def test_linear_chain_crf(self):
program = Program()
with program_guard(program, startup_program=Program()):
label_dict_len = 10
images = layers.data(name='pixel', shape=[784], dtype='float32')
label = layers.data(name='label', shape=[1], dtype='int32')
hidden = layers.fc(input=images, size=128)
crf = layers.linear_chain_crf(input=hidden,
label=label,
param_attr=ParamAttr(name="crfw"))
crf_decode = layers.crf_decoding(input=hidden,
param_attr=ParamAttr(name="crfw"))
layers.chunk_eval(input=crf_decode,
label=label,
chunk_scheme="IOB",
num_chunk_types=(label_dict_len - 1) // 2)
self.assertFalse(crf is None)
self.assertFalse(crf_decode is None)
print(str(program))
def test_linear_chain_crf(self):
program = Program()
with program_guard(program, startup_program=Program()):
label_dict_len = 10
images = layers.data(name='pixel', shape=[784], dtype='float32')
label = layers.data(name='label', shape=[1], dtype='int32')
hidden = layers.fc(input=images, size=128)
crf = layers.linear_chain_crf(
input=hidden, label=label, param_attr=ParamAttr(name="crfw"))
crf_decode = layers.crf_decoding(
input=hidden, param_attr=ParamAttr(name="crfw"))
layers.chunk_eval(
input=crf_decode,
label=label,
chunk_scheme="IOB",
num_chunk_types=(label_dict_len - 1) / 2)
self.assertFalse(crf is None)
self.assertFalse(crf_decode is None)
print(str(program))