fauxtograph
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Tools for using a variational auto-encoder for latent image encoding and generation.
Bumps [requests](https://github.com/psf/requests) from 2.7.0 to 2.31.0. Release notes Sourced from requests's releases. v2.31.0 2.31.0 (2023-05-22) Security Versions of Requests between v2.3.0 and v2.30.0 are vulnerable to potential forwarding of Proxy-Authorization...
Bumps [ipython](https://github.com/ipython/ipython) from 4.0.0 to 8.10.0. Release notes Sourced from ipython's releases. See https://pypi.org/project/ipython/ We do not use GitHub release anymore. Please see PyPI https://pypi.org/project/ipython/ 7.9.0 No release notes provided....
Bumps [wheel](https://github.com/pypa/wheel) from 0.24.0 to 0.38.1. Changelog Sourced from wheel's changelog. Release Notes UNRELEASED Updated vendored packaging to 22.0 0.38.4 (2022-11-09) Fixed PKG-INFO conversion in bdist_wheel mangling UTF-8 header values...
Bumps [pillow](https://github.com/python-pillow/Pillow) from 2.9.0 to 9.3.0. Release notes Sourced from pillow's releases. 9.3.0 https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html Changes Initialize libtiff buffer when saving #6699 [@radarhere] Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [@wiredfool]...
Bumps [joblib](https://github.com/joblib/joblib) from 0.8.4 to 1.2.0. Changelog Sourced from joblib's changelog. Release 1.2.0 Fix a security issue where eval(pre_dispatch) could potentially run arbitrary code. Now only basic numerics are supported....
Bumps [protobuf](https://github.com/protocolbuffers/protobuf) from 2.6.1 to 3.18.3. Release notes Sourced from protobuf's releases. Protocol Buffers v3.18.3 C++ Reduce memory consumption of MessageSet parsing This release addresses a Security Advisory for C++...
Bumps [numpy](https://github.com/numpy/numpy) from 1.9.2 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...
VAE and VAEGAN code is currently using [mean squared error](https://github.com/stitchfix/fauxtograph/blob/15bc0ba787d4724657379ec31dd7840304b8f858/fauxtograph/vaegan.py#L529) as the reconstruction loss function. In most papers / implementations, I'm more used to seeing binary cross entropy with numbers...
I encountered several bugs running it on Python 3. I fixed them here in a way compatible with both Python 2 and 3 so everyone's happy. This PR includes: -...
While training on my own images, I'm getting this error, chainer.utils.type_check.InvalidType: Invalid operation is performed in: LinearFunction (Forward) Expect: prod(in_types[0].shape[1:]) == in_types[1].shape[1] Actual: 259656 != 27648