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from caffe2.python import workspace, crf
from caffe2.python.cnn import CNNModelHelper
from caffe2.python.crf_predict import crf_update_predictions
from caffe2.python.test_util import TestCase
import hypothesis.strategies as st
from hypothesis import given, settings
import numpy as np
class TestCrfDecode(TestCase):
@given(num_tags=st.integers(2, 4), num_words=st.integers(2, 15))
@settings(deadline=2000)
def test_crf_viterbi(self, num_tags, num_words):
model = CNNModelHelper(name='external')
predictions = np.random.randn(num_words, num_tags).astype(np.float32)
transitions = np.random.uniform(
low=-1, high=1, size=(num_tags + 2, num_tags + 2)
).astype(np.float32)
predictions_blob, transitions_blob = (
model.net.AddExternalInputs('predictions', 'crf_transitions')
)
workspace.FeedBlob(str(transitions_blob), transitions)
workspace.FeedBlob(str(predictions_blob), predictions)
crf_layer = crf.CRFWithLoss(model, num_tags, transitions_blob)
updated_predictions = crf_update_predictions(
model, crf_layer, predictions_blob
)
ref_predictions = crf_layer.update_predictions(predictions_blob)
workspace.RunNetOnce(model.param_init_net)
workspace.RunNetOnce(model.net)
updated_predictions = workspace.FetchBlob(str(updated_predictions))
ref_predictions = workspace.FetchBlob(str(ref_predictions))
np.testing.assert_allclose(
updated_predictions,
ref_predictions,
atol=1e-4, rtol=1e-4, err_msg='Mismatch in CRF predictions'
)
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