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modeling_deepseekocr.py
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@ -945,6 +945,17 @@ class DeepseekOCRForCausalLM(DeepseekV2ForCausalLM):
use_cache = True
)
if '<image>' in conversation[0]['content'] and eval_mode:
outputs = tokenizer.decode(output_ids[0, input_ids.unsqueeze(0).cuda().shape[1]:])
stop_str = '<｜end▁of▁sentence｜>'
if outputs.endswith(stop_str):
outputs = outputs[:-len(stop_str)]
# re_match
outputs = outputs.strip()
return outputs
if '<image>' in conversation[0]['content'] and test_compress:
outputs = tokenizer.decode(output_ids[0, input_ids.unsqueeze(0).cuda().shape[1]:])
pure_texts_outputs_token_length = len(text_encode(tokenizer, outputs, bos=False, eos=False))
@ -1024,13 +1035,3 @@ class DeepseekOCRForCausalLM(DeepseekV2ForCausalLM):
plt.close()
result.save(f"{output_path}/result_with_boxes.jpg")
if '<image>' in conversation[0]['content'] and eval_mode:
outputs = tokenizer.decode(output_ids[0, input_ids.unsqueeze(0).cuda().shape[1]:])
stop_str = '<｜end▁of▁sentence｜>'
if outputs.endswith(stop_str):
outputs = outputs[:-len(stop_str)]
# re_match
outputs = outputs.strip()
return outputs