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	Update app.py
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        app.py
    CHANGED
    
    | @@ -31,15 +31,15 @@ def generate(slider_x, slider_y, prompt, seed, iterations, steps, | |
| 31 | 
             
                print("x_concept_1", x_concept_1, "x_concept_2", x_concept_2)
         | 
| 32 | 
             
                if not sorted(slider_x) == sorted([x_concept_1, x_concept_2]):
         | 
| 33 | 
             
                    avg_diff = clip_slider.find_latent_direction(slider_x[0], slider_x[1], num_iterations=iterations)
         | 
| 34 | 
            -
                    avg_diff[0].to(torch.float16)
         | 
| 35 | 
            -
                    avg_diff[1].to(torch.float16)
         | 
| 36 | 
             
                    x_concept_1, x_concept_2 = slider_x[0], slider_x[1]
         | 
| 37 |  | 
| 38 | 
             
                print("avg_diff[0].dtype", avg_diff[0].dtype)
         | 
| 39 | 
             
                if not sorted(slider_y) == sorted([y_concept_1, y_concept_2]):
         | 
| 40 | 
             
                    avg_diff_2nd = clip_slider.find_latent_direction(slider_y[0], slider_y[1], num_iterations=iterations)
         | 
| 41 | 
            -
                    avg_diff_2nd[0].to(torch.float16)
         | 
| 42 | 
            -
                    avg_diff_2nd[1].to(torch.float16)
         | 
| 43 | 
             
                    y_concept_1, y_concept_2 = slider_y[0], slider_y[1]
         | 
| 44 | 
             
                end_time = time.time()
         | 
| 45 | 
             
                print(f"direction time: {end_time - start_time:.2f} ms")
         | 
|  | |
| 31 | 
             
                print("x_concept_1", x_concept_1, "x_concept_2", x_concept_2)
         | 
| 32 | 
             
                if not sorted(slider_x) == sorted([x_concept_1, x_concept_2]):
         | 
| 33 | 
             
                    avg_diff = clip_slider.find_latent_direction(slider_x[0], slider_x[1], num_iterations=iterations)
         | 
| 34 | 
            +
                    avg_diff[0] = avg_diff[0].to(torch.float16)
         | 
| 35 | 
            +
                    avg_diff[1] = avg_diff[1].to(torch.float16)
         | 
| 36 | 
             
                    x_concept_1, x_concept_2 = slider_x[0], slider_x[1]
         | 
| 37 |  | 
| 38 | 
             
                print("avg_diff[0].dtype", avg_diff[0].dtype)
         | 
| 39 | 
             
                if not sorted(slider_y) == sorted([y_concept_1, y_concept_2]):
         | 
| 40 | 
             
                    avg_diff_2nd = clip_slider.find_latent_direction(slider_y[0], slider_y[1], num_iterations=iterations)
         | 
| 41 | 
            +
                    avg_diff_2nd[0] = avg_diff_2nd[0].to(torch.float16)
         | 
| 42 | 
            +
                    avg_diff_2nd[1] = avg_diff_2nd[1].to(torch.float16)
         | 
| 43 | 
             
                    y_concept_1, y_concept_2 = slider_y[0], slider_y[1]
         | 
| 44 | 
             
                end_time = time.time()
         | 
| 45 | 
             
                print(f"direction time: {end_time - start_time:.2f} ms")
         | 
