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Pull Request Overview
This PR introduces a new ScalarField modality and its corresponding autoencoder-based codec, ScalarFieldCodec, to extend the framework’s support for 2D scalar field data. Key changes include:
- Implementation of ScalarFieldCodec (with quantization and EMA support) in aion/codecs/scalar_field.py.
- Integration of the new ScalarField modality in aion/modalities.py and registration of the codec in aion/codecs/init.py.
- Addition of test cases and data for verifying codec functionality.
Reviewed Changes
Copilot reviewed 9 out of 9 changed files in this pull request and generated 2 comments.
Show a summary per file
| File | Description |
|---|---|
| tests/tokenizers/test_scalar_field_tokenizer.py | Adds tests for encoding/decoding scalar field data. |
| tests/test_data/*.pt | Provides test data for input, encoded, and decoded scalar field batches. |
| aion/modalities.py | Introduces new ScalarField modality and updates ModalityType union. |
| aion/codecs/scalar_field.py | Implements the ScalarFieldCodec with autoencoder, quantization, and EMA support. |
| aion/codecs/modules/ema.py | Adds ModelEmaV2 implementation for model weight averaging. |
| aion/codecs/init.py | Registers ScalarFieldCodec in the codecs package. |
Comments suppressed due to low confidence (1)
aion/codecs/scalar_field.py:96
- [nitpick] There's an inconsistent spelling between 'quantisation_loss_weight' in the parameter and 'quantization_loss_weight' in the assignment. Please choose one consistent spelling for clarity.
self.quantization_loss_weight = quantisation_loss_weight
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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This pull request introduces a new
ScalarFieldCodecfor handling scalar field modalities, including its implementation, integration into the existing framework, and associated tests. The changes focus on adding support for scalar fields as a new modality and ensuring compatibility with the current codec and modality structure.Codec and Modality Enhancements:
ScalarFieldCodecclass inaion/codecs/scalar_field.py, which includes an autoencoder-based architecture for encoding and decoding scalar fields. It supports features such as quantization, loss optimization, and exponential moving average (EMA) of model weights.ScalarFieldmodality inaion/modalities.pyto represent 2D scalar fields like density or temperature maps. Updated theModalityTypeunion to includeScalarField. [1] [2]Codebase Integration:
ScalarFieldCodecinaion/codecs/__init__.pyto make it accessible within the codec package. [1] [2]ModelEmaV2class inaion/codecs/modules/ema.pyto support exponential moving average for model weights, which is used in the new codec.Testing and Validation:
tests/test_datafor validating codec functionality. [1] [2] [3]tests/tokenizers/test_scalar_field_tokenizer.pyto verify the encoding and decoding processes of theScalarFieldCodecagainst reference data.