def create_frame_prediction_pairs(self):
return [
FramePredictionPair(
CompositionalMetricReporter.tree_to_metric_node(pred_tree),
CompositionalMetricReporter.tree_to_metric_node(target_tree),
) for pred_tree, target_tree in zip(self.all_pred_trees,
self.all_target_trees)
]
def aggregate_preds(self, new_batch, context=None):
if new_batch is None:
return
tree_preds = new_batch[0] # bsz X beam_size X seq_len
length_preds = new_batch[1]
target_vocab = self.tensorizers["trg_seq_tokens"].vocab
target_pad_token = target_vocab.get_pad_index()
target_bos_token = target_vocab.get_bos_index()
target_eos_token = target_vocab.get_eos_index()
cleaned_preds = [
self._remove_tokens(
pred, [target_pad_token, target_eos_token, target_bos_token])
for pred in self._make_simple_list(tree_preds)
]
self.aggregate_data(self.all_preds, cleaned_preds)
pred_trees = [
self.stringify_annotation_tree(pred[0], target_vocab)
for pred in cleaned_preds
]
beam_pred_trees = [[
CompositionalMetricReporter.tree_to_metric_node(
self.stringify_annotation_tree(pred, target_vocab))
for pred in beam
] for beam in cleaned_preds]
top_non_invalid_trees = [
self.get_annotation_from_string(
self.get_top_non_invalid(
[stringify(pred, target_vocab) for pred in beam]))
for beam in cleaned_preds
]
top_extracted_trees = [
self.get_annotation_from_string(
self.get_top_extract(
[stringify(pred, target_vocab) for pred in beam]))
for beam in cleaned_preds
]
self.aggregate_data(self.all_pred_trees, pred_trees)
self.aggregate_data(self.all_target_length_preds, length_preds)
self.aggregate_data(self.all_beam_preds, beam_pred_trees)
self.aggregate_data(self.all_top_non_invalid, top_non_invalid_trees)
self.aggregate_data(self.all_top_extract, top_extracted_trees)
def test_tree_to_metric_node(self):
TEXT_EXAMPLES = [
(
"[IN:alarm/set_alarm repeat the [SL:datetime 3 : 00 pm ] "
+ "[SL:alarm/name alarm ] [SL:datetime for Sunday august 12th ] ] ",
Node(
label="IN:alarm/set_alarm",
span=Span(start=0, end=49),
children={
Node(label="SL:datetime", span=Span(start=11, end=20)),
Node(label="SL:alarm/name", span=Span(start=21, end=26)),
Node(label="SL:datetime", span=Span(start=27, end=49)),
},
),
),
(
"[IN:calling/call_friend call [SL:person moms ] cellphone ]",
Node(
label="IN:calling/call_friend",
span=Span(start=0, end=19),
children={Node(label="SL:person", span=Span(start=5, end=9))},
),
),
(
"[IN:GET_DIRECTIONS I need [SL:ANCHOR directions] to [SL:DESTINATION "
+ "[IN:GET_EVENT the jazz festival]]]",
Node(
label="IN:GET_DIRECTIONS",
span=Span(start=0, end=38),
children={
Node(label="SL:ANCHOR", span=Span(start=7, end=17)),
Node(
label="SL:DESTINATION",
span=Span(start=21, end=38),
children={
Node(label="IN:GET_EVENT", span=Span(start=21, end=38))
},
),
},
),
),
]
for annotation_string, expected_frame in TEXT_EXAMPLES:
annotation = Annotation(annotation_string)
frame = CompositionalMetricReporter.tree_to_metric_node(annotation.tree)
self.assertEqual(frame, expected_frame)
def get_frame(parse: str) -> Node:
annotation = Annotation(parse)
frame = CompositionalMetricReporter.tree_to_metric_node(annotation.tree)
return frame