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[MLX] [bugfix] Preserve dtype of array when converting to torch #1349

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Jan 15, 2025
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[MLX] [bugfix] Preserve dtype of array when converting to torch #1349

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e9a573a
[MLX] Preserve dtype of array when converting to torch
neilmehta24 Dec 20, 2024
40f6ad1
Fix style and run pre-commit check
neilmehta24 Dec 20, 2024
a1056a5
Improve test coverage
neilmehta24 Dec 22, 2024
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6 changes: 3 additions & 3 deletions outlines/processors/base_logits_processor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,9 +110,9 @@ def _to_torch(tensor_like: Array) -> torch.Tensor:
import mlx.core as mx

# https://ml-explore.github.io/mlx/build/html/usage/numpy.html#pytorch
return torch.from_dlpack(
np.array(tensor_like.astype(mx.float32), copy=False)
)
if tensor_like.dtype == mx.bfloat16:
tensor_like = tensor_like.astype(mx.float32)
return torch.from_dlpack(np.array(tensor_like, copy=False))

elif is_jax_array_type(type(tensor_like)):
import jax
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2 changes: 1 addition & 1 deletion tests/processors/test_base_processor.py
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Expand Up @@ -17,7 +17,7 @@
try:
import mlx.core as mx

arrays["mlx"] = mx.array([[1, 2], [3, 4]], dtype=mx.float32)
arrays["mlx"] = mx.array([[1, 2], [3, 4]], dtype=mx.bfloat16)
except ImportError:
pass

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