[Snyk] Security upgrade tensorflow from 2.11.0 to 2.12.0rc1

[turian]

This PR was automatically created by Snyk using the credentials of a real user.

Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

Changes included in this PR

• Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
  • requirements.txt

⚠️ Warning

tensorflow-metadata 1.12.0 has requirement protobuf<4,>=3.13, but you have protobuf 4.24.4.
tensorflow-metadata 1.12.0 has requirement absl-py<2.0.0,>=0.9, but you have absl-py 2.1.0.
scikit-learn 1.0.2 requires scipy, which is not installed.
python-daemon 3.0.1 has requirement setuptools>=62.4.0, but you have setuptools 40.5.0.
note-seq 0.0.5 requires scipy, which is not installed.
mido 1.3.2 has requirement packaging~=23.1, but you have packaging 24.0.
librosa 0.10.1 requires scipy, which is not installed.
librosa 0.10.1 has requirement numba>=0.51.0, but you have numba 0.48.0.
librosa 0.10.1 has requirement numpy!=1.22.0,!=1.22.1,!=1.22.2,>=1.20.3, but you have numpy 1.19.2.
botocore 1.33.13 has requirement urllib3<1.27,>=1.25.4; python_version < "3.10", but you have urllib3 2.0.7.

Vulnerabilities that will be fixed

By pinning:

Severity	Priority Score (*)	Issue	Upgrade	Breaking Change	Exploit Maturity
	776/1000 Why? Proof of Concept exploit, Has a fix available, CVSS 9.1	Arbitrary File Write via Archive Extraction (Zip Slip) SNYK-PYTHON-TENSORFLOW-1315149	tensorflow: 2.11.0 -> 2.12.0rc1	No	Proof of Concept

(*) Note that the real score may have changed since the PR was raised.

Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

Check the changes in this PR to ensure they won't cause issues with your project.

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