fix(gallery): handle MPS float64 mask inputs (#5903)

Co-authored-by: Alexandre Teixeira <111787685+alteixeira20@users.noreply.github.com>
This commit is contained in:
Manuel Cartagena Herrera 2026-08-11 20:23:43 -04:00 committed by GitHub
parent 93653120d6
commit 5a016e492c
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
2 changed files with 55 additions and 8 deletions

View file

@ -127,6 +127,25 @@ def _load_grounding_backend():
return cached
def _model_input_to_device(value, device: str, torch):
if not hasattr(value, "to"):
return value
if (
device == "mps"
and hasattr(torch, "float64")
and getattr(value, "dtype", None) == torch.float64
):
return value.to(device=device, dtype=torch.float32)
return value.to(device)
def _model_inputs_to_device(inputs, device: str, torch) -> Dict[str, Any]:
return {
key: _model_input_to_device(value, device, torch)
for key, value in inputs.items()
}
def _ground_text_to_box(image, text: str, *, threshold: float = 0.05):
query = (text or "").strip()
if not query:
@ -142,10 +161,7 @@ def _ground_text_to_box(image, text: str, *, threshold: float = 0.05):
labels.append(f"a photo of {query}")
try:
inputs = processor(text=[labels], images=image, return_tensors="pt")
model_inputs = {
k: (v.to(device) if hasattr(v, "to") else v)
for k, v in inputs.items()
}
model_inputs = _model_inputs_to_device(inputs, device, torch)
with torch.no_grad():
outputs = model(**model_inputs)
target_sizes = torch.tensor([[image.height, image.width]])
@ -1869,10 +1885,7 @@ def setup_gallery_routes() -> APIRouter:
try:
inputs = processor(image, **kwargs)
model_inputs = {
k: (v.to(device) if hasattr(v, "to") else v)
for k, v in inputs.items()
}
model_inputs = _model_inputs_to_device(inputs, device, torch)
with torch.no_grad():
outputs = model(**model_inputs)
masks = processor.image_processor.post_process_masks(

View file

@ -0,0 +1,34 @@
import routes.gallery_routes as gallery_routes
class _TorchSentinel:
float32 = object()
float64 = object()
class _FakeTensor:
def __init__(self, dtype):
self.dtype = dtype
self.to_args = None
def to(self, *args, **kwargs):
self.to_args = (args, kwargs)
return self
def test_model_inputs_to_device_casts_mps_float64_to_float32():
float_tensor = _FakeTensor(_TorchSentinel.float64)
int_tensor = _FakeTensor("int64")
plain_value = object()
result = gallery_routes._model_inputs_to_device(
{"points": float_tensor, "labels": int_tensor, "plain": plain_value},
"mps",
_TorchSentinel,
)
assert result["points"] is float_tensor
assert float_tensor.to_args == ((), {"device": "mps", "dtype": _TorchSentinel.float32})
assert int_tensor.to_args == (("mps",), {})
assert result["plain"] is plain_value