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Update app.py
Browse files
app.py
CHANGED
@@ -31,15 +31,15 @@ def generate(slider_x, slider_y, prompt, seed, iterations, steps,
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print("x_concept_1", x_concept_1, "x_concept_2", x_concept_2)
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if not sorted(slider_x) == sorted([x_concept_1, x_concept_2]):
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avg_diff = clip_slider.find_latent_direction(slider_x[0], slider_x[1], num_iterations=iterations)
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avg_diff[0].to(torch.float16)
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avg_diff[1].to(torch.float16)
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x_concept_1, x_concept_2 = slider_x[0], slider_x[1]
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print("avg_diff[0].dtype", avg_diff[0].dtype)
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if not sorted(slider_y) == sorted([y_concept_1, y_concept_2]):
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avg_diff_2nd = clip_slider.find_latent_direction(slider_y[0], slider_y[1], num_iterations=iterations)
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avg_diff_2nd[0].to(torch.float16)
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avg_diff_2nd[1].to(torch.float16)
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y_concept_1, y_concept_2 = slider_y[0], slider_y[1]
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end_time = time.time()
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print(f"direction time: {end_time - start_time:.2f} ms")
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print("x_concept_1", x_concept_1, "x_concept_2", x_concept_2)
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if not sorted(slider_x) == sorted([x_concept_1, x_concept_2]):
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avg_diff = clip_slider.find_latent_direction(slider_x[0], slider_x[1], num_iterations=iterations)
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avg_diff[0] = avg_diff[0].to(torch.float16)
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avg_diff[1] = avg_diff[1].to(torch.float16)
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x_concept_1, x_concept_2 = slider_x[0], slider_x[1]
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print("avg_diff[0].dtype", avg_diff[0].dtype)
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if not sorted(slider_y) == sorted([y_concept_1, y_concept_2]):
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avg_diff_2nd = clip_slider.find_latent_direction(slider_y[0], slider_y[1], num_iterations=iterations)
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avg_diff_2nd[0] = avg_diff_2nd[0].to(torch.float16)
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avg_diff_2nd[1] = avg_diff_2nd[1].to(torch.float16)
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y_concept_1, y_concept_2 = slider_y[0], slider_y[1]
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end_time = time.time()
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print(f"direction time: {end_time - start_time:.2f} ms")
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