Files
mlx/python/src
Daniel Strobusch dfdb284e16 make behaviour of dtype arguments consistent and compliant to numpy (#379)
All functions that take an optional dtype should

* have a default dtype visible in the generated docs (accomplished via `"dtype"_a = std::optional{float32}`)
* behave identical when `dtype=None` or no dtype is passed

This important when passing kw args down from a numpy function like:

```
def f(x, dtype=None):
  mx.random.uniform(dtype=dtype)
  # ...
```

NumPy functions behave like this.

It also fixes a minor bug in `tri`: #378

Closes #378
2024-01-05 09:37:46 -08:00
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