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I'm submitting a ...
bug report
feature request
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Bug report - Occasionally, model.Facenet() returns a value error when using the non default model, something to do with the final BatchNorm1D torch.nn layer
What is the current behavior?
Works fine when a list of more than 1 image is passed to the model. However, when only 1 image is passed, the final batch normalisation layer raises the error: [Expected more than 1 value per channel when training, got input size torch.Size([1, 3, img_height, img_width])]
If the current behavior is a bug, please provide the steps to reproduce and if possible a minimal demo of the problem
Pass a single image to the model to reproduce this error
What is the expected behavior?
Model should ideally return embeddings for any number of images passed to it
What is the motivation / use case for changing the behavior?
Please tell us about your environment:
Version: 2.0.0-beta.X
Browser: [all | Chrome XX | Firefox XX | IE XX | Safari XX | Mobile Chrome XX | Android X.X Web Browser | iOS XX Safari | iOS XX UIWebView | iOS XX WKWebView ]
Note: for support questions, please use the discord server. This repository's issues are reserved for feature requests and bug reports.
I'm submitting a ...
Do you want to request a feature or report a bug? Give a brief on it.
Bug report - Occasionally, model.Facenet() returns a value error when using the non default model, something to do with the final BatchNorm1D torch.nn layer
What is the current behavior?
Works fine when a list of more than 1 image is passed to the model. However, when only 1 image is passed, the final batch normalisation layer raises the error:
[Expected more than 1 value per channel when training, got input size torch.Size([1, 3, img_height, img_width])]
If the current behavior is a bug, please provide the steps to reproduce and if possible a minimal demo of the problem
Pass a single image to the model to reproduce this error
What is the expected behavior?
Model should ideally return embeddings for any number of images passed to it
What is the motivation / use case for changing the behavior?
Please tell us about your environment:
Other information (e.g. detailed explanation, stacktraces, related issues, suggestions how to fix, links for us to have context, eg. stackoverflow, gitter, etc)
https://stackoverflow.com/questions/65882526/expected-more-than-1-value-per-channel-when-training-got-input-size-torch-size
https://github.com/timesler/facenet-pytorch/blob/fa70227bd5f02209512f60bd10e7e66877fdb4f6/models/inception_resnet_v1.py#L258C81-L258C81
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