Skip to content

Fix: propagate interpolate_pos_encoding through PixioEmbeddings and PixioModel #44723

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
aashirpersonal wants to merge 1 commit into from
Closed

Fix: propagate interpolate_pos_encoding through PixioEmbeddings and PixioModel #44723

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
9 changes: 6 additions & 3 deletions src/transformers/models/pixio/modeling_pixio.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -132,10 +132,12 @@ def interpolate_pos_encoding(self, embeddings: torch.Tensor, height: int, width:

return torch.cat((class_pos_embed, patch_pos_embed), dim=1)

def forward(self, pixel_values: torch.Tensor) -> torch.Tensor:
def forward(self, pixel_values: torch.Tensor, interpolate_pos_encoding: bool = False) -> torch.Tensor:
batch_size, _, height, width = pixel_values.shape
target_dtype = self.patch_embeddings.projection.weight.dtype
embeddings = self.patch_embeddings(pixel_values.to(dtype=target_dtype))
embeddings = self.patch_embeddings(
pixel_values.to(dtype=target_dtype), interpolate_pos_encoding=interpolate_pos_encoding
)

cls_tokens = self.cls_token.expand(batch_size, -1, -1)
embeddings = torch.cat((cls_tokens, embeddings), dim=1)
Expand Down Expand Up @@ -407,12 +409,13 @@ def get_input_embeddings(self) -> PixioPatchEmbeddings:
def forward(
self,
pixel_values: torch.Tensor | None = None,
interpolate_pos_encoding: bool = False,
**kwargs: Unpack[TransformersKwargs],
) -> BaseModelOutputWithPooling:
if pixel_values is None:
raise ValueError("You have to specify pixel_values")

embedding_output = self.embeddings(pixel_values)
embedding_output = self.embeddings(pixel_values, interpolate_pos_encoding=interpolate_pos_encoding)

encoder_outputs: BaseModelOutput = self.encoder(embedding_output, **kwargs)
sequence_output = encoder_outputs.last_hidden_state
Expand Down
9 changes: 6 additions & 3 deletions src/transformers/models/pixio/modular_pixio.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -172,10 +172,12 @@ def interpolate_pos_encoding(self, embeddings: torch.Tensor, height: int, width:

return torch.cat((class_pos_embed, patch_pos_embed), dim=1)

def forward(self, pixel_values: torch.Tensor) -> torch.Tensor:
def forward(self, pixel_values: torch.Tensor, interpolate_pos_encoding: bool = False) -> torch.Tensor:
batch_size, _, height, width = pixel_values.shape
target_dtype = self.patch_embeddings.projection.weight.dtype
embeddings = self.patch_embeddings(pixel_values.to(dtype=target_dtype))
embeddings = self.patch_embeddings(
pixel_values.to(dtype=target_dtype), interpolate_pos_encoding=interpolate_pos_encoding
)

cls_tokens = self.cls_token.expand(batch_size, -1, -1)
embeddings = torch.cat((cls_tokens, embeddings), dim=1)
Expand Down Expand Up @@ -274,12 +276,13 @@ def get_input_embeddings(self) -> PixioPatchEmbeddings:
def forward(
self,
pixel_values: torch.Tensor | None = None,
interpolate_pos_encoding: bool = False,
**kwargs: Unpack[TransformersKwargs],
) -> BaseModelOutputWithPooling:
if pixel_values is None:
raise ValueError("You have to specify pixel_values")

embedding_output = self.embeddings(pixel_values)
embedding_output = self.embeddings(pixel_values, interpolate_pos_encoding=interpolate_pos_encoding)

encoder_outputs: BaseModelOutput = self.encoder(embedding_output, **kwargs)
sequence_output = encoder_outputs.last_hidden_state
Expand Down
Loading