Package Health Score

87 / 100

security
No known security issues
popularity
Recognized
maintenance
Healthy
community
Active

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sac
36

Popularity

Recognized

GitHub Stars: 17.36K
Forks: 4.18K
Contributors: 150

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package mlagents, we found that it has been starred 17,358 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Oct 5, 2024
Direct Vulnerabilities: 0
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0
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0
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Indirect Vulnerabilities: 0
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0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

We found a way for you to contribute to the project! Looks like mlagents is missing a security policy.

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Maintenance

Healthy

Commit Frequency

Open Issues: 13
Open PR: 36
Last Release: 3 months ago
Last Commit: 2 months ago

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

We found that mlagents 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

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 150
Funding: No

A good and healthy external contribution signal for mlagents project, which invites more than one hundred open source maintainers to collaborate on the repository.

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Package

Python Versions Compatibility: <=3.10.12,>=3.10.1

Age: 6 years
Latest Release: 3 months ago
Dependencies: 0 Direct
Versions: 47
Maintainers: 0
Wheels: OS Independent

Not sure how to use mlagents?

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

Unity-Technologies / ml-agents / ml-agents / mlagents / trainers / sac / models.py View on Github

)
        # We assume m_size is divisible by 4
        # Create the non-Policy inputs
        # Use a default placeholder here so nothing has to be provided during
        # Barracuda inference. Note that the default value is just the tiled input
        # for the policy, which is thrown away.
        three_fourths_m_size = m_size * 3 // 4
        self.other_memory_in = tf.placeholder_with_default(
            input=tf.tile(self.inference_memory_in, [1, 3]),
            shape=[None, three_fourths_m_size],
            name="other_recurrent_in",
        )

        # Concat and use this as the "placeholder"
        # for training
        self.memory_in = tf.concat(
            [self.other_memory_in, self.inference_memory_in], axis=1
        )

        # Re-break-up for each network
        num_mems = 4
        mem_ins = []
        for i in range(num_mems):
            _start = m_size // num_mems * i
            _end = m_size // num_mems * (i + 1)
            mem_ins.append(self.memory_in[:, _start:_end])
        self.value_memory_in = mem_ins[0]
        self.q1_memory_in = mem_ins[1]
        self.q2_memory_in = mem_ins[2]
        self.policy_memory_in = mem_ins[3]

View more ways to use mlagents

Unity ML-Agents Trainers

The mlagents Python package is part of the ML-Agents Toolkit. mlagents provides a set of reinforcement and imitation learning algorithms designed to be used with Unity environments. The algorithms interface with the Python API provided by the mlagents_envs package. See here for more information on mlagents_envs.

The algorithms can be accessed using the: mlagents-learn access point. See here for more information on using this package.

Installation

Install the mlagents package with:

python -m pip install mlagents==1.1.0

Usage & More Information

For more information on the ML-Agents Toolkit and how to instrument a Unity scene with the ML-Agents SDK, check out the main ML-Agents Toolkit documentation.

Limitations

Resuming self-play from a checkpoint resets the reported ELO to the default value.

FAQs

What is mlagents?

Unity Machine Learning Agents. Visit Snyk Advisor to see a full health score report for mlagents, including popularity, security, maintenance & community analysis.

Is mlagents popular?

The python package mlagents receives a total of 3,729 weekly downloads. As such, mlagents popularity was classified as a recognized. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is mlagents well maintained?

We found that mlagents demonstrated a healthy version release cadence and project activity. It has a community of 150 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is mlagents safe to use?

The python package mlagents 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 22 December-2024, at 07:36 (UTC).

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mlagents

Unity Machine Learning Agents For more information about how to use this package see README

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Unity ML-Agents Trainers

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Usage & More Information

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Not sure how to use mlagents?

Unity ML-Agents Trainers

Installation

Usage & More Information

Limitations

FAQs

What is mlagents?

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Is mlagents well maintained?

Is mlagents safe to use?

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Source Code

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Config

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