Unverified Commit 525dbbf8 authored by Yih-Dar's avatar Yih-Dar Committed by GitHub
Browse files

Remove loss from some flax models docs & examples (#15492)



* Remove return_loss from Flax models

* fix more

* fix
Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
parent 21dcaec5
...@@ -144,8 +144,6 @@ CLIP_INPUTS_DOCSTRING = r""" ...@@ -144,8 +144,6 @@ CLIP_INPUTS_DOCSTRING = r"""
pixel_values (`numpy.ndarray` of shape `(batch_size, num_channels, height, width)`): pixel_values (`numpy.ndarray` of shape `(batch_size, num_channels, height, width)`):
Pixel values. Padding will be ignored by default should you provide it. Pixel values can be obtained using Pixel values. Padding will be ignored by default should you provide it. Pixel values can be obtained using
[`CLIPFeatureExtractor`]. See [`CLIPFeatureExtractor.__call__`] for details. [`CLIPFeatureExtractor`]. See [`CLIPFeatureExtractor.__call__`] for details.
return_loss (`bool`, *optional*):
Whether or not to return the contrastive loss.
output_attentions (`bool`, *optional*): output_attentions (`bool`, *optional*):
Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned
tensors for more detail. tensors for more detail.
......
...@@ -561,9 +561,8 @@ VISION_TEXT_DUAL_ENCODER_MODEL_DOCSTRING = r""" ...@@ -561,9 +561,8 @@ VISION_TEXT_DUAL_ENCODER_MODEL_DOCSTRING = r"""
... input_ids=inputs.input_ids, ... input_ids=inputs.input_ids,
... attention_mask=inputs.attention_mask, ... attention_mask=inputs.attention_mask,
... pixel_values=inputs.pixel_values, ... pixel_values=inputs.pixel_values,
... return_loss=True,
... ) ... )
>>> loss, logits_per_image = outputs.loss, outputs.logits_per_imag # this is the image-text similarity score >>> logits_per_image = outputs.logits_per_image # this is the image-text similarity score
>>> # save and load from pretrained >>> # save and load from pretrained
>>> model.save_pretrained("vit-bert") >>> model.save_pretrained("vit-bert")
......
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