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Runtime error
Ahsen Khaliq
commited on
Commit
β’
2041e1f
1
Parent(s):
1de2d14
Update app.py
Browse files
app.py
CHANGED
@@ -357,7 +357,7 @@ def inference(text):
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losses_str = ', '.join(f'{loss.item():g}' for loss in losses)
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tqdm.write(f'i: {i}, loss: {sum(losses).item():g}, losses: {losses_str}')
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out = synth(z)
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TF.to_pil_image(out[0].cpu()).save('progress.png')
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#display.display(display.Image('progress.png'))
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def ascend_txt():
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@@ -374,13 +374,13 @@ def inference(text):
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result.append(prompt(iii))
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img = np.array(out.mul(255).clamp(0, 255)[0].cpu().detach().numpy().astype(np.uint8))[:,:,:]
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img = np.transpose(img, (1, 2, 0))
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imageio.imwrite('./steps/' + str(i) + '.png', np.array(img))
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return result
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def train(i):
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opt.zero_grad()
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lossAll = ascend_txt()
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if i % args.display_freq == 0:
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checkin(i, lossAll)
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@@ -389,19 +389,20 @@ def inference(text):
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opt.step()
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with torch.no_grad():
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z.copy_(z.maximum(z_min).minimum(z_max))
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i = 0
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try:
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with tqdm() as pbar:
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while True:
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train(i)
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if i == max_iterations:
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break
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i += 1
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pbar.update()
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except KeyboardInterrupt:
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pass
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return
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title = "VQGAN + CLIP"
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description = "Gradio demo for VQGAN + CLIP. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
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@@ -410,7 +411,7 @@ article = "<p style='text-align: center'>Originally made by Katherine Crowson (h
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gr.Interface(
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inference,
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gr.inputs.Textbox(label="Input"),
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gr.outputs.Image(type="
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title=title,
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description=description,
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article=article,
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losses_str = ', '.join(f'{loss.item():g}' for loss in losses)
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tqdm.write(f'i: {i}, loss: {sum(losses).item():g}, losses: {losses_str}')
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out = synth(z)
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+
#TF.to_pil_image(out[0].cpu()).save('progress.png')
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#display.display(display.Image('progress.png'))
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def ascend_txt():
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result.append(prompt(iii))
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img = np.array(out.mul(255).clamp(0, 255)[0].cpu().detach().numpy().astype(np.uint8))[:,:,:]
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img = np.transpose(img, (1, 2, 0))
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#imageio.imwrite('./steps/' + str(i) + '.png', np.array(img))
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return result, np.array(img)
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def train(i):
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opt.zero_grad()
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lossAll, image = ascend_txt()
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if i % args.display_freq == 0:
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checkin(i, lossAll)
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opt.step()
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with torch.no_grad():
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z.copy_(z.maximum(z_min).minimum(z_max))
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return image
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i = 0
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try:
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with tqdm() as pbar:
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while True:
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image = train(i)
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if i == max_iterations:
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break
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i += 1
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pbar.update()
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except KeyboardInterrupt:
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pass
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return image
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title = "VQGAN + CLIP"
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description = "Gradio demo for VQGAN + CLIP. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
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gr.Interface(
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inference,
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gr.inputs.Textbox(label="Input"),
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gr.outputs.Image(type="numpy", label="Output"),
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title=title,
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description=description,
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article=article,
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