Comments (6)
I will make this a feature and leave it open. I think it's a good idea to have useful type hints for the stable Python API.
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I ran a quick Python script to see which files are missing type annotations, does this look right?
Report: https://pastebin.com/raw/PepZW2jM
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I would only consider files in the subdirectory python/mlx
for now. We don't need to add strict type hints to benchmarks and tests.
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That makes sense - I've modified this here. I was just crawling .py
files, changed that around.
https://github.com/AbhinavMir/mlx/blob/typeAnno/type_annotation_report.md
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I have added some type hints for few functions given in above file by @AbhinavMir
Please let me know if they're right
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One of my friends @catplotlib wants to try Open Source, tagging her here so she can pick up a few type hints!
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Related Issues (20)
- Memory Leakage Issue in MLX 0.16 HOT 9
- [PERFORMANCE] grads for bitwise ops + indexing HOT 1
- [Performance] Linear Layer Benchmark HOT 2
- [BUG] expm1 handling of overflow / underflow causes wrong results
- [Feature Request] mx.pad supports the "edge" padding mode.
- [BUG] Cannot use mlx.metallib from xcode MacOS project (Swift, C++)
- [BUG] Cannot convert a list with `None` to `mx.array` HOT 1
- [BUG] Docs not building HOT 4
- How can we enable w4a8 GEMM in MLX? HOT 6
- Missing pyi file for mlx.core HOT 1
- Performance Comparison Issue: Matrix Multiplication on MLX vs. PyTorch on Mac HOT 3
- [Feature Request] Cannot create tensor from raw bytes + dtypes HOT 3
- [BUG] mx.std returns NaN HOT 1
- What is the equivalent to a Flatten layer in MLX? HOT 6
- How to mask out padding tokens when calculating the cross-entropy? HOT 2
- 使用exo+mlx多台mac运行llama-3.1-70b,返现量化时报错[BUG] HOT 1
- [Performance] PyTorch (MPS) is faster than MLX in backward of convolution layer HOT 4
- [BUG] Dropout not preserving `dtype` HOT 5
- [BUG] Convergence issue in MLX when compared to PyTorch HOT 4
- [BUG] Unable to load from a saved checkpoint, `KeyError` for all dropout modules... HOT 1
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