onnx2pytorch | Transform ONNX model to PyTorch representation | Machine Learning library

by ToriML Python Version: 0.4.1 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | onnx2pytorch Summary

onnx2pytorch is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Transformer applications. onnx2pytorch has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install onnx2pytorch' or download it from GitHub, PyPI.

Transform ONNX model to PyTorch representation

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Quality

Security

License

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Support

onnx2pytorch has a low active ecosystem.

It has 58 star(s) with 7 fork(s). There are 6 watchers for this library.

It had no major release in the last 12 months.

There are 7 open issues and 2 have been closed. On average issues are closed in 27 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of onnx2pytorch is 0.4.1

Quality

onnx2pytorch has 0 bugs and 19 code smells.

Security

onnx2pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

onnx2pytorch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

onnx2pytorch 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

onnx2pytorch 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.

It has 1961 lines of code, 151 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 onnx2pytorch and discovered the below as its top functions. This is intended to give you an instant insight into onnx2pytorch implemented functionality, and help decide if they suit your requirements.

Convert opset_version layer
Extract padding params
Extracts the values from an attribute
Extracts attributes from a node
Perform the forward computation
Assign values to tensor
Return a tuple of the split sections
Forward the model
Debugging function
Get activation value from inputs
Perform forward computation
Get a slice of the given indices
Set input indices
Return the axis of the input shape
Forward computation
Convert a slice into a positive step
Calculate the inverse matrix

Get all kandi verified functions for this library.

onnx2pytorch Key Features

No Key Features are available at this moment for onnx2pytorch.

onnx2pytorch Examples and Code Snippets

ONNX to PyTorch,Usage

Python

Lines of Code : 5

License : Permissive (Apache-2.0)

Copy

import onnx
from onnx2pytorch import ConvertModel

onnx_model = onnx.load(path_to_onnx_model)
pytorch_model = ConvertModel(onnx_model)

UnpicklingError: A load persistent id instruction was encountered, but no persistent_load function was specified

Python

Lines of Code : 26

License : Strong Copyleft (CC BY-SA 4.0)

Copy

import onnx
from onnx2pytorch import ConvertModel


def load_model_weights(model_architecture, weights_path):
    if os.path.isfile("model.onnx"):
        cherrypy.log("CHERRYPYLOG Loading model from: {}".format(weights_path))
        onnx

AttributeError: 'ConvertModel' object has no attribute 'seek'

Python

Lines of Code : 9

License : Strong Copyleft (CC BY-SA 4.0)

Copy

import io

with open('my_data.dat', 'rb') as f:
    buf = io.BytesIO(f.read())

    buf.seek(4)

    x = buf.read(1)

Community Discussions

Trending Discussions on onnx2pytorch

AttributeError: 'ConvertModel' object has no attribute 'seek'

QUESTION

AttributeError: 'ConvertModel' object has no attribute 'seek'

Asked 2021-Feb-21 at 18:09

I tried converting a MATLAB model to PyTorch using ONNX, like proposed here by Andrew Naguib:

How to import deep learning models from MATLAB to PyTorch?

I tried running the model using the following code:

...

ANSWER

Answered 2021-Feb-21 at 16:35

Assuming my_data.dat is a file containing binary data, the following code loads it into an ioBytesIO buffer that is seekable:

Source https://stackoverflow.com/questions/66304260

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

Vulnerabilities

No vulnerabilities reported

Install onnx2pytorch

From onnxruntime>=1.5.0 you need to add the following to your .bashrc or .zshrc if you are running OSx: export KMP_DUPLICATE_LIB_OK=True.

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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