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Update app.py
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app.py
CHANGED
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@@ -81,8 +81,10 @@ def generate_answers(img=None, aud = None, q = None, max_tokens = 30):
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predicted_word_token_logits = model_output_logits[:, -1, :].unsqueeze(1)
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predicted_word_token = torch.argmax(predicted_word_token_logits, dim = -1)
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predicted_caption[:, pos] = predicted_word_token.view(1,-1).to('cpu')
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next_token_embeds = phi2_model.model.embed_tokens(predicted_word_token)
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combined_embeds = torch.cat([combined_embeds, next_token_embeds], dim=1)
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predicted_captions_decoded = tokenizer.batch_decode(predicted_caption,ignore_index = 50256)[0]
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predicted_captions_decoded = predicted_captions_decoded.replace("<|endoftext|>","")
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return predicted_captions_decoded
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@@ -112,4 +114,4 @@ with gr.Blocks() as demo:
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if __name__ == "__main__":
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demo.launch(share=True)
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predicted_word_token_logits = model_output_logits[:, -1, :].unsqueeze(1)
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predicted_word_token = torch.argmax(predicted_word_token_logits, dim = -1)
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predicted_caption[:, pos] = predicted_word_token.view(1,-1).to('cpu')
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print(predicted_caption)
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next_token_embeds = phi2_model.model.embed_tokens(predicted_word_token)
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combined_embeds = torch.cat([combined_embeds, next_token_embeds], dim=1)
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print("combined_embeds", combined_embeds.shape)
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predicted_captions_decoded = tokenizer.batch_decode(predicted_caption,ignore_index = 50256)[0]
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predicted_captions_decoded = predicted_captions_decoded.replace("<|endoftext|>","")
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return predicted_captions_decoded
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if __name__ == "__main__":
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demo.launch(share=True, debug=True)
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