本文整理汇总了Python中torchtext.vocab.items方法的典型用法代码示例。如果您正苦于以下问题：Python vocab.items方法的具体用法？Python vocab.items怎么用？Python vocab.items使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类torchtext.vocab的用法示例。
在下文中一共展示了vocab.items方法的10个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _load_fields
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def _load_fields(dataset, data_type, opt, checkpoint):
if checkpoint is not None:
logger.info('Loading vocab from checkpoint at %s.' % opt.train_from)
fields = load_fields_from_vocab(
checkpoint['vocab'], data_type)
else:
fields = load_fields_from_vocab(
torch.load(opt.data + '.vocab.pt'), data_type)
fields = dict([(k, f) for (k, f) in fields.items()
if k in dataset.examples[0].__dict__])
if data_type == 'text':
logger.info(' * vocabulary size. source = %d; target = %d; template = %d'%
(len(fields['src'].vocab), len(fields['tgt'].vocab),len(fields['template'].vocab)))
else:
logger.info(' * vocabulary size. target = %d' %
(len(fields['tgt'].vocab)))
return fields 示例2: load_fields_from_vocab
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def load_fields_from_vocab(vocab, data_type="text"):
"""
Load Field objects from `vocab.pt` file.
"""
vocab = dict(vocab)
n_src_features = len(collect_features(vocab, 'src'))
n_tgt_features = len(collect_features(vocab, 'tgt'))
fields = get_fields(data_type, n_src_features, n_tgt_features)
for k, v in vocab.items():
# Hack. Can't pickle defaultdict :(
v.stoi = defaultdict(lambda: 0, v.stoi)
fields[k].vocab = v
return fields 示例3: save_fields_to_vocab
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def save_fields_to_vocab(fields):
"""
Save Vocab objects in Field objects to `vocab.pt` file.
"""
vocab = []
for k, f in fields.items():
if f is not None and 'vocab' in f.__dict__:
f.vocab.stoi = dict(f.vocab.stoi)
vocab.append((k, f.vocab))
return vocab 示例4: join_dicts
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def join_dicts(*args):
"""
args: dictionaries with disjoint keys
returns: a single dictionary that has the union of these keys
"""
return dict(chain(*[d.items() for d in args])) 示例5: load_fields
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def load_fields(vocab):
vocab = dict(vocab)
fields = TableDataset.get_fields()
for k, v in vocab.items():
# Hack. Can't pickle defaultdict :(
v.stoi = defaultdict(lambda: 0, v.stoi)
fields[k].vocab = v
return fields 示例6: save_vocab
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def save_vocab(fields):
vocab = []
for k, f in fields.items():
if 'vocab' in f.__dict__:
f.vocab.stoi = dict(f.vocab.stoi)
vocab.append((k, f.vocab))
return vocab 示例7: load_fields
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def load_fields(vocab):
vocab = dict(vocab)
fields = ONMTDataset.get_fields(len(ONMTDataset.collect_features(vocab)))
for k, v in vocab.items():
# Hack. Can't pickle defaultdict :(
v.stoi = defaultdict(lambda: 0, v.stoi)
fields[k].vocab = v
return fields 示例8: save_fields_to_vocab
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def save_fields_to_vocab(fields):
"""
Save Vocab objects in Field objects to `vocab.pt` file.
"""
vocab = []
for k, f in fields.items():
if 'vocab' in f.__dict__:
f.vocab.stoi = dict(f.vocab.stoi)
vocab.append((k, f.vocab))
return vocab 示例9: _join_dicts
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def _join_dicts(*args):
"""
Args:
dictionaries with disjoint keys.
Returns:
a single dictionary that has the union of these keys.
"""
return dict(chain(*[d.items() for d in args])) 示例10: filter_counter
# 需要导入模块: from torchtext import vocab [as 别名]
# 或者: from torchtext.vocab import items [as 别名]
def filter_counter(freqs, min_freq):
cnt = Counter()
for k, v in freqs.items():
if (min_freq is None) or (v >= min_freq):
cnt[k] = v
return cnt