From 69e49599a17b9fbf013f1bbf209bf612a69b1255 Mon Sep 17 00:00:00 2001 From: galbria Date: Tue, 28 Oct 2025 08:17:05 +0000 Subject: [PATCH] Refactor FIBO classes to BriaFibo naming convention - Updated class names from FIBO to BriaFibo for consistency across the module. - Modified instances of FIBOEmbedND, FIBOTimesteps, TextProjection, and TimestepProjEmbeddings to reflect the new naming. - Ensured all references in the BriaFiboTransformer2DModel are updated accordingly. --- .../transformers/transformer_bria_fibo.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/src/diffusers/models/transformers/transformer_bria_fibo.py b/src/diffusers/models/transformers/transformer_bria_fibo.py index 68a0765536..714faeda5c 100644 --- a/src/diffusers/models/transformers/transformer_bria_fibo.py +++ b/src/diffusers/models/transformers/transformer_bria_fibo.py @@ -214,7 +214,7 @@ class BriaFiboAttention(torch.nn.Module, AttentionModuleMixin): return self.processor(self, hidden_states, encoder_hidden_states, attention_mask, image_rotary_emb, **kwargs) -class FIBOEmbedND(torch.nn.Module): +class BriaFiboEmbedND(torch.nn.Module): # modified from https://github.com/black-forest-labs/flux/blob/c00d7c60b085fce8058b9df845e036090873f2ce/src/flux/modules/layers.py#L11 def __init__(self, theta: int, axes_dim: List[int]): super().__init__() @@ -297,7 +297,7 @@ class BriaFiboSingleTransformerBlock(nn.Module): return hidden_states -class TextProjection(nn.Module): +class BriaFiboTextProjection(nn.Module): def __init__(self, in_features, hidden_size): super().__init__() self.linear = nn.Linear(in_features=in_features, out_features=hidden_size, bias=False) @@ -393,7 +393,7 @@ class BriaFiboTransformerBlock(nn.Module): return encoder_hidden_states, hidden_states -class FIBOTimesteps(nn.Module): +class BriaFiboTimesteps(nn.Module): def __init__( self, num_channels: int, flip_sin_to_cos: bool, downscale_freq_shift: float, scale: int = 1, time_theta=10000 ): @@ -416,11 +416,11 @@ class FIBOTimesteps(nn.Module): return t_emb -class TimestepProjEmbeddings(nn.Module): +class BriaFiboTimestepProjEmbeddings(nn.Module): def __init__(self, embedding_dim, time_theta): super().__init__() - self.time_proj = FIBOTimesteps( + self.time_proj = BriaFiboTimesteps( num_channels=256, flip_sin_to_cos=True, downscale_freq_shift=0, time_theta=time_theta ) self.timestep_embedder = TimestepEmbedding(in_channels=256, time_embed_dim=embedding_dim) @@ -469,12 +469,12 @@ class BriaFiboTransformer2DModel(ModelMixin, ConfigMixin, PeftAdapterMixin, From self.out_channels = in_channels self.inner_dim = self.config.num_attention_heads * self.config.attention_head_dim - self.pos_embed = FIBOEmbedND(theta=rope_theta, axes_dim=axes_dims_rope) + self.pos_embed = BriaFiboEmbedND(theta=rope_theta, axes_dim=axes_dims_rope) - self.time_embed = TimestepProjEmbeddings(embedding_dim=self.inner_dim, time_theta=time_theta) + self.time_embed = BriaFiboTimestepProjEmbeddings(embedding_dim=self.inner_dim, time_theta=time_theta) if guidance_embeds: - self.guidance_embed = TimestepProjEmbeddings(embedding_dim=self.inner_dim) + self.guidance_embed = BriaFiboTimestepProjEmbeddings(embedding_dim=self.inner_dim) self.context_embedder = nn.Linear(self.config.joint_attention_dim, self.inner_dim) self.x_embedder = torch.nn.Linear(self.config.in_channels, self.inner_dim) @@ -507,7 +507,7 @@ class BriaFiboTransformer2DModel(ModelMixin, ConfigMixin, PeftAdapterMixin, From self.gradient_checkpointing = False caption_projection = [ - TextProjection(in_features=text_encoder_dim, hidden_size=self.inner_dim // 2) + BriaFiboTextProjection(in_features=text_encoder_dim, hidden_size=self.inner_dim // 2) for i in range(self.config.num_layers + self.config.num_single_layers) ] self.caption_projection = nn.ModuleList(caption_projection)