找不到Google Colab笔记本错误文件

Question

我正在Google Colab笔记本中运行下面的代码。我面临与文件未找到错误相关的非常奇怪的问题。“atis.test.pkl”和“atis.train.pkl”都在同一个文件夹中（c:\users\downloads）。代码没有为“atis.train.pkl”抛出错误，但为“atis.test.pkl”抛出错误，它给出了错误“File not Found”

回溯如下：

Done  loading:  ./atis.train.pkl
      samples: 4978    vocab_size:  943


slot count:  129  intent count:   26 Query text: BOS what are the seating capacities of planes between pittsburgh and baltimore EOS Query vector:  [178 916 228 827 750 285 646 686 259 682 215 247 179] Intent label:  capacity Slot text:  O O O O O O O O O B-fromloc.city_name O B-toloc.city_name O Slot vector:  [128, 128, 128, 128, 128, 128, 128, 128, 128, 48, 128, 78, 128]
************************************************************************** Query text: BOS okay i would like to know the type of aircraft used on a flight from cleveland to dallas please EOS Query vector:  [178 653 479 932 545 851 516 827 883 646 196 892 654 180 428 444 304 851  339 688 179] Intent label:  aircraft Slot text:  O O O O O O O O O O O O O O O O B-fromloc.city_name O B-toloc.city_name O O Slot vector:  [128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 48, 128, 78, 128, 128]
************************************************************************** Query text: BOS i 'm planning a trip to pittsburgh and i live in denver can you help me EOS Query vector:  [178 479   3 687 180 870 851 682 215 479 553 482 351 282 938 467 581 179] Intent label:  flight Slot text:  O O O O O O O B-toloc.city_name O O O O B-fromloc.city_name O O O O O Slot vector:  [128, 128, 128, 128, 128, 128, 128, 78, 128, 128, 128, 128, 48, 128, 128, 128, 128, 128]
************************************************************************** Query text: BOS i would like an early morning flight from chicago into seattle on continental airlines EOS Query vector:  [178 479 932 545 214 388 606 428 444 297 497 752 654 325 200 179] Intent label:  flight Slot text:  O O O O O B-depart_time.period_of_day B-depart_time.period_of_day O O B-fromloc.city_name O B-toloc.city_name O B-airline_name I-airline_name O Slot vector:  [128, 128, 128, 128, 128, 33, 33, 128, 128, 48, 128, 78, 128, 2, 83, 128]
************************************************************************** Query text: BOS show me the flights from boston to philadelphia EOS Query vector:  [178 770 581 827 429 444 266 851 678 179] Intent label: flight Slot text:  O O O O O O B-fromloc.city_name O B-toloc.city_name O Slot vector:  [128, 128, 128, 128, 128, 128, 48, 128, 78, 128]
**************************************************************************
--------------------------------------------------------------------------- FileNotFoundError                         Traceback (most recent call last) <ipython-input-24-861a72e5a86c> in <module>()
     70 
     71 # load ATIS testing dataset
---> 72 t2i_test, s2i_test, in2i_test, i2t_test, i2s_test, i2in_test, input_tensor_test, target_tensor_test, query_data_test, intent_data_test, intent_data_label_test, slot_data_test = load_atis('atis.test.pkl')

1 frames <ipython-input-24-861a72e5a86c> in load_ds(fname, verbose)
      6 # load Pickle file
      7 def load_ds(fname, verbose=True):
----> 8     with open(fname, 'rb') as stream:
      9         ds,dicts = pickle.load(stream)
     10     if verbose:

FileNotFoundError: [Errno 2] No such file or directory: './atis.test.pkl'

代码如下：

import pickle
import numpy as np
DATA_DIR="."

# load Pickle file 
def load_ds(fname, verbose=True):
    with open(fname, 'rb') as stream:
        ds,dicts = pickle.load(stream)
    if verbose:
      print('Done  loading: ', fname)
      print('      samples: {:4d}'.format(len(ds['query'])))
      print('   vocab_size: {:4d}'.format(len(dicts['token_ids'])))
      print('   slot count: {:4d}'.format(len(dicts['slot_ids'])))
      print(' intent count: {:4d}'.format(len(dicts['intent_ids'])))
    return ds,dicts

# convert Pickle file to arrays
def load_atis(filename, add_start_end_token=False, verbose=True):
    train_ds, dicts = load_ds(os.path.join(DATA_DIR,filename), verbose)
    t2i, s2i, in2i = map(dicts.get, ['token_ids', 'slot_ids','intent_ids'])
    i2t, i2s, i2in = map(lambda d: {d[k]:k for k in d.keys()}, [t2i,s2i,in2i])
    query, slots, intent =  map(train_ds.get, ['query', 'slot_labels', 'intent_labels'])

    if add_start_end_token:
        i2s[178] = 'BOS'
        i2s[179] = 'EOS'
        s2i['BOS'] = 178
        s2i['EOS'] = 179

    input_tensor = []
    target_tensor = []
    query_data = []
    intent_data = []
    slot_data = []
    to_show = np.random.randint(0, len(query)-1, 5)
    for i in range(len(query)):
        input_tensor.append(query[i])
        slot_text = []
        slot_vector = []
        for j in range(len(query[i])):
            slot_text.append(i2s[slots[i][j]])
            slot_vector.append(slots[i][j])
        if add_start_end_token:
            slot_text[0] = 'BOS'
            slot_vector[0] = 178
            slot_text[-1] = 'EOS'
            slot_vector[-1]= 179
        target_tensor.append(slot_vector)
        q = ' '.join(map(i2t.get, query[i]))
        query_data.append(q.replace('BOS', '').replace('EOS',''))
        intent_data.append(i2in[intent[i][0]])
        slot = ' '.join(slot_text)
        slot_data.append(slot[1:-1])
        if i in to_show and verbose:
          print('Query text:', q)
          print('Query vector: ', query[i])
          print('Intent label: ', i2in[intent[i][0]])
          print('Slot text: ', slot)
          print('Slot vector: ', slot_vector)
          print('*'*74)
    query_data = np.array(query_data)
    intent_data = np.array(intent_data)
    slot_data = np.array(slot_data)
    intent_data_label = np.array(intent).flatten()
    return t2i, s2i, in2i, i2t, i2s, i2in, input_tensor, target_tensor, query_data, intent_data, intent_data_label, slot_data

# load ATIS training dataset
t2i_train, s2i_train, in2i_train, i2t_train, i2s_train, i2in_train, input_tensor_train, target_tensor_train, query_data_train, intent_data_train, intent_data_label_train, slot_data_train = load_atis('atis.train.pkl')

# load ATIS testing dataset
t2i_test, s2i_test, in2i_test, i2t_test, i2s_test, i2in_test, input_tensor_test, target_tensor_test, query_data_test, intent_data_test, intent_data_label_test, slot_data_test = load_atis('atis.test.pkl')

Answer 1

Colab在云虚拟机上运行，无法访问本地文件系统（即c:\users\downloads\等路径）。要访问在Colaboratory中运行的Python脚本中的文件，首先必须将这些文件上载到Colab VM

本笔记本概述了如何从各种来源上传文件：https://colab.research.google.com/notebooks/io.ipynb