View tf2onnx on Snyk Open Source Advisor

Package Health Score

74 / 100

security
Security review needed
popularity
Influential project
maintenance
Sustainable
community
Active

Popularity

Influential project

GitHub Stars: 2.35K
Forks: 431
Contributors: 100

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package tf2onnx, we found that it has been starred 2,347 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Jan 16, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
1
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

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Maintenance

Sustainable

Commit Frequency

Open Issues: 201
Open PR: 9
Last Release: 11 months ago
Last Commit: 1 month ago

Further analysis of the maintenance status of tf2onnx based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Sustainable.

We found that tf2onnx demonstrates a positive version release cadence with at least one new version released in the past 12 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

Active

Readme: No
Contributing.md: Yes
Code of Conduct: No
Contributors: 100
Funding: No

With more than 10 contributors for the tf2onnx repository, this is possibly a sign for a growing and inviting community.

We found a way for you to contribute to the project! Looks like tf2onnx is missing a Code of Conduct.

How about a good first contribution to this project? It seems that tf2onnx is missing a README file.

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Package

Python Versions Compatibility: ==3.10.*, ==3.7.*, ==3.8.*, ==3.9.*

Age: 6 years
Latest Release: 11 months ago
Dependencies: 6 Direct / 11 Total
Versions: 34
Maintainers: 0
Wheels: OS Independent

Not sure how to use tf2onnx?

To help you get started, we've collected the most common ways that tf2onnx is being used within popular public projects.

onnx / tensorflow-onnx / tf2onnx / onnx_opset / nn.py View on Github

def add_padding(ctx, node, kernel_shape, strides, dilations=None, spatial=2):
    padding = node.get_attr("padding")
    if padding:
        if dilations is None:
            dilations = [1] * spatial * 2
        padding = padding.s.decode("utf-8")
        if padding == 'SAME':
            pads = [0] * spatial * 2
            input_shape = ctx.get_shape(node.input[0])
            output_shape = ctx.get_shape(node.output[0])
            # check if the input shape is valid
            if len(input_shape) != len(pads):
                logger.error("node %s input needs to be rank %d, is %d", node.name, len(pads), len(input_shape))
            # transpose shape to nchw
            if node.is_nhwc():
                input_shape = spatial_map(input_shape, constants.NHWC_TO_NCHW)
                output_shape = spatial_map(output_shape, constants.NHWC_TO_NCHW)
            # calculate pads
            if any(input_shape[i + 2] == -1 or output_shape[i + 2] == -1 for i in range(spatial)):
                logger.debug(
                    "node %s has unknown dim for pads calculation, fallback to auto_pad: "
                    "input_shape=%s, output_shape=%s",
                    node.name, input_shape, output_shape)
                node.set_attr("auto_pad", "SAME_UPPER")
            else:
                for i in range(spatial):
                    pad = (output_shape[i + 2] - 1) * strides[i] + dilations[i] * kernel_shape[i] - input_shape[i + 2]
                    pad = max(pad, 0)
                    pads[i] = pad // 2
                    pads[i + spatial] = pad - pad // 2
                node.set_attr("pads", pads)

View more ways to use tf2onnx

tf2onnx dependencies

flatbuffers numpy onnx protobuf requests six

FAQs

What is tf2onnx?

Tensorflow to ONNX converter. Visit Snyk Advisor to see a full health score report for tf2onnx, including popularity, security, maintenance & community analysis.

Is tf2onnx popular?

The python package tf2onnx receives a total of 108,569 weekly downloads. As such, tf2onnx popularity was classified as an influential project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is tf2onnx well maintained?

We found indications that tf2onnx maintenance is sustainable demonstrating some project activity. We saw a total of 100 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is tf2onnx safe to use?

While scanning the latest version of tf2onnx, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 21 December-2024, at 15:19 (UTC).

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tf2onnx

Tensorflow to ONNX converter For more information about how to use this package see README

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Package Health Score

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Security

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Community

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tf2onnx dependencies

FAQs

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Is tf2onnx well maintained?

Is tf2onnx safe to use?

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Package Health Score

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Commit Frequency

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tf2onnx dependencies

FAQs

What is tf2onnx?

Is tf2onnx popular?

Is tf2onnx well maintained?

Is tf2onnx safe to use?

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Source Code

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