conv
- W must be Constant value or have initializer value
- b must be Constant value or have initializer value
Cos
Div
- 1st input must not be "constant"
Dropout
- equivalent identity function
Elu
Exp
Flatten
Gemm
- B must be Constant value or have initializer value
- C must be Constant value or have initializer value
GlobalAveragePool
HardSigmoid
HardSwish
LeakyRelu
LRN
LSTM
- only seq_length == 1
- direction must be forward
- Supported activations are below
  - Sigmoid
  - Tanh
  - Relu
- Not support clip and input_forget
MatMul
MaxPool
- ceil_mode = 1 is not supported
- dilations must be array of 1.
Mul
Pad
- mode must be "constant"
Pow
- 2nd input must be 2.0
PRelu
- slope must be "constant" and a single value tensor
ReduceMean
ReduceSum
Relu
Reshape
Resize
- must be from opset version >= 11
- mode must be "linear" or "nearest"
- nearest_mode must be "floor"
- coordinate_transformation_mode must be either "pytorch_half_pixel" or "align_corners" for "linear" mode
- coordinate_transformation_mode must be either "asymmetric" for "nearest" mode
Sigmoid
Sin
Slice
- must be from opset version >= 10
- starts must be Constant value or have initializer value
- ends must be Constant value or have initializer value
- axes must be Constant value or have initializer value
- steps is not supported
Softmax
Split
Sqrt
Squeeze
Sub
Sum
- 2 inputs
Tan
Tanh
Transpose
Unsqueeze
Where
- condition must be Constant value
- condition must all true or all false
- the input value not selected must be constant

FAQs

What is nnoir-onnx?

ONNX to NNOIR Converter. Visit Snyk Advisor to see a full health score report for nnoir-onnx, including popularity, security, maintenance & community analysis.

Is nnoir-onnx popular?

The python package nnoir-onnx receives a total of 253 weekly downloads. As such, nnoir-onnx popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is nnoir-onnx well maintained?

We found that nnoir-onnx demonstrated a healthy version release cadence and project activity. It has a community of 20 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is nnoir-onnx safe to use?

The python package nnoir-onnx was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 12 December-2024, at 06:53 (UTC).

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nnoir-onnx

ONNX to NNOIR Converter For more information about how to use this package see README

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Readme

nnoir-onnx

Install

Example

Supported ONNX Operators

FAQs

What is nnoir-onnx?

Is nnoir-onnx popular?

Is nnoir-onnx well maintained?

Is nnoir-onnx safe to use?

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Scan your app for vulnerabilities

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Readme

nnoir-onnx

Install

Example

Supported ONNX Operators

FAQs

What is nnoir-onnx?

Is nnoir-onnx popular?

Is nnoir-onnx well maintained?

Is nnoir-onnx safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

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