256

app.py

@@ -50,7 +50,7 @@ def kl_divergence(latent1: torch.Tensor, latent2: torch.Tensor) -> torch.Tensor:
     kl_div = F.kl_div(latent1_log_prob, latent2_prob, reduction="batchmean")
     return kl_div
 
-def batch_decode(_z: torch.Tensor, decode, batch_size: int = 10) -> torch.Tensor:
+def batch_decode(_z: torch.Tensor, decode, batch_size: int = 5) -> torch.Tensor:
     num_samples = _z.size(0)
     decoded_batches = []
 
@@ -278,6 +278,7 @@ with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         gr.Markdown("# CrossFlow")
         gr.Markdown("CrossFlow directly transforms text representations into images for text-to-image generation, enabling interpolation in the input text latent space.")
+        # gr.Markdown("CrossFlow directly transforms text representations into images for text-to-image generation, enabling interpolation in the input text latent space.")
 
         with gr.Row():
             prompt1 = gr.Text(