1. 30 May, 2023 8 commits
  2. 29 May, 2023 1 commit
  3. 26 May, 2023 14 commits
  4. 25 May, 2023 2 commits
  5. 24 May, 2023 3 commits
  6. 23 May, 2023 10 commits
  7. 22 May, 2023 2 commits
    • Will Berman's avatar
      do not scale the initial global step by gradient accumulation steps when... · 67cd4601
      Will Berman authored
      do not scale the initial global step by gradient accumulation steps when loading from checkpoint (#3506)
      
      67cd4601
    • Birch-san's avatar
      Support for cross-attention bias / mask (#2634) · 64bf5d33
      Birch-san authored
      
      
      * Cross-attention masks
      
      prefer qualified symbol, fix accidental Optional
      
      prefer qualified symbol in AttentionProcessor
      
      prefer qualified symbol in embeddings.py
      
      qualified symbol in transformed_2d
      
      qualify FloatTensor in unet_2d_blocks
      
      move new transformer_2d params attention_mask, encoder_attention_mask to the end of the section which is assumed (e.g. by functions such as checkpoint()) to have a stable positional param interface. regard return_dict as a special-case which is assumed to be injected separately from positional params (e.g. by create_custom_forward()).
      
      move new encoder_attention_mask param to end of CrossAttn block interfaces and Unet2DCondition interface, to maintain positional param interface.
      
      regenerate modeling_text_unet.py
      
      remove unused import
      
      unet_2d_condition encoder_attention_mask docs
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      
      versatile_diffusion/modeling_text_unet.py encoder_attention_mask docs
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      
      transformer_2d encoder_attention_mask docs
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      
      unet_2d_blocks.py: add parameter name comments
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      
      revert description. bool-to-bias treatment happens in unet_2d_condition only.
      
      comment parameter names
      
      fix copies, style
      
      * encoder_attention_mask for SimpleCrossAttnDownBlock2D, SimpleCrossAttnUpBlock2D
      
      * encoder_attention_mask for UNetMidBlock2DSimpleCrossAttn
      
      * support attention_mask, encoder_attention_mask in KCrossAttnDownBlock2D, KCrossAttnUpBlock2D, KAttentionBlock. fix binding of attention_mask, cross_attention_kwargs params in KCrossAttnDownBlock2D, KCrossAttnUpBlock2D checkpoint invocations.
      
      * fix mistake made during merge conflict resolution
      
      * regenerate versatile_diffusion
      
      * pass time embedding into checkpointed attention invocation
      
      * always assume encoder_attention_mask is a mask (i.e. not a bias).
      
      * style, fix-copies
      
      * add tests for cross-attention masks
      
      * add test for padding of attention mask
      
      * explain mask's query_tokens dim. fix explanation about broadcasting over channels; we actually broadcast over query tokens
      
      * support both masks and biases in Transformer2DModel#forward. document behaviour
      
      * fix-copies
      
      * delete attention_mask docs on the basis I never tested self-attention masking myself. not comfortable explaining it, since I don't actually understand how a self-attn mask can work in its current form: the key length will be different in every ResBlock (we don't downsample the mask when we downsample the image).
      
      * review feedback: the standard Unet blocks shouldn't pass temb to attn (only to resnet). remove from KCrossAttnDownBlock2D,KCrossAttnUpBlock2D#forward.
      
      * remove encoder_attention_mask param from SimpleCrossAttn{Up,Down}Block2D,UNetMidBlock2DSimpleCrossAttn, and mask-choice in those blocks' #forward, on the basis that they only do one type of attention, so the consumer can pass whichever type of attention_mask is appropriate.
      
      * put attention mask padding back to how it was (since the SD use-case it enabled wasn't important, and it breaks the original unclip use-case). disable the test which was added.
      
      * fix-copies
      
      * style
      
      * fix-copies
      
      * put encoder_attention_mask param back into Simple block forward interfaces, to ensure consistency of forward interface.
      
      * restore passing of emb to KAttentionBlock#forward, on the basis that removal caused test failures. restore also the passing of emb to checkpointed calls to KAttentionBlock#forward.
      
      * make simple unet2d blocks use encoder_attention_mask, but only when attention_mask is None. this should fix UnCLIP compatibility.
      
      * fix copies
      64bf5d33