def make_dataset_from_selfplay(data_extracts):
"""
Returns an iterable of tf.Examples.
Args:
data_extracts: An iterable of (position, pi, result) tuples
"""
f = dual_net.get_features()
tf_examples = (make_tf_example(features_lib.extract_features(pos, f), pi,
result)
for pos, pi, result in data_extracts)
return tf_examples
def test_make_dataset_from_sgf(self):
with tempfile.NamedTemporaryFile() as sgf_file, \
tempfile.NamedTemporaryFile() as record_file:
sgf_file.write(TEST_SGF.encode('utf8'))
sgf_file.seek(0)
preprocessing.make_dataset_from_sgf(sgf_file.name,
record_file.name)
recovered_data = self.extract_data(record_file.name)
start_pos = go.Position()
first_move = coords.from_sgf('fd')
next_pos = start_pos.play_move(first_move)
second_move = coords.from_sgf('cf')
f = dual_net.get_features()
expected_data = [
(features.extract_features(start_pos, f),
preprocessing._one_hot(coords.to_flat(first_move)), -1),
(features.extract_features(next_pos, f),
preprocessing._one_hot(coords.to_flat(second_move)), -1)
]
self.assertEqualData(expected_data, recovered_data)
def _make_tf_example_from_pwc(position_w_context):
f = dual_net.get_features()
features = features_lib.extract_features(position_w_context.position, f)
pi = _one_hot(coords.to_flat(position_w_context.next_move))
value = position_w_context.result
return make_tf_example(features, pi, value)
