46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
import torch
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from model.light_module import LightModule
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from model.light_module import ModelRunner
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import numpy as np
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import dataset.dataset as ds
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if __name__ == "__main__":
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# checkpoint_path = "log/bigger/version_0/checkpoints/epoch=72-step=360328.ckpt"
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# checkpoint_path = "log/bigger/version_4/checkpoints/epoch=81-step=64288.ckpt"
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checkpoint_path = "log/bigger/version_8/checkpoints/epoch=14-step=67455.ckpt"
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qwen = LightModule.load_from_checkpoint(checkpoint_path=checkpoint_path)
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qwen.eval()
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conf = qwen.config
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torch.manual_seed(conf.seed)
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np.random.seed(conf.seed)
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torch.cuda.manual_seed_all(conf.seed)
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runner = ModelRunner(qwen.llm)
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val = ds.InitValDataset(conf).dataset
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md = val.meaning_dataset
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map = md.get_meaning_map()
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# seq:844
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# seq:849
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# seq:991
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# seq:995
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node = map.get_nodetree(995)
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item, l, rank_idx, rank_all = map.get_sequence(995)
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print("len of seq:" + str(len(item)))
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for i in range(1, len(item)):
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itemm = [item[:i]]
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batch = torch.tensor([item[:i]], dtype=torch.int64)
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sorted_logits, sorted_indices = runner.ChatTokens(batch, sample=False)
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next_token = sorted_indices.detach().cpu().numpy()[0][0]
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if item[i] != next_token:
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node.set_seq_prop(i, "ERR_" + str(next_token))
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print(str(item[i]) + " " + str(next_token) + " ERROR")
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node.print()
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