chages

app.py

@@ -28,27 +28,53 @@ with gr.Blocks() as app:
             with gr.Row():
                 search_text = gr.Textbox(value=fn_query_on_load, placeholder='Search..', label=None)
 
-            with gr.Row():
-                submit_btn = gr.Button("Submit", variant='primary')
-                clear_btn = gr.ClearButton()
 
     with gr.Row(visible=True):
-        output_images = gr.Gallery(value=fn_refresh, interactive=False, every=5)
+        with gr.Column():
+            with gr.Row():
+                out1 = gr.Image(interactive=False, label='Oil Painting')
+                submit1 = gr.Button("submit", variant='primary')
+
+        with gr.Column():
+            with gr.Row():
+                out2 = gr.Image(interactive=False, label='Low Poly HD Style')
+                submit2 = gr.Button("submit", variant='primary')
 
+        with gr.Column():
+            with gr.Row():
+                out3 = gr.Image(interactive=False, label='Matrix style')
+                submit3 = gr.Button("submit", variant='primary')
+
+
+        with gr.Column():
+            with gr.Row():
+                out4 = gr.Image(interactive=False, label='Dreamy Painting')
+                submit4 = gr.Button("submit", variant='primary')
+
+        with gr.Column():
+            with gr.Row():
+                out5 = gr.Image(interactive=False, label='Depth Map Style')
+                submit5 = gr.Button("submit", variant='primary')
+
+
+    with gr.Row(visible=True):
+        clear_btn = gr.ClearButton()
 
     def clear_data():
         return {
-            output_images: None,
+            out1: None,
+            out2: None,
+            out3: None,
+            out4: None,
+            out5: None,
             search_text: None
         }
 
 
-    clear_btn.click(clear_data, None, [output_images, search_text])
+    clear_btn.click(clear_data, None, [out1, out2, out3, out4, out5, search_text])
 
 
-    def func_generate(query):
-        global is_clicked
-        is_clicked = True
+    def func_generate(query, concept_idx, seed):
         prompt = query + ' in the style of bulb'
         text_input = tokenizer(prompt, padding="max_length", max_length=tokenizer.model_max_length, truncation=True,
                                return_tensors="pt")
@@ -58,44 +84,63 @@ with gr.Blocks() as app:
         position_ids = text_encoder.text_model.embeddings.position_ids[:, :77]
         position_embeddings = pos_emb_layer(position_ids)
 
-        s = 0
-        for i in range(5):
-            token_embeddings = token_emb_layer(input_ids)
-            # The new embedding - our special birb word
-            replacement_token_embedding = concept_embeds[i].to(torch_device)
+        s = seed
+
+        token_embeddings = token_emb_layer(input_ids)
+        # The new embedding - our special birb word
+        replacement_token_embedding = concept_embeds[concept_idx].to(torch_device)
 
-            # Insert this into the token embeddings
-            token_embeddings[0, torch.where(input_ids[0] == 22373)] = replacement_token_embedding.to(torch_device)
+        # Insert this into the token embeddings
+        token_embeddings[0, torch.where(input_ids[0] == 22373)] = replacement_token_embedding.to(torch_device)
 
-            # Combine with pos embs
-            input_embeddings = token_embeddings + position_embeddings
+        # Combine with pos embs
+        input_embeddings = token_embeddings + position_embeddings
 
-            #  Feed through to get final output embs
-            modified_output_embeddings = get_output_embeds(input_embeddings)
+        #  Feed through to get final output embs
+        modified_output_embeddings = get_output_embeds(input_embeddings)
 
-            # And generate an image with this:
+        # And generate an image with this:
 
-            s = random.randint(s + 1, s + 30)
-            g = torch.manual_seed(s)
-            output = generate_with_embs(text_input, modified_output_embeddings, output=out_img_list[i], generator=g)
-            #output_images.append(dict(seed=s, output=output))
+        s = random.randint(s + 1, s + 30)
+        g = torch.manual_seed(s)
+        return generate_with_embs(text_input, modified_output_embeddings, generator=g)
+
+
+    submit1.click(
+        func_generate,
+        [search_text, 0, 0],
+        out1
+    )
 
-        is_clicked = False
+    submit2.click(
+        func_generate,
+        [search_text, 1, 30],
+        out2
+    )
 
-        return None
+    submit3.click(
+        func_generate,
+        [search_text, 2, 60],
+        out3
+    )
 
+    submit4.click(
+        func_generate,
+        [search_text, 3, 90],
+        out4
+    )
 
-    submit_btn.click(
+    submit5.click(
         func_generate,
-        [search_text],
-        None
+        [search_text, 4, 120],
+        out5
     )
 
 
 '''
 Launch the app
 '''
-app.queue.launch(share=True)
+app.launch()