def forward(self, batch, task, tokenizer, compute_loss: bool = False):
with transformer_utils.output_hidden_states_context(self.encoder):
encoder_output = get_output_from_encoder_and_batch(
encoder=self.encoder, batch=batch)
# A tuple of layers of hidden states
hidden_states = take_one(encoder_output.other)
layer_hidden_states = hidden_states[self.layer]
if isinstance(self.pooler_head, heads.MeanPoolerHead):
logits = self.pooler_head(unpooled=layer_hidden_states,
input_mask=batch.input_mask)
elif isinstance(self.pooler_head, heads.FirstPoolerHead):
logits = self.pooler_head(layer_hidden_states)
else:
raise TypeError(type(self.pooler_head))
# TODO: Abuse of notation - these aren't really logits (issue #1187)
if compute_loss:
# TODO: make this optional? (issue #1187)
return LogitsAndLossOutput(
logits=logits,
loss=torch.tensor([0.0]), # This is a horrible hack
other=encoder_output.other,
)
else:
return LogitsOutput(logits=logits, other=encoder_output.other)
def read_examples(self, path, set_type):
input_data = read_json(path, encoding="utf-8")["data"]
is_training = set_type == PHASE.TRAIN
examples = []
data = take_one(input_data)
for paragraph in maybe_tqdm(data["paragraphs"]):
for qa in paragraph["qas"]:
qas_id = qa["id"]
# Because answers can also come from questions, we're going to abuse notation
# slightly and put the entire background+situation+question into the "context"
# and leave nothing for the "question"
question_text = " "
if self.include_background:
context_segments = [
paragraph["background"],
paragraph["situation"],
qa["question"],
]
else:
context_segments = [paragraph["situation"], qa["question"]]
full_context = " ".join(segment.strip()
for segment in context_segments)
if is_training:
answer = qa["answers"][0]
start_position_character = full_context.find(
answer["text"])
answer_text = answer["text"]
answers = []
else:
start_position_character = None
answer_text = None
answers = [{
"text":
answer["text"],
"answer_start":
full_context.find(answer["text"])
} for answer in qa["answers"]]
example = Example(
qas_id=qas_id,
question_text=question_text,
context_text=full_context,
answer_text=answer_text,
start_position_character=start_position_character,
title="",
is_impossible=False,
answers=answers,
background_text=paragraph["background"],
situation_text=paragraph["situation"],
)
examples.append(example)
return examples
def test_take_one():
assert py_datastructures.take_one([9]) == 9
assert py_datastructures.take_one((9, )) == 9
assert py_datastructures.take_one({9}) == 9
assert py_datastructures.take_one("9") == "9"
assert py_datastructures.take_one({9: 10}) == 9
with pytest.raises(IndexError):
py_datastructures.take_one([])
with pytest.raises(IndexError):
py_datastructures.take_one([1, 2])
with pytest.raises(IndexError):
py_datastructures.take_one("2342134")