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2 changes: 1 addition & 1 deletion src/diffusers/models/transformer_2d.py
Original file line number Diff line number Diff line change
Expand Up @@ -225,7 +225,7 @@ def forward(
hidden_states ( When discrete, `torch.LongTensor` of shape `(batch size, num latent pixels)`.
When continuous, `torch.FloatTensor` of shape `(batch size, channel, height, width)`): Input
hidden_states
encoder_hidden_states ( `torch.LongTensor` of shape `(batch size, encoder_hidden_states dim)`, *optional*):
encoder_hidden_states ( `torch.FloatTensor` of shape `(batch size, sequence len, embed dims)`, *optional*):
Conditional embeddings for cross attention layer. If not given, cross-attention defaults to
self-attention.
timestep ( `torch.long`, *optional*):
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