def test_text_block():
block = hyperblock_module.TextBlock()
block.set_state(block.get_state())
hp = kerastuner.HyperParameters()
block.build(hp, ak.TextInput())
assert common.name_in_hps('vectorizer', hp)
def assemble(self, input_node):
ratio = self.sw_ratio()
if not isinstance(input_node, node.TextNode):
raise ValueError('The input_node should be a TextNode.')
pretraining = 'random'
if ratio < 1500:
vectorizer = 'ngram'
else:
vectorizer = 'sequence'
if ratio < 15000:
pretraining = 'glove'
return hyperblock.TextBlock(vectorizer=vectorizer,
pretraining=pretraining)(input_node)
