Buckets:
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| Input <code>hidden_states</code>.`,name:"hidden_states"},{anchor:"diffusers.BriaFiboTransformer2DModel.forward.encoder_hidden_states",description:`<strong>encoder_hidden_states</strong> (<code>torch.FloatTensor</code> of shape <code>(batch size, sequence_len, embed_dims)</code>) — | |
| Conditional embeddings (embeddings computed from the input conditions such as prompts) to use.`,name:"encoder_hidden_states"},{anchor:"diffusers.BriaFiboTransformer2DModel.forward.pooled_projections",description:`<strong>pooled_projections</strong> (<code>torch.FloatTensor</code> of shape <code>(batch_size, projection_dim)</code>) — Embeddings projected | |
| from the embeddings of input conditions.`,name:"pooled_projections"},{anchor:"diffusers.BriaFiboTransformer2DModel.forward.timestep",description:`<strong>timestep</strong> ( <code>torch.LongTensor</code>) — | |
| Used to indicate denoising step.`,name:"timestep"},{anchor:"diffusers.BriaFiboTransformer2DModel.forward.joint_attention_kwargs",description:`<strong>joint_attention_kwargs</strong> (<code>dict</code>, <em>optional</em>) — | |
| A kwargs dictionary that if specified is passed along to the <code>AttentionProcessor</code> as defined under | |
| <code>self.processor</code> in | |
| <a href="https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/attention_processor.py" rel="nofollow">diffusers.models.attention_processor</a>.`,name:"joint_attention_kwargs"},{anchor:"diffusers.BriaFiboTransformer2DModel.forward.return_dict",description:`<strong>return_dict</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>True</code>) — | |
| Whether or not to return a <code>~models.transformer_2d.Transformer2DModelOutput</code> instead of a plain | |
| tuple.`,name:"return_dict"}],source:"https://github.com/huggingface/diffusers/blob/vr_12849/src/diffusers/models/transformers/transformer_bria_fibo.py#L513",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p>If <code>return_dict</code> is True, an <code>~models.transformer_2d.Transformer2DModelOutput</code> is returned, otherwise a | |
| <code>tuple</code> where the first element is the sample tensor.</p> | |
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