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Force contiguous searchsorted #396

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Merged
merged 4 commits into from
Apr 8, 2025
Merged

Force contiguous searchsorted #396

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86847f3
force contiguous tensors in torch searchsorted
LarsKue Apr 8, 2025
57a7392
improve warning message for torch backend
LarsKue Apr 8, 2025
d862baf
run linter
LarsKue Apr 8, 2025
657d28f
undo using workers in workflow (subject to a different issue)
LarsKue Apr 8, 2025
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4 changes: 4 additions & 0 deletions bayesflow/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,8 +40,12 @@ def setup():
torch.autograd.set_grad_enabled(False)

logging.warning(
"\n"
"When using torch backend, we need to disable autograd by default to avoid excessive memory usage. Use\n"
"\n"
"with torch.enable_grad():\n"
" ...\n"
"\n"
"in contexts where you need gradients (e.g. custom training loops)."
)

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4 changes: 3 additions & 1 deletion bayesflow/utils/tensor_utils.py
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Expand Up @@ -202,7 +202,9 @@ def searchsorted(sorted_sequence: Tensor, values: Tensor, side: str = "left") ->

out_int32 = len(sorted_sequence) <= np.iinfo(np.int32).max

indices = torch.searchsorted(sorted_sequence, values, side=side, out_int32=out_int32)
indices = torch.searchsorted(
sorted_sequence.contiguous(), values.contiguous(), side=side, out_int32=out_int32
)

return indices
case _:
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