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Update ToDtype to avoid unnecessary to() calls and fixing types on Transform #6773

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Merged
datumbox merged 6 commits into from
Oct 14, 2022
Merged

Update ToDtype to avoid unnecessary to() calls and fixing types on Transform #6773

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d92cb47
Fix `ToDtype` to avoid errors when a type is not defined.
datumbox Oct 14, 2022
1fcc660
Nit `(features.is_simple_tensor, features._Feature)` to `(Tensor,)`
datumbox Oct 14, 2022
89d57a4
Fixing linter
datumbox Oct 14, 2022
0efdc4b
Adding comment.
datumbox Oct 14, 2022
6827e59
Switch back to indexing. Python's default dict seems to have a nasty …
datumbox Oct 14, 2022
a0a7b06
Merge branch 'main' into bugfix/todtype
datumbox Oct 14, 2022
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5 changes: 4 additions & 1 deletion torchvision/prototype/transforms/_misc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -157,7 +157,10 @@ def __init__(self, dtype: Union[torch.dtype, Dict[Type, torch.dtype]]) -> None:
self.dtype = dtype

def _transform(self, inpt: Any, params: Dict[str, Any]) -> Any:
return inpt.to(self.dtype[type(inpt)])
dtype = self.dtype[type(inpt)]
if dtype is None:
return inpt
return inpt.to(dtype=dtype)


class RemoveSmallBoundingBoxes(Transform):
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8 changes: 2 additions & 6 deletions torchvision/prototype/transforms/_transform.py
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Expand Up @@ -5,19 +5,15 @@
import torch
from torch import nn
from torch.utils._pytree import tree_flatten, tree_unflatten
from torchvision.prototype import features
from torchvision.prototype.transforms._utils import _isinstance
from torchvision.utils import _log_api_usage_once


class Transform(nn.Module):

# Class attribute defining transformed types. Other types are passed-through without any transformation
_transformed_types: Tuple[Union[Type, Callable[[Any], bool]], ...] = (
features.is_simple_tensor,
features._Feature,
PIL.Image.Image,
)
# We support both Types and callables that are able to do further checks on the type of the input.
_transformed_types: Tuple[Union[Type, Callable[[Any], bool]], ...] = (torch.Tensor, PIL.Image.Image)

def __init__(self) -> None:
super().__init__()
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