Update app.py

app.py

@@ -177,6 +177,7 @@ def uploadNote(prompt,num_inference_steps,guidance_scale,timestamp):
 @spaces.GPU(duration=30)
 def generate_30(
     prompt: str,
+    prompt2: str,
     negative_prompt: str = "",
     use_negative_prompt: bool = False,
     style_selection: str = "",
@@ -191,10 +192,30 @@ def generate_30(
     generator = torch.Generator(device='cuda').manual_seed(seed)
     pipe.text_encoder=text_encoder.to(device=device, dtype=torch.bfloat16)
     pipe.text_encoder_2=text_encoder_2.to(device=device, dtype=torch.bfloat16)
+
+    text_inputs1 = tokenizer(
+                    prompt,
+                    padding="max_length",
+                    max_length=77,
+                    truncation=True,
+                    return_tensors="pt",
+    )
+    text_inputs2 = tokenizer(
+                    prompt2,
+                    padding="max_length",
+                    max_length=77,
+                    truncation=True,
+                    return_tensors="pt",
+    )
+    prompt_embedsa = text_encoder(text_input_ids.to(device), output_hidden_states=True)
+    prompt_embedsb = text_encoder(text_input_ids.to(device), output_hidden_states=True)
+    prompt_embeds = torch.cat([prompt_embedsa,prompt_embedsb]).mean(dim=-1)
+
     options = {
-        "prompt": [prompt],
-        "negative_prompt": [negative_prompt],
-        "negative_prompt_2": [neg_prompt_2],
+        #"prompt": prompt,
+        "prompt_embeds": prompt_embeds,
+        "negative_prompt": negative_prompt,
+        "negative_prompt_2": neg_prompt_2,
         "width": width,
         "height": height,
         "guidance_scale": guidance_scale,
@@ -219,6 +240,7 @@ def generate_30(
 @spaces.GPU(duration=60)
 def generate_60(
     prompt: str,
+    prompt2: str,
     negative_prompt: str = "",
     use_negative_prompt: bool = False,
     style_selection: str = "",
@@ -233,10 +255,30 @@ def generate_60(
     generator = torch.Generator(device='cuda').manual_seed(seed)
     pipe.text_encoder=text_encoder.to(device=device, dtype=torch.bfloat16)
     pipe.text_encoder_2=text_encoder_2.to(device=device, dtype=torch.bfloat16)
+
+    text_inputs1 = tokenizer(
+                    prompt,
+                    padding="max_length",
+                    max_length=77,
+                    truncation=True,
+                    return_tensors="pt",
+    )
+    text_inputs2 = tokenizer(
+                    prompt2,
+                    padding="max_length",
+                    max_length=77,
+                    truncation=True,
+                    return_tensors="pt",
+    )
+    prompt_embedsa = text_encoder(text_input_ids.to(device), output_hidden_states=True)
+    prompt_embedsb = text_encoder(text_input_ids.to(device), output_hidden_states=True)
+    prompt_embeds = torch.cat([prompt_embedsa,prompt_embedsb]).mean(dim=-1)
+
     options = {
-        "prompt": [prompt],
-        "negative_prompt": [negative_prompt],
-        "negative_prompt_2": [neg_prompt_2],
+        #"prompt": prompt,
+        "prompt_embeds": prompt_embeds,
+        "negative_prompt": negative_prompt,
+        "negative_prompt_2": neg_prompt_2,
         "width": width,
         "height": height,
         "guidance_scale": guidance_scale,
@@ -261,6 +303,7 @@ def generate_60(
 @spaces.GPU(duration=90)
 def generate_90(
     prompt: str,
+    prompt2: str,
     negative_prompt: str = "",
     use_negative_prompt: bool = False,
     style_selection: str = "",
@@ -275,10 +318,30 @@ def generate_90(
     generator = torch.Generator(device='cuda').manual_seed(seed)
     pipe.text_encoder=text_encoder.to(device=device, dtype=torch.bfloat16)
     pipe.text_encoder_2=text_encoder_2.to(device=device, dtype=torch.bfloat16)
+
+    text_inputs1 = tokenizer(
+                    prompt,
+                    padding="max_length",
+                    max_length=77,
+                    truncation=True,
+                    return_tensors="pt",
+    )
+    text_inputs2 = tokenizer(
+                    prompt2,
+                    padding="max_length",
+                    max_length=77,
+                    truncation=True,
+                    return_tensors="pt",
+    )
+    prompt_embedsa = text_encoder(text_input_ids.to(device), output_hidden_states=True)
+    prompt_embedsb = text_encoder(text_input_ids.to(device), output_hidden_states=True)
+    prompt_embeds = torch.cat([prompt_embedsa,prompt_embedsb]).mean(dim=-1)
+
     options = {
-        "prompt": [prompt],
-        "negative_prompt": [negative_prompt],
-        "negative_prompt_2": [neg_prompt_2],
+        #"prompt": prompt,
+        "prompt_embeds": prompt_embeds,
+        "negative_prompt": negative_prompt,
+        "negative_prompt_2": neg_prompt_2,
         "width": width,
         "height": height,
         "guidance_scale": guidance_scale,
@@ -338,6 +401,13 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             placeholder="Enter your prompt",
             container=False,
         )
+        prompt2 = gr.Text(
+            label="Prompt 2",
+            show_label=False,
+            max_lines=1,
+            placeholder="Enter your prompt",
+            container=False,
+        )
         run_button_30 = gr.Button("Run 30 Seconds", scale=0)
         run_button_60 = gr.Button("Run 60 Seconds", scale=0)
         run_button_90 = gr.Button("Run 90 Seconds", scale=0)
@@ -416,6 +486,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
         fn=generate_30,
         inputs=[
             prompt,
+            prompt2,
             negative_prompt,
             use_negative_prompt,
             style_selection,
@@ -435,6 +506,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
         fn=generate_60,
         inputs=[
             prompt,
+            prompt2,
             negative_prompt,
             use_negative_prompt,
             style_selection,
@@ -454,6 +526,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
         fn=generate_90,
         inputs=[
             prompt,
+            prompt2,
             negative_prompt,
             use_negative_prompt,
             style_selection,