def add(self, name, lines, reload_cache=False):
hash_fn = join(self.cache, name + '.hash')
old_hsh = None
if isfile(hash_fn):
with open(hash_fn, 'rb') as g:
old_hsh = g.read()
min_ver = splitext(padatious.__version__)[0]
new_hsh = lines_hash([min_ver] + lines)
if reload_cache or old_hsh != new_hsh:
self.objects_to_train.append(self.cls(name=name, hsh=new_hsh))
else:
self.objects.append(self.cls.from_file(name=name, folder=self.cache))
self.train_data.add_lines(name, lines)
def add(self, name, lines, reload_cache=False, must_train=True):
# special case: load persisted (aka. cached) resource (i.e.
# entity or intent) from file into memory data structures
if not must_train:
self.objects.append(
self.cls.from_file(name=name, folder=self.cache))
# general case: load resource (entity or intent) to training queue
# or if no change occurred to memory data structures
else:
hash_fn = join(self.cache, name + '.hash')
old_hsh = None
if isfile(hash_fn):
with open(hash_fn, 'rb') as g:
old_hsh = g.read()
min_ver = splitext(padatious.__version__)[0]
new_hsh = lines_hash([min_ver] + lines)
if reload_cache or old_hsh != new_hsh:
self.objects_to_train.append(self.cls(name=name, hsh=new_hsh))
else:
self.objects.append(
self.cls.from_file(name=name, folder=self.cache))
self.train_data.add_lines(name, lines)
def test_lines_hash():
assert lines_hash(['word1', 'word2']) != lines_hash(['word2', 'word1'])
assert lines_hash(['word1', 'word2']) != lines_hash(['word1', 'word1'])