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Encoder Compatibility Issue Across Models Using mit_b0 #967

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shahidul034 opened this issue Oct 28, 2024 · 1 comment
Open

Encoder Compatibility Issue Across Models Using mit_b0 #967

shahidul034 opened this issue Oct 28, 2024 · 1 comment

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@shahidul034
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Encoder Compatibility Issue Across Models Using mit_b0

Description

While using mit_b0 as an encoder, I encountered compatibility issues with several models, not just the previously mentioned Linknet and Unet++. According to the documentation, Linknet and Unet++ do not support mit_b0 as an encoder, and FPN supports it only with an encoder depth of 5. However, in practice, other models also fail to support mit_b0 as an encoder.

Models and Observed Behavior

Below is a list of models and the observed training status using mit_b0 as an encoder:

Trained Successfully

  • Unet (both with imagenet and without a pretrained encoder)
  • FPN (both with imagenet and without a pretrained encoder)
  • PSPNet (both with imagenet and without a pretrained encoder)
  • MAnet (both with imagenet and without a pretrained encoder)

Encountered Exceptions (Not Trained)

  • UnetPlusPlus (both with imagenet and without a pretrained encoder)
  • Linknet (both with imagenet and without a pretrained encoder)
  • DeepLabV3 (both with imagenet and without a pretrained encoder)
  • DeepLabV3Plus (both with imagenet and without a pretrained encoder)
  • PAN (both with imagenet and without a pretrained encoder)

Expected Behavior

The documentation should either:

  1. Clarify that mit_b0 is not compatible with certain models, including but not limited to Linknet and Unet++.
  2. Indicate that these models are not supported with the current encoder configuration.

This clarification would help set clear expectations for users attempting to use mit_b0 across various models.

Environment

  • OS: Ubuntu 24.04.1 LTS
  • Framework: PyTorch
  • Python version: 3.11
@brianhou0208
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Check the PR here #975

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