Skip to content
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

[Blip] Fix blip output name #24889

Merged
merged 4 commits into from
Jul 18, 2023
Merged

[Blip] Fix blip output name #24889

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
25f0bcb
fix blip output name
younesbelkada Jul 18, 2023
6e094fb
add property
younesbelkada Jul 18, 2023
6c9bd2a
oops
younesbelkada Jul 18, 2023
9e34b24
fix failing test
younesbelkada Jul 18, 2023
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
16 changes: 13 additions & 3 deletions src/transformers/models/blip/modeling_blip.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
# limitations under the License.
""" PyTorch BLIP model."""

import warnings
from dataclasses import dataclass
from typing import Any, Optional, Tuple, Union

Expand Down Expand Up @@ -74,7 +75,7 @@ class BlipForConditionalGenerationModelOutput(ModelOutput):
Args:
loss (`torch.FloatTensor`, *optional*, returned when `labels` is provided, `torch.FloatTensor` of shape `(1,)`):
Languge modeling loss from the text decoder.
decoder_logits (`torch.FloatTensor` of shape `(batch_size, sequence_length, config.vocab_size)`, *optional*):
logits (`torch.FloatTensor` of shape `(batch_size, sequence_length, config.vocab_size)`, *optional*):
Prediction scores of the language modeling head of the text decoder model.
image_embeds (`torch.FloatTensor` of shape `(batch_size, output_dim)`, *optional*):
The image embeddings obtained after applying the Vision Transformer model to the input image.
Expand All @@ -94,12 +95,21 @@ class BlipForConditionalGenerationModelOutput(ModelOutput):
"""

loss: Optional[Tuple[torch.FloatTensor]] = None
decoder_logits: Optional[Tuple[torch.FloatTensor]] = None
logits: Optional[Tuple[torch.FloatTensor]] = None
image_embeds: Optional[torch.FloatTensor] = None
last_hidden_state: torch.FloatTensor = None
hidden_states: Optional[Tuple[torch.FloatTensor]] = None
attentions: Optional[Tuple[torch.FloatTensor]] = None

@property
def decoder_logits(self):
warnings.warn(
"`decoder_logits` attribute is deprecated and will be removed in version 5 of Transformers."
" Please use the `logits` attribute to retrieve the final output instead.",
FutureWarning,
)
return self.logits


@dataclass
class BlipTextVisionModelOutput(ModelOutput):
Expand Down Expand Up @@ -1011,7 +1021,7 @@ def forward(

return BlipForConditionalGenerationModelOutput(
loss=outputs.loss,
decoder_logits=outputs.logits,
logits=outputs.logits,
image_embeds=image_embeds,
last_hidden_state=vision_outputs.last_hidden_state,
hidden_states=vision_outputs.hidden_states,
Expand Down
16 changes: 13 additions & 3 deletions src/transformers/models/blip/modeling_tf_blip.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@

from __future__ import annotations

import warnings
from dataclasses import dataclass
from typing import Any, Optional, Tuple, Union

Expand Down Expand Up @@ -84,7 +85,7 @@ class TFBlipForConditionalGenerationModelOutput(ModelOutput):
Args:
loss (`tf.Tensor`, *optional*, returned when `labels` is provided, `tf.Tensor` of shape `(1,)`):
Languge modeling loss from the text decoder.
decoder_logits (`tf.Tensor` of shape `(batch_size, sequence_length, config.vocab_size)`, *optional*):
logits (`tf.Tensor` of shape `(batch_size, sequence_length, config.vocab_size)`, *optional*):
Prediction scores of the language modeling head of the text decoder model.
image_embeds (`tf.Tensor` of shape `(batch_size, output_dim)`, *optional*):
The image embeddings obtained after applying the Vision Transformer model to the input image.
Expand All @@ -104,12 +105,21 @@ class TFBlipForConditionalGenerationModelOutput(ModelOutput):
"""

loss: Tuple[tf.Tensor] | None = None
decoder_logits: Tuple[tf.Tensor] | None = None
logits: Tuple[tf.Tensor] | None = None
image_embeds: tf.Tensor | None = None
last_hidden_state: tf.Tensor = None
hidden_states: Tuple[tf.Tensor] | None = None
attentions: Tuple[tf.Tensor] | None = None

@property
def decoder_logits(self):
warnings.warn(
"`decoder_logits` attribute is deprecated and will be removed in version 5 of Transformers."
" Please use the `logits` attribute to retrieve the final output instead.",
FutureWarning,
)
return self.logits


@dataclass
class TFBlipTextVisionModelOutput(ModelOutput):
Expand Down Expand Up @@ -1078,7 +1088,7 @@ def call(

return TFBlipForConditionalGenerationModelOutput(
loss=outputs.loss,
decoder_logits=outputs.logits,
logits=outputs.logits,
image_embeds=image_embeds,
last_hidden_state=vision_outputs.last_hidden_state,
hidden_states=vision_outputs.hidden_states,
Expand Down