测试错误

[niliusha123]

您好：我用python3.6，训练出现下面情况

• Building prefix dict from the default dictionary ...
• Loading model from cache /tmp/jieba.cache
• Loading model cost 0.699 seconds.
• Prefix dict has been built succesfully.
• 开始训练模型！！！
• 13724it [00:00, 133884.01it/s]
• Python 3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 01:22:34)
• [GCC 7.3.0] on linux
• Type "help", "copyright", "credits" or "license" for more information.
• (InteractiveConsole)

测试时报错如下

• Building prefix dict from the default dictionary ...
• Loading model from cache /tmp/jieba.cache
• Loading model cost 0.692 seconds.
• Prefix dict has been built succesfully.
• 2019-06-10 23:07:51.152866: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
• 2019-06-10 23:07:52.790032: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
• name: GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
• pciBusID: 0000:02:00.0
• totalMemory: 10.73GiB freeMemory: 10.53GiB
• 2019-06-10 23:07:52.790099: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
• 2019-06-10 23:07:53.229309: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
• 2019-06-10 23:07:53.229363: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
• 2019-06-10 23:07:53.229376: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
• 2019-06-10 23:07:53.229666: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10168 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:02:00.0, compute capability: 7.5)
• WARNING:tensorflow:From /data/proj/Captcha/ner-slot_filling/models/model.py:385: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.
• Instructions for updating:
• Future major versions of TensorFlow will allow gradients to flow
• into the labels input on backprop by default.
• See tf.nn.softmax_cross_entropy_with_logits_v2.
• /home/jiang.li/.local/lib/python3.6/site-packages/tensorflow/python/ops/gradients_impl.py:112: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
• "Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
• 2019-06-10 23:07:55,057 - /data/proj/Captcha/ner-slot_filling/log/train.log - INFO - Created model with fresh parameters.
• Loading pretrained embeddings from /Users/gaoquan/Documents/ml-learning/ner-learning/NER_medical_records/assets/cooked_corpus/vec.txt...
• Traceback (most recent call last):
• File "train_evaluate.py", line 251, in

• main(args)
  

• File "train_evaluate.py", line 247, in main

• evaluate_line()
  

• File "train_evaluate.py", line 230, in evaluate_line

• load_word2vec, config, id_to_char, logger)
  

• File "/data/proj/Captcha/ner-slot_filling/utils/utils.py", line 158, in create_model

• emb_weights = load_vec(config["emb_file"], id_to_char, config["char_dim"], emb_weights)
  

• File "/data/proj/Captcha/ner-slot_filling/utils/data_utils.py", line 172, in load_word2vec

• for i, line in enumerate(codecs.open(emb_path, 'r', 'utf-8')):
  

• File "/home/jiang.li/ENTER/envs/pytorch/lib/python3.6/codecs.py", line 897, in open

• file = builtins.open(filename, mode, buffering)
  

• FileNotFoundError: [Errno 2] No such file or directory: '/Users/gaoquan/Documents/ml-learning/ner-learning/NER_medical_records/assets/cooked_corpus/vec.txt'

请问该如何修改，谢谢

[hopegithub]

在目录configs下，有个文件config_file，修改其配置为：“emb_file”:"./assets/cooked_corpus/vec.txt"

[hopegithub]

@GaoQ1 这里有对应的论文没有呢

[niliusha123]

在目录configs下，有个文件config_file，修改其配置为：“emb_file”:"./assets/cooked_corpus/vec.txt"

多谢，